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Olivier Darné
(Olivier Darne)

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Blog mentions

As found by EconAcademics.org, the blog aggregator for Economics research:
  1. Karim Barhoumi & Olivier Darné & Laurent Ferrara, 2014. "Dynamic factor models: A review of the literature," OECD Journal: Journal of Business Cycle Measurement and Analysis, OECD Publishing, Centre for International Research on Economic Tendency Surveys, vol. 2013(2), pages 73-107.

    Mentioned in:

    1. Guest Contribution: “Nowcasting Global GDP Growth”
      by Menzie Chinn in Econbrowser on 2015-03-12 09:56:18

Wikipedia or ReplicationWiki mentions

(Only mentions on Wikipedia that link back to a page on a RePEc service)
  1. Charles, Amélie & Darné, Olivier, 2019. "Volatility estimation for Bitcoin: Replication and robustness," International Economics, Elsevier, vol. 157(C), pages 23-32.

    Mentioned in:

    1. Volatility estimation for Bitcoin: Replication and robustness (International Economics 2019) in ReplicationWiki ()

Working papers

  1. Amélie Charles & Chew Lian Chua & Olivier Darné & Sandy Suardi, 2020. "On the Pernicious Effects of Oil Price Uncertainty on U.S. Real Economic Activities," Post-Print hal-03040689, HAL.

    Cited by:

    1. Amélie Charles & Chew Lian Chua & Olivier Darné & Sandy Suardi, 2021. "Oil price shocks, real economic activity and uncertainty," Bulletin of Economic Research, Wiley Blackwell, vol. 73(3), pages 364-392, July.
    2. Rosnawintang Rosnawintang & Tajuddin Tajuddin & Pasrun Adam & Yuwanda Purnamasari Pasrun & La Ode Saidi, 2021. "Effects of Crude Oil Prices Volatility, the Internet and Inflation on Economic Growth in ASEAN-5 Countries: A Panel Autoregressive Distributed Lag Approach," International Journal of Energy Economics and Policy, Econjournals, vol. 11(1), pages 15-21.

  2. Olivier Darné & Amélie Charles, 2019. "Volatility estimation for Bitcoin: Replication and robustness," Post-Print hal-01941102, HAL.

    Cited by:

    1. Cheikh, Nidhaleddine Ben & Zaied, Younes Ben & Chevallier, Julien, 2020. "Asymmetric volatility in cryptocurrency markets: New evidence from smooth transition GARCH models," Finance Research Letters, Elsevier, vol. 35(C).
    2. Vahidin Jeleskovic & Mirko Meloni & Zahid Irshad Younas, 2020. "Cryptocurrencies: A Copula Based Approach for Asymmetric Risk Marginal Allocations," MAGKS Papers on Economics 202034, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    3. Bergsli, Lykke Øverland & Lind, Andrea Falk & Molnár, Peter & Polasik, Michał, 2022. "Forecasting volatility of Bitcoin," Research in International Business and Finance, Elsevier, vol. 59(C).
    4. Cristina Chinazzo & Vahidin Jeleskovic, 2024. "Forecasting Bitcoin Volatility: A Comparative Analysis of Volatility Approaches," Papers 2401.02049, arXiv.org.
    5. Roy Cerqueti & Massimiliano Giacalone & Raffaele Mattera, 2020. "Skewed non-Gaussian GARCH models for cryptocurrencies volatility modelling," Papers 2004.11674, arXiv.org.
    6. Zhiyong Tu & Lan Ju, 2019. "A Normative Dual-value Theory for Bitcoin and other Cryptocurrencies," Papers 1904.05028, arXiv.org.
    7. Paola Stolfi & Mauro Bernardi & Davide Vergni, 2022. "Robust estimation of time-dependent precision matrix with application to the cryptocurrency market," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-25, December.
    8. Charfeddine, Lanouar & Benlagha, Noureddine & Maouchi, Youcef, 2020. "Investigating the dynamic relationship between cryptocurrencies and conventional assets: Implications for financial investors," Economic Modelling, Elsevier, vol. 85(C), pages 198-217.
    9. Fakhfekh, Mohamed & Jeribi, Ahmed, 2020. "Volatility dynamics of crypto-currencies’ returns: Evidence from asymmetric and long memory GARCH models," Research in International Business and Finance, Elsevier, vol. 51(C).
    10. Zhang, Wei & Li, Yi, 2020. "Is idiosyncratic volatility priced in cryptocurrency markets?," Research in International Business and Finance, Elsevier, vol. 54(C).
    11. D’Amato, Valeria & Levantesi, Susanna & Piscopo, Gabriella, 2022. "Deep learning in predicting cryptocurrency volatility," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 596(C).
    12. Utku Altunoz, 2023. "Analyzing the Volatility Dynamics of Crypto Currency and the Occurrence of Speculative Bubbles: The Examples of Bitcoin, Ethereum, and Ripple," Istanbul Journal of Economics-Istanbul Iktisat Dergisi, Istanbul University, Faculty of Economics, vol. 73(73-1), pages 615-643, June.
    13. Khanh Hoang & Cuong C. Nguyen & Kongchheng Poch & Thang X. Nguyen, 2020. "Does Bitcoin Hedge Commodity Uncertainty?," JRFM, MDPI, vol. 13(6), pages 1-14, June.
    14. Ahmed, Walid M.A., 2021. "How do Islamic equity markets respond to good and bad volatility of cryptocurrencies? The case of Bitcoin," Pacific-Basin Finance Journal, Elsevier, vol. 70(C).
    15. Catania, Leopoldo & Grassi, Stefano, 2022. "Forecasting cryptocurrency volatility," International Journal of Forecasting, Elsevier, vol. 38(3), pages 878-894.
    16. Sercan Demiralay & Selçuk Bayracı, 2021. "Should stock investors include cryptocurrencies in their portfolios after all? Evidence from a conditional diversification benefits measure," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(4), pages 6188-6204, October.
    17. José Antonio Núñez-Mora & Mario Iván Contreras-Valdez & Roberto Joaquín Santillán-Salgado, 2023. "Risk Premium of Bitcoin and Ethereum during the COVID-19 and Non-COVID-19 Periods: A High-Frequency Approach," Mathematics, MDPI, vol. 11(20), pages 1-20, October.
    18. Nikolaos A. Kyriazis, 2021. "A Survey on Volatility Fluctuations in the Decentralized Cryptocurrency Financial Assets," JRFM, MDPI, vol. 14(7), pages 1-46, June.
    19. Demiralay, Sercan & Golitsis, Petros, 2021. "On the dynamic equicorrelations in cryptocurrency market," The Quarterly Review of Economics and Finance, Elsevier, vol. 80(C), pages 524-533.
    20. Pinar Deniz & Thanasis Stengos, 2020. "Cryptocurrency Returns before and after the Introduction of Bitcoin Futures," JRFM, MDPI, vol. 13(6), pages 1-21, June.

  3. Amélie Charles & Olivier Darné, 2019. "Volatility estimation for cryptocurrencies: Further evidence with jumps and structural breaks," Post-Print hal-03794543, HAL.

    Cited by:

    1. OlaOluwa S. Yaya & Ahamuefula E. Ogbonna & Robert Mudida & Nuruddeen Abu, 2021. "Market efficiency and volatility persistence of cryptocurrency during pre‐ and post‐crash periods of Bitcoin: Evidence based on fractional integration," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(1), pages 1318-1335, January.
    2. Cristina Chinazzo & Vahidin Jeleskovic, 2024. "Forecasting Bitcoin Volatility: A Comparative Analysis of Volatility Approaches," Papers 2401.02049, arXiv.org.
    3. Walid Chkili, 2021. "Modeling Bitcoin price volatility: long memory vs Markov switching," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 11(3), pages 433-448, September.
    4. Fan Fang & Carmine Ventre & Michail Basios & Leslie Kanthan & David Martinez-Rego & Fan Wu & Lingbo Li, 2022. "Cryptocurrency trading: a comprehensive survey," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-59, December.
    5. Abakah, Emmanuel Joel Aikins & Gil-Alana, Luis Alberiko & Madigu, Godfrey & Romero-Rojo, Fatima, 2020. "Volatility persistence in cryptocurrency markets under structural breaks," International Review of Economics & Finance, Elsevier, vol. 69(C), pages 680-691.
    6. Ahmed M. Khedr & Ifra Arif & Pravija Raj P V & Magdi El‐Bannany & Saadat M. Alhashmi & Meenu Sreedharan, 2021. "Cryptocurrency price prediction using traditional statistical and machine‐learning techniques: A survey," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 28(1), pages 3-34, January.

  4. Amélie Charles & Olivier Darné & Jean-François Hoarau, 2019. "How resilient is La Réunion in terms of international tourism attractiveness: an assessment from unit root tests with structural breaks from 1981-2015," Post-Print hal-02053296, HAL.

    Cited by:

    1. Jean-François Hoarau, 2020. "Is international tourism responsible for the pandemic of COVID-19? A very preliminary assessment with a special focus on small islands," Economics Bulletin, AccessEcon, vol. 40(3), pages 2395-2407.
    2. Jennifer C. H. MIN & Hsien-Hung KUNG & Tsangyao CHANG, 2019. "Testing the Structural Break of Taiwan Inbound Tourism Markets," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(2), pages 117-130, June.
    3. Jean-François Hoarau, 2020. "Is international tourism responsible for the pandemic of COVID-19? A preliminary cross-country analysis with a special focus on small islands," TEPP Working Paper 2020-04, TEPP.
    4. Jean-François Hoarau, 2022. "Is international tourism responsible for the outbreak of the COVID-19 pandemic? A cross-country analysis with a special focus on small islands," Review of World Economics (Weltwirtschaftliches Archiv), Springer;Institut für Weltwirtschaft (Kiel Institute for the World Economy), vol. 158(2), pages 493-528, May.
    5. James E Payne & Junsoo Lee, 2024. "Global perspective on the permanent or transitory nature of shocks to tourist arrivals: Evidence from new unit root tests with structural breaks and factors," Tourism Economics, , vol. 30(1), pages 67-103, February.

  5. Olivier Darné & Laurent Ferrara & Dominique Ladiray, 2018. "A Brief History of Seasonal Adjustment Methods and Software Tools," Post-Print hal-03754072, HAL.

    Cited by:

    1. Simone di Paolo & Danilo Liberati, 2024. "Seasonal adjustment of credit time series in the Bank of Italy," Questioni di Economia e Finanza (Occasional Papers) 835, Bank of Italy, Economic Research and International Relations Area.

  6. Amélie Charles & Olivier Darné, 2017. "Forecasting crude-oil market volatility: Further evidence with jumps," Post-Print hal-01598141, HAL.

    Cited by:

    1. Gong, Xu & Lin, Boqiang, 2018. "The incremental information content of investor fear gauge for volatility forecasting in the crude oil futures market," Energy Economics, Elsevier, vol. 74(C), pages 370-386.
    2. Mohamed Chikhi & Claude Diebolt & Tapas Mishra, 2019. "Measuring Success: Does Predictive Ability of an Asset Price Rest in 'Memory'? Insights from a New Approach," Working Papers 11-19, Association Française de Cliométrie (AFC).
    3. Li, Mingchen & Cheng, Zishu & Lin, Wencan & Wei, Yunjie & Wang, Shouyang, 2023. "What can be learned from the historical trend of crude oil prices? An ensemble approach for crude oil price forecasting," Energy Economics, Elsevier, vol. 123(C).
    4. Scarcioffolo, Alexandre R. & Etienne, Xiaoli L., 2021. "Regime-switching energy price volatility: The role of economic policy uncertainty," International Review of Economics & Finance, Elsevier, vol. 76(C), pages 336-356.
    5. Chatziantoniou, Ioannis & Degiannakis, Stavros & Filis, George, 2019. "Futures-based forecasts: How useful are they for oil price volatility forecasting?," Energy Economics, Elsevier, vol. 81(C), pages 639-649.
    6. Mohamed Chikhi & Claude Diebolt & Tapas Mishra, 2019. "Memory that Drives! New Insights into Forecasting Performance of Stock Prices from SEMIFARMA-AEGAS Model," Working Papers of BETA 2019-24, Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg.
    7. Sherzod N. Tashpulatov, 2022. "Modeling Electricity Price Dynamics Using Flexible Distributions," Mathematics, MDPI, vol. 10(10), pages 1-15, May.
    8. Jo-Hui & Chen & Sabbor Hussain, 2022. "Jump Dynamics and Leverage Effect: Evidences from Energy Exchange Traded Fund (ETFs)," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 12(6), pages 1-7.
    9. Wei Kuang, 2022. "Oil tail-risk forecasts: from financial crisis to COVID-19," Risk Management, Palgrave Macmillan, vol. 24(4), pages 420-460, December.
    10. Frantiv{s}ek v{C}ech & Jozef Barun'ik, 2018. "Panel quantile regressions for estimating and predicting the Value--at--Risk of commodities," Papers 1807.11823, arXiv.org.
    11. Hasanov, Akram Shavkatovich & Shaiban, Mohammed Sharaf & Al-Freedi, Ajab, 2020. "Forecasting volatility in the petroleum futures markets: A re-examination and extension," Energy Economics, Elsevier, vol. 86(C).
    12. Arturo Lorenzo-Valdés, 2021. "Conditional Probability of Jumps in Oil Prices," Remef - Revista Mexicana de Economía y Finanzas Nueva Época REMEF (The Mexican Journal of Economics and Finance), Instituto Mexicano de Ejecutivos de Finanzas, IMEF, vol. 16(4), pages 1-14, Octubre -.
    13. Bei, Shuhua & Yang, Aijun & Pei, Haotian & Si, Xiaoli, 2023. "Price Risk Analysis using GARCH Family Models: Evidence from Shanghai Crude Oil Futures Market," Economic Modelling, Elsevier, vol. 125(C).
    14. Chai, Jian & Xing, Li-Min & Zhou, Xiao-Yang & Zhang, Zhe George & Li, Jie-Xun, 2018. "Forecasting the WTI crude oil price by a hybrid-refined method," Energy Economics, Elsevier, vol. 71(C), pages 114-127.
    15. Markus Vogl, 2022. "Quantitative modelling frontiers: a literature review on the evolution in financial and risk modelling after the financial crisis (2008–2019)," SN Business & Economics, Springer, vol. 2(12), pages 1-69, December.
    16. Ding, Shusheng & Cui, Tianxiang & Zhang, Yongmin, 2022. "Futures volatility forecasting based on big data analytics with incorporating an order imbalance effect," International Review of Financial Analysis, Elsevier, vol. 83(C).
    17. Xiafei Li & Dongxin Li & Xuhui Zhang & Guiwu Wei & Lan Bai & Yu Wei, 2021. "Forecasting regular and extreme gold price volatility: The roles of asymmetry, extreme event, and jump," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(8), pages 1501-1523, December.
    18. Fen Li & Zhehao Huang & Junhao Zhong & Khaldoon Albitar, 2020. "Do Tense Geopolitical Factors Drive Crude Oil Prices?," Energies, MDPI, vol. 13(16), pages 1-20, August.
    19. Sherzod N. Tashpulatov, 2021. "Modeling and Estimating Volatility of Day-Ahead Electricity Prices," Mathematics, MDPI, vol. 9(7), pages 1-11, March.
    20. Mohamed CHIKHI & Claude DIEBOLT & Tapas MISHRA, 2019. "Does Predictive Ability of an Asset Price Rest in 'Memory'? Insights from a New Approach," Working Papers of BETA 2019-43, Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg.
    21. Zhao, Jing, 2022. "Exploring the influence of the main factors on the crude oil price volatility: An analysis based on GARCH-MIDAS model with Lasso approach," Resources Policy, Elsevier, vol. 79(C).
    22. Gong, Xu & Guan, Keqin & Chen, Liqing & Liu, Tangyong & Fu, Chengbo, 2021. "What drives oil prices? — A Markov switching VAR approach," Resources Policy, Elsevier, vol. 74(C).
    23. Gong, Xu & Chen, Liqiang & Lin, Boqiang, 2020. "Analyzing dynamic impacts of different oil shocks on oil price," Energy, Elsevier, vol. 198(C).
    24. Lu, Quanying & Li, Yuze & Chai, Jian & Wang, Shouyang, 2020. "Crude oil price analysis and forecasting: A perspective of “new triangle”," Energy Economics, Elsevier, vol. 87(C).
    25. Jiqian Wang & Feng Ma & M.I.M. Wahab & Dengshi Huang, 2021. "Forecasting China's Crude Oil Futures Volatility: The Role of the Jump, Jumps Intensity, and Leverage Effect," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(5), pages 921-941, August.
    26. Chen, Rongda & Bao, Weiwei & Jin, Chenglu, 2021. "Investor sentiment and predictability for volatility on energy futures Markets: Evidence from China," International Review of Economics & Finance, Elsevier, vol. 75(C), pages 112-129.
    27. Dondukova Oyuna & Liu Yaobin, 2021. "Forecasting the Crude Oil Prices Volatility With Stochastic Volatility Models," SAGE Open, , vol. 11(3), pages 21582440211, July.
    28. Yingying Xu & Donald Lien, 2022. "Forecasting volatilities of oil and gas assets: A comparison of GAS, GARCH, and EGARCH models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(2), pages 259-278, March.
    29. Kais Tissaoui & Taha Zaghdoudi & Abdelaziz Hakimi & Mariem Nsaibi, 2023. "Do Gas Price and Uncertainty Indices Forecast Crude Oil Prices? Fresh Evidence Through XGBoost Modeling," Computational Economics, Springer;Society for Computational Economics, vol. 62(2), pages 663-687, August.
    30. Sherzod N. Tashpulatov, 2021. "The Impact of Regulatory Reforms on Demand Weighted Average Prices," Mathematics, MDPI, vol. 9(10), pages 1-15, May.
    31. Kais Tissaoui & Taha Zaghdoudi & Abdelaziz Hakimi & Ousama Ben-Salha & Lamia Ben Amor, 2022. "Does Uncertainty Forecast Crude Oil Volatility before and during the COVID-19 Outbreak? Fresh Evidence Using Machine Learning Models," Energies, MDPI, vol. 15(15), pages 1-20, August.
    32. Bonnier, Jean-Baptiste, 2022. "Forecasting crude oil volatility with exogenous predictors: As good as it GETS?," Energy Economics, Elsevier, vol. 111(C).
    33. Elie Bouri, 2019. "The Effect of Jumps in the Crude Oil Market on the Sovereign Risks of Major Oil Exporters," Risks, MDPI, vol. 7(4), pages 1-15, December.
    34. Hasanov, Akram Shavkatovich & Poon, Wai Ching & Al-Freedi, Ajab & Heng, Zin Yau, 2018. "Forecasting volatility in the biofuel feedstock markets in the presence of structural breaks: A comparison of alternative distribution functions," Energy Economics, Elsevier, vol. 70(C), pages 307-333.
    35. Ma, Feng & Zhang, Yaojie & Huang, Dengshi & Lai, Xiaodong, 2018. "Forecasting oil futures price volatility: New evidence from realized range-based volatility," Energy Economics, Elsevier, vol. 75(C), pages 400-409.
    36. Chen, Yixiang & Ma, Feng & Zhang, Yaojie, 2019. "Good, bad cojumps and volatility forecasting: New evidence from crude oil and the U.S. stock markets," Energy Economics, Elsevier, vol. 81(C), pages 52-62.

  7. Amélie Charles & Olivier Darné & Fabien Tripier, 2017. "Uncertainty and the Macroeconomy: Evidence from an Uncertainty Composite Indicator," Working Papers 2017-25, CEPII research center.

    Cited by:

    1. Hristov, Nikolay & Roth, Markus, 2019. "Uncertainty shocks and financial crisis indicators," Discussion Papers 36/2019, Deutsche Bundesbank.
    2. Zied Ftiti & Fredj Jawadi, 2019. "Forecasting Inflation Uncertainty in the United States and Euro Area," Computational Economics, Springer;Society for Computational Economics, vol. 54(1), pages 455-476, June.
    3. Francisco Serranito & Nicolas Himounet & Julien Vauday, 2023. "Uncertainty is bad for Business. Really?," Working Papers hal-04219283, HAL.
    4. Hippolyte d'Albis & Ekrame Boubtane & Dramane Coulibaly, 2022. "Global Uncertainty and International Migration to Western Europe," PSE Working Papers halshs-03770391, HAL.
    5. Mei-Chih Wang & Pao-Lan Kuo & Chan-Sheng Chen & Chien-Liang Chiu & Tsangyao Chang, 2020. "Yield Spread and Economic Policy Uncertainty: Evidence from Japan," Sustainability, MDPI, vol. 12(10), pages 1-14, May.
    6. Selmi, Refk & Bouoiyour, Jamal & Wohar, Mark E., 2022. "“Digital Gold” and geopolitics," Research in International Business and Finance, Elsevier, vol. 59(C).
    7. Nicolas Himounet, 2021. "Searching for the Nature of Uncertainty: Macroeconomic VS Financial," Working Papers 2021.05, International Network for Economic Research - INFER.
    8. Oscar Claveria, 2020. "Measuring and assessing economic uncertainty," IREA Working Papers 202011, University of Barcelona, Research Institute of Applied Economics, revised Jul 2020.
    9. Yingting Yi & Jiangshui Luo & Michael Wübbenhorst, 2020. "Research on political instability, uncertainty and risk during 1953–2019: a scientometric review," Scientometrics, Springer;Akadémiai Kiadó, vol. 123(2), pages 1051-1076, May.
    10. Dang, Tam Hoang-Nhat & Nguyen, Canh Phuc & Lee, Gabriel S. & Nguyen, Binh Quang & Le, Thuy Thu, 2023. "Measuring the energy-related uncertainty index," Energy Economics, Elsevier, vol. 124(C).
    11. Matheus Pereira Libório & Petr Iakovlevitch Ekel & Carlos Augusto Paiva Martins, 2023. "Economic analysis through alternative data and big data techniques: what do they tell about Brazil?," SN Business & Economics, Springer, vol. 3(1), pages 1-16, January.
    12. Jamal Bouoiyour & Refk Selmi & Mark Wohar, 2018. "Measuring the response of gold prices to uncertainty: An analysis beyond the mean," Post-Print hal-01817067, HAL.
    13. Oscar Claveria, 2021. "Uncertainty indicators based on expectations of business and consumer surveys," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 48(2), pages 483-505, May.
    14. Oscar Claveria, 2021. "On the Aggregation of Survey-Based Economic Uncertainty Indicators Between Different Agents and Across Variables," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 17(1), pages 1-26, April.
    15. Tihana Škrinjarić, 2023. "Credit-to-GDP Gap Estimates in Real Time: A Stable Indicator for Macroprudential Policy Making in Croatia," Comparative Economic Studies, Palgrave Macmillan;Association for Comparative Economic Studies, vol. 65(3), pages 582-614, September.
    16. Corinna Ghirelli & María Gil & Javier J. Pérez & Alberto Urtasun, 2021. "Measuring economic and economic policy uncertainty and their macroeconomic effects: the case of Spain," Empirical Economics, Springer, vol. 60(2), pages 869-892, February.
    17. Hristov, Nikolay & Roth, Markus, 2022. "Uncertainty shocks and systemic-risk indicators," Journal of International Money and Finance, Elsevier, vol. 122(C).
    18. Cagli, Efe Caglar & Mandaci, Pinar Evrim, 2023. "Time and frequency connectedness of uncertainties in cryptocurrency, stock, currency, energy, and precious metals markets," Emerging Markets Review, Elsevier, vol. 55(C).
    19. Matheus Pereira Libório & Lívia Maria Leite Silva & Petr Iakovlevitch Ekel & Letícia Ribeiro Figueiredo & Patrícia Bernardes, 2022. "Consensus-Based Sub-Indicator Weighting Approach: Constructing Composite Indicators Compatible with Expert Opinion," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 164(3), pages 1073-1099, December.
    20. Ding, Yibing & Liu, Ziyu & Liu, Dayu, 2022. "Structural news shock, financial market uncertainty and China's business fluctuations," Pacific-Basin Finance Journal, Elsevier, vol. 76(C).
    21. Bartsch, Zachary, 2019. "Economic policy uncertainty and dollar-pound exchange rate return volatility," Journal of International Money and Finance, Elsevier, vol. 98(C), pages 1-1.
    22. Ömer YALÇINKAYA & Muhammet DAŞTAN, 2020. "Effects of Global Economic, Political and Geopolitical Uncertainties on the Turkish Economy: A SVAR Analysis," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(1), pages 97-116, March.
    23. Oscar Claveria, 2021. "Disagreement on expectations: firms versus consumers," SN Business & Economics, Springer, vol. 1(12), pages 1-23, December.

  8. Amélie Charles & Olivier Darné & Jae H Kim, 2017. "International Stock Return Predictability: Evidence from New Statistical Tests," Post-Print hal-01626101, HAL.

    Cited by:

    1. Li, Xiyang & Chen, Xiaoyue & Li, Bin & Singh, Tarlok & Shi, Kan, 2022. "Predictability of stock market returns: New evidence from developed and developing countries," Global Finance Journal, Elsevier, vol. 54(C).
    2. Theologos Dergiades & Panos K. Pouliasis, 2021. "Should Stock Returns Predictability be hooked on Long Horizon Regressions?," Discussion Paper Series 2021_03, Department of Economics, University of Macedonia, revised Feb 2021.
    3. Xu, Yongan & Wang, Jianqiong & Chen, Zhonglu & Liang, Chao, 2021. "Economic policy uncertainty and stock market returns: New evidence," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).
    4. Yin, Anwen, 2020. "Equity premium prediction and optimal portfolio decision with Bagging," The North American Journal of Economics and Finance, Elsevier, vol. 54(C).
    5. Dahmene, Meriam & Boughrara, Adel & Slim, Skander, 2021. "Nonlinearity in stock returns: Do risk aversion, investor sentiment and, monetary policy shocks matter?," International Review of Economics & Finance, Elsevier, vol. 71(C), pages 676-699.
    6. Jurdi, Doureige J., 2022. "Predicting the Australian equity risk premium," Pacific-Basin Finance Journal, Elsevier, vol. 71(C).
    7. Yin, Anwen, 2019. "Out-of-sample equity premium prediction in the presence of structural breaks," International Review of Financial Analysis, Elsevier, vol. 65(C).
    8. Zhang, Yaojie & Wei, Yu & Ma, Feng & Yi, Yongsheng, 2019. "Economic constraints and stock return predictability: A new approach," International Review of Financial Analysis, Elsevier, vol. 63(C), pages 1-9.

  9. Amélie Charles & Olivier Darné & Fabien Tripier, 2017. "Uncertainty and the Macroeconomy," Post-Print hal-01549625, HAL.

    Cited by:

    1. Laurent Ferrara & Stéphane Lhuissier & Fabien Tripier, 2018. "Uncertainty Fluctuations: Measures, Effects and Macroeconomic Policy Challenges," Financial and Monetary Policy Studies, in: Laurent Ferrara & Ignacio Hernando & Daniela Marconi (ed.), International Macroeconomics in the Wake of the Global Financial Crisis, pages 159-181, Springer.
    2. Jamal Bouoiyour & Refk Selmi & Mark Wohar, 2018. "Measuring the response of gold prices to uncertainty: An analysis beyond the mean," Post-Print hal-01817067, HAL.

  10. Amélie Charles & Olivier Darné & Jae H Kim, 2017. "Adaptive markets hypothesis for Islamic stock indices: Evidence from Dow Jones size and sector-indices," Post-Print hal-01579718, HAL.

    Cited by:

    1. Ozkan, Oktay, 2021. "Impact of COVID-19 on stock market efficiency: Evidence from developed countries," Research in International Business and Finance, Elsevier, vol. 58(C).
    2. Ashok Chanabasangouda Patil & Shailesh Rastogi, 2019. "Time-Varying Price–Volume Relationship and Adaptive Market Efficiency: A Survey of the Empirical Literature," JRFM, MDPI, vol. 12(2), pages 1-18, June.
    3. Karim, Muhammad Mahmudul & Kawsar, Najmul Haque & Ariff, Mohamed & Masih, Mansur, 2022. "Does implied volatility (or fear index) affect Islamic stock returns and conventional stock returns differently? Wavelet-based granger-causality, asymmetric quantile regression and NARDL approaches," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 77(C).
    4. Uddin, Gazi Salah & Hernandez, Jose Areola & Shahzad, Syed Jawad Hussain & Yoon, Seong-Min, 2018. "Time-varying evidence of efficiency, decoupling, and diversification of conventional and Islamic stocks," International Review of Financial Analysis, Elsevier, vol. 56(C), pages 167-180.
    5. Salisu, Afees A. & Ndako, Umar B. & Adediran, Idris A. & Swaray, Raymond, 2020. "A fractional cointegration VAR analysis of Islamic stocks: A global perspective," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
    6. Hill, Jonathan B. & Motegi, Kaiji, 2019. "Testing the white noise hypothesis of stock returns," Economic Modelling, Elsevier, vol. 76(C), pages 231-242.
    7. Oktay Ozkan, 2020. "Time-varying return predictability and adaptive markets hypothesis: Evidence on MIST countries from a novel wild bootstrap likelihood ratio approach," Bogazici Journal, Review of Social, Economic and Administrative Studies, Bogazici University, Department of Economics, vol. 34(2), pages 101-113.
    8. Ferreira, Joaquim & Morais, Flávio, 2023. "Predict or to be predicted? A transfer entropy view between adaptive green markets, structural shocks and sentiment index," Finance Research Letters, Elsevier, vol. 56(C).
    9. Sherif, Mohamed, 2020. "The impact of Coronavirus (COVID-19) outbreak on faith-based investments: An original analysis," Journal of Behavioral and Experimental Finance, Elsevier, vol. 28(C).
    10. Al-Yahyaee, Khamis Hamed & Mensi, Walid & Rehman, Mobeen Ur & Vo, Xuan Vinh & Kang, Sang Hoon, 2020. "Do Islamic stocks outperform conventional stock sectors during normal and crisis periods? Extreme co-movements and portfolio management analysis," Pacific-Basin Finance Journal, Elsevier, vol. 62(C).
    11. Muhammad Shehryar & Furrukh Bashir & Kashif Raza & Rashid Ahmad, 2022. "Random Walk Hypothesis: An Empirical Comparison of Shari’ah and Non-Shari’ah Capital Markets of Pakistan and China," iRASD Journal of Economics, International Research Alliance for Sustainable Development (iRASD), vol. 4(3), pages 439-447, September.

  11. Amélie Charles & Olivier Darné & Jae H Kim, 2017. "Adaptive Markets Hypothesis for Islamic Stock Portfolios: Evidence from Dow Jones Size and Sector-Indices," Post-Print hal-01526483, HAL.

    Cited by:

    1. Ozkan, Oktay, 2021. "Impact of COVID-19 on stock market efficiency: Evidence from developed countries," Research in International Business and Finance, Elsevier, vol. 58(C).
    2. Ashok Chanabasangouda Patil & Shailesh Rastogi, 2019. "Time-Varying Price–Volume Relationship and Adaptive Market Efficiency: A Survey of the Empirical Literature," JRFM, MDPI, vol. 12(2), pages 1-18, June.
    3. Karim, Muhammad Mahmudul & Kawsar, Najmul Haque & Ariff, Mohamed & Masih, Mansur, 2022. "Does implied volatility (or fear index) affect Islamic stock returns and conventional stock returns differently? Wavelet-based granger-causality, asymmetric quantile regression and NARDL approaches," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 77(C).
    4. Uddin, Gazi Salah & Hernandez, Jose Areola & Shahzad, Syed Jawad Hussain & Yoon, Seong-Min, 2018. "Time-varying evidence of efficiency, decoupling, and diversification of conventional and Islamic stocks," International Review of Financial Analysis, Elsevier, vol. 56(C), pages 167-180.
    5. Hill, Jonathan B. & Motegi, Kaiji, 2019. "Testing the white noise hypothesis of stock returns," Economic Modelling, Elsevier, vol. 76(C), pages 231-242.
    6. Oktay Ozkan, 2020. "Time-varying return predictability and adaptive markets hypothesis: Evidence on MIST countries from a novel wild bootstrap likelihood ratio approach," Bogazici Journal, Review of Social, Economic and Administrative Studies, Bogazici University, Department of Economics, vol. 34(2), pages 101-113.
    7. Sherif, Mohamed, 2020. "The impact of Coronavirus (COVID-19) outbreak on faith-based investments: An original analysis," Journal of Behavioral and Experimental Finance, Elsevier, vol. 28(C).
    8. Al-Yahyaee, Khamis Hamed & Mensi, Walid & Rehman, Mobeen Ur & Vo, Xuan Vinh & Kang, Sang Hoon, 2020. "Do Islamic stocks outperform conventional stock sectors during normal and crisis periods? Extreme co-movements and portfolio management analysis," Pacific-Basin Finance Journal, Elsevier, vol. 62(C).
    9. Muhammad Shehryar & Furrukh Bashir & Kashif Raza & Rashid Ahmad, 2022. "Random Walk Hypothesis: An Empirical Comparison of Shari’ah and Non-Shari’ah Capital Markets of Pakistan and China," iRASD Journal of Economics, International Research Alliance for Sustainable Development (iRASD), vol. 4(3), pages 439-447, September.

  12. Laurent Ferrara & Olivier Darné & Karim Barhoumi, 2016. "A world trade leading index (WLTI)," Post-Print hal-01635948, HAL.

    Cited by:

    1. Jaime Martínez-Martín & Elena Rusticelli, 2020. "Keeping track of global trade in real time," Working Papers 2019, Banco de España.
    2. Amélie Charles & Olivier Darné, 2022. "Backcasting world trade growth using data reduction methods," The World Economy, Wiley Blackwell, vol. 45(10), pages 3169-3191, October.
    3. Chinn Menzie & Meunier Baptiste & Stumpner Sebastian, 2023. "Nowcasting world trade in real time with machine learning [Estimation du commerce mondial en temps réel grâce à l’apprentissage automatique]," Bulletin de la Banque de France, Banque de France, issue 248.
    4. Çiðdem Kurt Cihangir, 2018. "Küresel Risk Algýsýnýn Küresel Ticaret Üzerindeki Etkisi," Isletme ve Iktisat Calismalari Dergisi, Econjournals, vol. 6(1), pages 1-10.

  13. Amélie Charles & Olivier Darné, 2016. "Stock market reactions to FIFA World Cup announcements: An event study," Post-Print hal-01395333, HAL.

    Cited by:

    1. Harjito, Dwipraptono Agus & Alam, Md. Mahmudul & Dewi, Rani Ayu Kusuma, 2021. "Impacts of International Sports Events on the Stock Market: Evidence from the Announcement of the 18th Asian Games and 30th Southeast Asian Games," OSF Preprints 4dgne, Center for Open Science.
    2. Steffen Hundt & Andreas Horsch, 2019. "Sponsorship of the FIFA world cup, shareholder wealth, and the impact of corruption," Applied Economics, Taylor & Francis Journals, vol. 51(23), pages 2468-2491, May.

  14. Amélie Charles & Olivier Darné & Jae H. Kim & Etienne Redor, 2016. "Stock Exchange Mergers and Market," Post-Print hal-01238707, HAL.

    Cited by:

    1. Li, Shaofang & Marinč, Matej, 2018. "Economies of scale and scope in financial market infrastructures," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 53(C), pages 17-49.

  15. Amélie Charles & Olivier Darné & Jessica Fouilloux, 2016. "The impact of screening strategies on the performance of ESG indices," Working Papers hal-01344699, HAL.

    Cited by:

    1. Borja Diez-Cañamero & Tania Bishara & Jose Ramon Otegi-Olaso & Rikardo Minguez & José María Fernández, 2020. "Measurement of Corporate Social Responsibility: A Review of Corporate Sustainability Indexes, Rankings and Ratings," Sustainability, MDPI, vol. 12(5), pages 1-36, March.

  16. Amélie Charles & Olivier Darné, 2015. "Are the Islamic indexes size or sector oriented? evidence from Dow Jones Islamic indexes," Post-Print hal-01330467, HAL.

    Cited by:

    1. Yildiz Selim & Abdelbari El Khamlichi, 2017. "The Performance Ranking of Emerging Markets Islamic Indices Using Risk Adjusted Performance Measures," Post-Print hal-01653400, HAL.
    2. Abdelbari El Khamlichi & Thi Hong Van Hoang & Wing‐keung Wong, 2016. "Is Gold Different for Islamic and Conventional Portfolios? A Sectorial Analysis," Post-Print hal-02964594, HAL.
    3. Biancone, Paolo Pietro & Radwan, Maha, 2018. "Sharia-Compliant financing for public utility infrastructure," Utilities Policy, Elsevier, vol. 52(C), pages 88-94.
    4. Hoang, Thi-Hong-Van & Zhu, Zhenzhen & El Khamlichi, Abdelbari & Wong, Wing-Keung, 2019. "Does the Shari’ah screening impact the gold-stock nexus? A sectorial analysis," Resources Policy, Elsevier, vol. 61(C), pages 617-626.
    5. Trichilli, Yousra & Abbes, Mouna Boujelbène & Masmoudi, Afif, 2020. "Islamic and conventional portfolios optimization under investor sentiment states: Bayesian vs Markowitz portfolio analysis," Research in International Business and Finance, Elsevier, vol. 51(C).
    6. Delle Foglie, Andrea & Panetta, Ida Claudia, 2020. "Islamic stock market versus conventional: Are islamic investing a ‘Safe Haven’ for investors? A systematic literature review," Pacific-Basin Finance Journal, Elsevier, vol. 64(C).

  17. Amélie Charles & Olivier Darné & Adrian Pop, 2015. "Risk and ethical investment: Empirical evidence from Dow Jones Islamic indexes," Post-Print hal-01153899, HAL.

    Cited by:

    1. El Mehdi, Imen Khanchel & Mghaieth, Asma, 2017. "Volatility spillover and hedging strategies between Islamic and conventional stocks in the presence of asymmetry and long memory," Research in International Business and Finance, Elsevier, vol. 39(PA), pages 595-611.
    2. Khan, Salman & Azmat, Saad, 2020. "Debt externality in equity markets: Leveraged portfolios and Islamic indices," International Review of Economics & Finance, Elsevier, vol. 69(C), pages 152-177.
    3. Camgöz, Mevlüt & Topal, Mehmet Hanefi, 2022. "Identifying the asymmetric price dynamics of Islamic equities: Implications for international investors," Research in International Business and Finance, Elsevier, vol. 60(C).
    4. Khelifa Mazouz & Abdulkadir Mohamed & Brahim Saadouni, 2019. "Price Reaction of Ethically Screened Stocks: A Study of the Dow Jones Islamic Market World Index," Journal of Business Ethics, Springer, vol. 154(3), pages 683-699, February.
    5. Amélie Charles & Olivier Darné & Jae H Kim, 2017. "Adaptive Markets Hypothesis for Islamic Stock Portfolios: Evidence from Dow Jones Size and Sector-Indices," Post-Print hal-01526483, HAL.
    6. Alkhazali, Osamah M. & Zoubi, Taisier A., 2020. "Gold and portfolio diversification: A stochastic dominance analysis of the Dow Jones Islamic indices," Pacific-Basin Finance Journal, Elsevier, vol. 60(C).
    7. Azad, A.S.M.S. & Azmat, Saad & Chazi, Abdelaziz & Ahsan, Amirul, 2018. "Sailing with the non-conventional stocks when there is no place to hide," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 57(C), pages 1-16.
    8. Amélie Charles & Olivier Darné & Jae H Kim, 2017. "Adaptive markets hypothesis for Islamic stock indices: Evidence from Dow Jones size and sector-indices," Post-Print hal-01579718, HAL.
    9. Umar, Zaghum, 2017. "Islamic vs conventional equities in a strategic asset allocation framework," Pacific-Basin Finance Journal, Elsevier, vol. 42(C), pages 1-10.
    10. Maghyereh, Aktham I. & Awartani, Basel, 2016. "Dynamic transmissions between Sukuk and bond markets," Research in International Business and Finance, Elsevier, vol. 38(C), pages 246-261.
    11. Bahrawar Said & Shafiq Ur Rehman & Muhammad Wajid Raza, 2022. "Three Major Crises and Asian Emerging Market Informational Efficiency: A Case of Pakistan Stock Exchange-100 Index," JRFM, MDPI, vol. 15(12), pages 1-13, December.
    12. Naeem, Muhammad Abubakr & Qureshi, Fiza & Arif, Muhammad & Balli, Faruk, 2021. "Asymmetric relationship between gold and Islamic stocks in bearish, normal and bullish market conditions," Resources Policy, Elsevier, vol. 72(C).
    13. Trabelsi, Nader & Naifar, Nader, 2017. "Are Islamic stock indexes exposed to systemic risk? Multivariate GARCH estimation of CoVaR," Research in International Business and Finance, Elsevier, vol. 42(C), pages 727-744.
    14. Raza, Naveed & Ibrahimy, Ahmad & Ali, Azwadi, 2015. "Gold and Islamic Stocks: A Hedge and Safe Haven Comparison in Time - Grequency domain for BRICS," MPRA Paper 69366, University Library of Munich, Germany.
    15. Boudt, Kris & Raza, Muhammad Wajid & Wauters, Marjan, 2019. "Evaluating the Shariah-compliance of equity portfolios: The weighting method matters," International Review of Financial Analysis, Elsevier, vol. 63(C), pages 406-417.
    16. Rida Ahroum & Boujemâa Achchab, 2021. "Harvesting Islamic risk premium with long–short strategies: A time scale decomposition using the wavelet theory," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(1), pages 430-444, January.
    17. Imed Medhioub & Mustapha Chaffai, 2019. "Islamic Finance and Herding Behavior Theory: A Sectoral Analysis for Gulf Islamic Stock Market," IJFS, MDPI, vol. 7(4), pages 1-11, November.
    18. Godil, Danish Iqbal & Sarwat, Salman & Khan, Muhammad Kamran & Ashraf, Muhammad Sajjad & Sharif, Arshian & Ozturk, Ilhan, 2022. "How the price dynamics of energy resources and precious metals interact with conventional and Islamic Stocks: Fresh insight from dynamic ARDL approach," Resources Policy, Elsevier, vol. 75(C).
    19. Sherif, Mohamed, 2020. "The impact of Coronavirus (COVID-19) outbreak on faith-based investments: An original analysis," Journal of Behavioral and Experimental Finance, Elsevier, vol. 28(C).
    20. Maghyereh, Aktham I. & Abdoh, Hussein & Awartani, Basel, 2019. "Connectedness and hedging between gold and Islamic securities: A new evidence from time-frequency domain approaches," Pacific-Basin Finance Journal, Elsevier, vol. 54(C), pages 13-28.
    21. Alhomaidi, Asem & Hassan, M. Kabir & Hippler, William J. & Mamun, Abdullah, 2019. "The impact of religious certification on market segmentation and investor recognition," Journal of Corporate Finance, Elsevier, vol. 55(C), pages 28-48.
    22. Asem Alhomaidi & M. Kabir Hassan & William J. Hippler, 2018. "The Effect of Implicit Market Barriers on Stock Trading and Liquidity," NFI Working Papers 2018-WP-02, Indiana State University, Scott College of Business, Networks Financial Institute.
    23. Trichilli, Yousra & Abbes, Mouna Boujelbène & Masmoudi, Afif, 2020. "Islamic and conventional portfolios optimization under investor sentiment states: Bayesian vs Markowitz portfolio analysis," Research in International Business and Finance, Elsevier, vol. 51(C).
    24. Zaghum Umar & Tahir Suleman, 2017. "Asymmetric Return and Volatility Transmission in Conventional and Islamic Equities," Risks, MDPI, vol. 5(2), pages 1-18, March.
    25. Haddad, Hedi Ben & Mezghani, Imed & Al Dohaiman, Mohammed, 2020. "Common shocks, common transmission mechanisms and time-varying connectedness among Dow Jones Islamic stock market indices and global risk factors," Economic Systems, Elsevier, vol. 44(2).
    26. Delle Foglie, Andrea & Panetta, Ida Claudia, 2020. "Islamic stock market versus conventional: Are islamic investing a ‘Safe Haven’ for investors? A systematic literature review," Pacific-Basin Finance Journal, Elsevier, vol. 64(C).

  18. Amélie Charles & Olivier Darné & Jae H. Kim, 2015. "Will precious metals shine ? A market efficiency perspective," Post-Print hal-01238706, HAL.

    Cited by:

    1. Schweikert, Karsten, 2018. "Are gold and silver cointegrated? New evidence from quantile cointegrating regressions," Journal of Banking & Finance, Elsevier, vol. 88(C), pages 44-51.
    2. Ozkan, Oktay, 2021. "Impact of COVID-19 on stock market efficiency: Evidence from developed countries," Research in International Business and Finance, Elsevier, vol. 58(C).
    3. Bariviera, Aurelio F. & Font-Ferrer, Alejandro & Sorrosal-Forradellas, M. Teresa & Rosso, Osvaldo A., 2019. "An information theory perspective on the informational efficiency of gold price," The North American Journal of Economics and Finance, Elsevier, vol. 50(C).
    4. Go, You-How & Lau, Wee-Yeap, 2017. "Investor demand, market efficiency and spot-futures relation: Further evidence from crude palm oil," Resources Policy, Elsevier, vol. 53(C), pages 135-146.
    5. Li, Yang & Brooks, Robert, 2022. "Evidence of arbitrage trading activity: The case of Chinese metal futures contracts," Emerging Markets Review, Elsevier, vol. 51(PB).
    6. Labidi, Chiaz & Rahman, Md Lutfur & Hedström, Axel & Uddin, Gazi Salah & Bekiros, Stelios, 2018. "Quantile dependence between developed and emerging stock markets aftermath of the global financial crisis," International Review of Financial Analysis, Elsevier, vol. 59(C), pages 179-211.
    7. Rahman, Md. Lutfur & Lee, Doowon & Shamsuddin, Abul, 2017. "Time-varying return predictability in South Asian equity markets," International Review of Economics & Finance, Elsevier, vol. 48(C), pages 179-200.
    8. Sheng‐Tun Li & Kuei‐Chen Chiu & Chien‐Chang Wu, 2023. "Apply big data analytics for forecasting the prices of precious metals futures to construct a hedging strategy for industrial material procurement," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 44(2), pages 942-959, March.
    9. Syeda Tayyaba Ijaz & Rabia Komal, 2015. "Role Of Hurst Exponent In Prediction Of Market Efficiency In Kse-100 Index," IBT Journal of Business Studies (JBS), Ilma University, Faculty of Management Science, vol. 11(2), pages 41-54.
    10. Bredin, Don & Conlon, Thomas & Potì, Valerio, 2017. "The price of shelter - Downside risk reduction with precious metals," International Review of Financial Analysis, Elsevier, vol. 49(C), pages 48-58.
    11. O'Connor, Fergal & Lucey, Brian & Batten, Jonathan & Baur, Dirk, 2015. "The Financial Economics of Gold - a survey," MPRA Paper 65484, University Library of Munich, Germany.
    12. Naeem, Muhammad Abubakr & Agyemang, Abraham & Hasan Chowdhury, Md Iftekhar & Hasan, Mudassar & Shahzad, Syed Jawad Hussain, 2022. "Precious metals as hedge and safe haven for African stock markets," Resources Policy, Elsevier, vol. 78(C).
    13. Corbet, Shaen & Dowling, Michael & Gao, Xiangyun & Huang, Shupei & Lucey, Brian & Vigne, Samuel A., 2019. "An analysis of the intellectual structure of research on the financial economics of precious metals," Resources Policy, Elsevier, vol. 63(C), pages 1-1.
    14. Vigne, Samuel A. & Lucey, Brian M. & O’Connor, Fergal A. & Yarovaya, Larisa, 2017. "The financial economics of white precious metals — A survey," International Review of Financial Analysis, Elsevier, vol. 52(C), pages 292-308.
    15. Mensi, Walid & Sensoy, Ahmet & Vo, Xuan Vinh & Kang, Sang Hoon, 2020. "Impact of COVID-19 outbreak on asymmetric multifractality of gold and oil prices," Resources Policy, Elsevier, vol. 69(C).
    16. Chen, James Ming & Rehman, Mobeen Ur & Vo, Xuan Vinh, 2021. "Clustering commodity markets in space and time: Clarifying returns, volatility, and trading regimes through unsupervised machine learning," Resources Policy, Elsevier, vol. 73(C).
    17. Salisu, Afees A. & Ndako, Umar B. & Oloko, Tirimisiyu F., 2019. "Assessing the inflation hedging of gold and palladium in OECD countries," Resources Policy, Elsevier, vol. 62(C), pages 357-377.
    18. Apergis, Nicholas & Eleftheriou, Sofia, 2016. "Gold returns: Do business cycle asymmetries matter? Evidence from an international country sample," Economic Modelling, Elsevier, vol. 57(C), pages 164-170.
    19. Perera, Devmali & Białkowski, Jędrzej & Bohl, Martin T., 2020. "Does the tea market require a futures contract? Evidence from the Sri Lankan tea market," Research in International Business and Finance, Elsevier, vol. 54(C).
    20. Wahab, Bashir A. & Adewuyi, Adeolu O., 2021. "Analysis of major properties of metal prices using new methods: Structural breaks, non-linearity, stationarity and bubbles," Resources Policy, Elsevier, vol. 74(C).
    21. Baur, Dirk G. & Dichtl, Hubert & Drobetz, Wolfgang & Wendt, Viktoria-Sophie, 2020. "Investing in gold – Market timing or buy-and-hold?," International Review of Financial Analysis, Elsevier, vol. 71(C).
    22. Esra ALP & Ünal SEVEN, 2019. "Türkiye Konut Piyasasında Etkinlik Analizi," Istanbul Business Research, Istanbul University Business School, vol. 48(1), pages 84-112, May.
    23. Izabela Pruchnicka-Grabias, 2021. "Silver in Equity Portfolio Risk Optimization: Polish Investor Perspective," European Research Studies Journal, European Research Studies Journal, vol. 0(3), pages 716-728.
    24. Dichtl, Hubert, 2020. "Forecasting excess returns of the gold market: Can we learn from stock market predictions?," Journal of Commodity Markets, Elsevier, vol. 19(C).
    25. Low, Rand Kwong Yew & Yao, Yiran & Faff, Robert, 2016. "Diamonds vs. precious metals: What shines brightest in your investment portfolio?," International Review of Financial Analysis, Elsevier, vol. 43(C), pages 1-14.
    26. Batten, Jonathan A. & Lucey, Brian M. & Peat, Maurice, 2016. "Gold and silver manipulation: What can be empirically verified?," Economic Modelling, Elsevier, vol. 56(C), pages 168-176.

  19. Amélie Charles & Olivier Darné & Jae H. Kim & Etienne Redor, 2014. "Stock Exchange Mergers and Market Efficiency," Working Papers hal-00940105, HAL.

    Cited by:

    1. Liu, Yuna, 2016. "Essays on Stock Market Integration - On Stock Market Efficiency, Price Jumps and Stock Market Correlations," Umeå Economic Studies 926, Umeå University, Department of Economics.
    2. Li, Shaofang & Marinč, Matej, 2018. "Economies of scale and scope in financial market infrastructures," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 53(C), pages 17-49.
    3. Liu, Yuna, 2016. "Stock exchange integration and price jump risks - The case of the OMX Nordic exchange mergers," Umeå Economic Studies 925, Umeå University, Department of Economics.

  20. Liang Guo-Fitoussi & Olivier Darné, 2014. "A Comparison of the Finite Sample Properties of Selection Rules of Factor Numbers in Large Datasets," Working Papers hal-00962247, HAL.

    Cited by:

    1. Francesco Trebbi & Eric Weese, 2015. "Insurgency and Small Wars: Estimation of Unobserved Coalition Structures," NBER Working Papers 21202, National Bureau of Economic Research, Inc.
    2. Dalibor Stevanovic & Charles Olivier Mao Takongmo, 2014. "Selection of the number of factors in presence of structural instability: a Monte Carlo study," CIRANO Working Papers 2014s-44, CIRANO.

  21. Philippe Charlot & Olivier Darné & Zakaria Moussa, 2014. "Commodity returns co-movements: Fundamentals or "style" effect?," Working Papers hal-01093631, HAL.

    Cited by:

    1. Markus Haas, 2018. "A note on the absolute moments of the bivariate normal distribution," Economics Bulletin, AccessEcon, vol. 38(1), pages 650-656.
    2. Bonnier, Jean-Baptiste, 2021. "Speculation and informational efficiency in commodity futures markets," Journal of International Money and Finance, Elsevier, vol. 117(C).
    3. Jin, Jiayu & Han, Liyan & Xu, Yang, 2022. "Does the SDR stabilize investing in commodities?," International Review of Economics & Finance, Elsevier, vol. 81(C), pages 160-172.
    4. Maghyereh, Aktham & Abdoh, Hussein, 2020. "The tail dependence structure between investor sentiment and commodity markets," Resources Policy, Elsevier, vol. 68(C).
    5. Yang, Baochen & Pu, Yingjian & Su, Yunpeng, 2020. "The financialization of Chinese commodity markets," Finance Research Letters, Elsevier, vol. 34(C).
    6. Liu, Lu & Zhang, Xiang, 2019. "Financialization and commodity excess spillovers," International Review of Economics & Finance, Elsevier, vol. 64(C), pages 195-216.
    7. Mohammad Isleimeyyeh & Amine Ben Amar & Stéphane Goutte & Ramzi Benkraiem, 2022. "Commodity markets dynamics: What do cross-commodities over different nearest-to-maturities tell us?," Post-Print hal-03674806, HAL.
    8. Ben Amar, Amine & Goutte, Stéphane & Isleimeyyeh, Mohammad, 2022. "Asymmetric cyclical connectedness on the commodity markets: Further insights from bull and bear markets," The Quarterly Review of Economics and Finance, Elsevier, vol. 85(C), pages 386-400.
    9. de Boyrie Maria E. & Pavlova Ivelina, 2018. "Equities and Commodities Comovements: Evidence from Emerging Markets," Global Economy Journal, De Gruyter, vol. 18(3), pages 1-14, September.

  22. Marie-Sophie Hervieux & Olivier Darné, 2014. "Production and consumption-based approaches for the Environmental Kuznets Curve in Latin America using Ecological Footprint," Working Papers hal-00958692, HAL.

    Cited by:

    1. Barakatou Atte-Oudeyi & Bruno Kestemont & Jean Luc De Meulemeester, 2016. "Road Transport, Economic Growth and Carbon Dioxide Emissions in the BRIICS: Conditions For a Low Carbon Economic Development," Working Papers CEB 16-023, ULB -- Universite Libre de Bruxelles.

  23. Amélie Charles & Olivier Darné & Laurent Ferrara, 2014. "Does the Great Recession imply the end of the Great Moderation? International evidence," Working Papers hal-00952951, HAL.

    Cited by:

    1. Catherine Doz & Laurent Ferrara & Pierre-Alain Pionnier, 2020. "Business cycle dynamics after the Great Recession: An Extended Markov-Switching Dynamic Factor Model," Working Papers halshs-02443364, HAL.
    2. Amélie Charles & Olivier Darné, 0. "Econometric history of the growth–volatility relationship in the USA: 1919–2017," Cliometrica, Springer;Cliometric Society (Association Francaise de Cliométrie), vol. 0, pages 1-24.
    3. Nady Rapelanoro, 2016. "Spillover effects of global liquiditys expansion on emerging countries: evidences from a Panel VAR approach," EconomiX Working Papers 2016-17, University of Paris Nanterre, EconomiX.
    4. Kuo‐Hsuan Chin, 2022. "Forecast evaluation of DSGE models: Linear and nonlinear likelihood," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(6), pages 1099-1130, September.
    5. Michael Fritsch & Alina Sorgner & Michael Wyrwich & Evguenii Zazdravnykh, 2016. "Historical Shocks and Persistence of Economic Activity: Evidence from a Unique Natural Experiment," Jena Economics Research Papers 2016-007, Friedrich-Schiller-University Jena.
    6. Shah, Adil Ahmad & Paul, Manas & Bhanja, Niyati & Dar, Arif Billah, 2021. "Dynamics of connectedness across crude oil, precious metals and exchange rate: Evidence from time and frequency domains," Resources Policy, Elsevier, vol. 73(C).
    7. Rizwan Khalid & Choudhry Tanveer Shehzad & Bushra Naqvi, 2023. "Impact of capital account liberalization on stock market crashes," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(4), pages 3700-3726, October.
    8. Hasan Engin Duran, 2019. "Structural change and output volatility reduction in OECD countries: evidence of the Second Great Moderation," Journal of Economic Structures, Springer;Pan-Pacific Association of Input-Output Studies (PAPAIOS), vol. 8(1), pages 1-14, December.
    9. Alexander Yu. Apokin & Irina B. Ipatova, 2016. "Structural Breaks in Potential GDP Of Three Major Economies: Just Impaired Credit or the “New Normal”?," HSE Working papers WP BRP 142/EC/2016, National Research University Higher School of Economics.
    10. Florian Misch & Martin Rey, 2022. "The case for a loan-based euro area stability fund," Discussion Papers 20, European Stability Mechanism, revised 05 May 2022.
    11. Adam Check & Jeremy Piger, 2021. "Structural Breaks in U.S. Macroeconomic Time Series: A Bayesian Model Averaging Approach," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 53(8), pages 1999-2036, December.

  24. Mogliani, M. & Brunhes-Lesage, V. & Darné, O. & Pluyaud, B., 2014. "New estimate of the MIBA forecasting model. Modeling first-release GDP using the Banque de France's Monthly Business Survey and the “blocking” approach," Working papers 473, Banque de France.

    Cited by:

    1. C. Thubin & T. Ferrière & E. Monnet & M. Marx & V. Oung, 2016. "The PRISME model: can disaggregation on the production side help to forecast GDP?," Working papers 596, Banque de France.
    2. Cyrille Lenoel & Garry Young, 2020. "Real-time turning point indicators: Review of current international practices," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2020-05, Economic Statistics Centre of Excellence (ESCoE).
    3. M. Mogliani & T. Ferrière, 2016. "Rationality of announcements, business cycle asymmetry, and predictability of revisions. The case of French GDP," Working papers 600, Banque de France.
    4. E. Monnet & C. Thubin, 2017. "Construction crises and business cycle: consequences for GDP forecasts," Rue de la Banque, Banque de France, issue 39, february..
    5. Clément Bortoli & Stéphanie Combes & Thomas Renault, 2018. "Nowcasting GDP Growth by Reading Newspapers," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-03205161, HAL.
    6. Bańbura, Marta & Belousova, Irina & Bodnár, Katalin & Tóth, Máté Barnabás, 2023. "Nowcasting employment in the euro area," Working Paper Series 2815, European Central Bank.
    7. Frédérique Bec & Matteo Mogliani, 2013. "Nowcasting French GDP in Real-Time from Survey Opinions : Information or Forecast Combinations ?," Working Papers 2013-21, Center for Research in Economics and Statistics.
    8. Tomas Adam & Filip Novotny, 2018. "Assessing the External Demand of the Czech Economy: Nowcasting Foreign GDP Using Bridge Equations," Working Papers 2018/18, Czech National Bank.
    9. Cobb, Marcus P A, 2018. "Improving Underlying Scenarios for Aggregate Forecasts: A Multi-level Combination Approach," MPRA Paper 88593, University Library of Munich, Germany.
    10. Gerardin Mathilde, & Ranvier Martial., 2021. "Enrichment of the Banque de France’s monthly business survey: lessons from textual analysis of business leaders’ comments," Working papers 821, Banque de France.
    11. Daniel Roash & Tanya Suhoy, 2019. "Sentiment Indicators Based on a Short Business Tendency Survey," Bank of Israel Working Papers 2019.11, Bank of Israel.

  25. Amélie Charles & Olivier Darné, 2014. "Large shocks in the volatility of the Dow Jones Industrial Average index: 1928–2013," Post-Print hal-01122507, HAL.

    Cited by:

    1. Lorenzo Cerboni Baiardi & Massimo Costabile & Domenico De Giovanni & Fabio Lamantia & Arturo Leccadito & Ivar Massabó & Massimiliano Menzietti & Marco Pirra & Emilio Russo & Alessandro Staino, 2020. "The Dynamics of the S&P 500 under a Crisis Context: Insights from a Three-Regime Switching Model," Risks, MDPI, vol. 8(3), pages 1-15, July.
    2. Amélie Charles & Olivier Darné & Laurent Ferrara, 2014. "Does the Great Recession imply the end of the Great Moderation? International evidence," Working Papers hal-04141344, HAL.
    3. Tammuz Alraheb & Amine Tarazi, 2018. "Local Versus International Crises, Foreign Subsidiaries and Bank Stability: Evidence from the MENA Region," Post-Print hal-01558246, HAL.
    4. Carnero Fernández, María Ángeles & Pérez, Ana & Ruiz Ortega, Esther, 2014. "Identification of asymmetric conditional heteroscedasticity in the presence of outliers," DES - Working Papers. Statistics and Econometrics. WS ws141912, Universidad Carlos III de Madrid. Departamento de Estadística.
    5. Mensi, Walid & Al-Yahyaee, Khamis Hamed & Kang, Sang Hoon, 2019. "Structural breaks and double long memory of cryptocurrency prices: A comparative analysis from Bitcoin and Ethereum," Finance Research Letters, Elsevier, vol. 29(C), pages 222-230.
    6. Lu Wang & Feng Ma & Guoshan Liu, 2020. "Forecasting stock volatility in the presence of extreme shocks: Short‐term and long‐term effects," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(5), pages 797-810, August.
    7. He, Chengying & Wen, Zhang & Huang, Ke & Ji, Xiaoqin, 2022. "Sudden shock and stock market network structure characteristics: A comparison of past crisis events," Technological Forecasting and Social Change, Elsevier, vol. 180(C).
    8. Hanedar, Avni Önder & Yaldız Hanedar, Elmas, 2017. "Stock market reactions to wars and political risks: A cliometric perspective for a falling empire," MPRA Paper 85600, University Library of Munich, Germany, revised 25 Mar 2018.
    9. Ramona Dumitriu & Razvan Stefanescu, 2016. "Impact of the NYSE Shocks on the European Developed Capital Markets," Risk in Contemporary Economy, "Dunarea de Jos" University of Galati, Faculty of Economics and Business Administration, pages 327-334.
    10. Tammuz H. Alraheb & Amine Tarazi, 2018. "Local versus International Crises and Bank Stability: does bank foreign expansion make a difference?," Applied Economics, Taylor & Francis Journals, vol. 50(10), pages 1138-1155, February.
    11. Amélie Charles & Olivier Darné, 0. "Econometric history of the growth–volatility relationship in the USA: 1919–2017," Cliometrica, Springer;Cliometric Society (Association Francaise de Cliométrie), vol. 0, pages 1-24.
    12. Piotr Fiszeder & Marta Ma³ecka, 2022. "Forecasting volatility during the outbreak of Russian invasion of Ukraine: application to commodities, stock indices, currencies, and cryptocurrencies," Equilibrium. Quarterly Journal of Economics and Economic Policy, Institute of Economic Research, vol. 17(4), pages 939-967, December.
    13. Abildgren, Kim, 2014. "Far out in the tails – The historical distributions of macro-financial risk factors in Denmark," Nationaløkonomisk tidsskrift, Nationaløkonomisk Forening, vol. 2014(1), pages 1-31.
    14. Md. Abu HASAN, 2017. "Efficiency and Volatility of the Stock Market in Bangladesh: A Macroeconometric Analysis," Turkish Economic Review, KSP Journals, vol. 4(2), pages 239-249, June.
    15. Hanedar, Avni Önder & Hanedar, Elmas Yaldız, 2017. "Ottoman stock returns during the Turco-Italian and Balkan Wars of 1910-1914," eabh Papers 17-02, The European Association for Banking and Financial History (EABH).
    16. Behmiri, Niaz Bashiri & Manera, Matteo, 2015. "The Role of Outliers and Oil Price Shocks on Volatility of Metal Prices," Energy: Resources and Markets 208768, Fondazione Eni Enrico Mattei (FEEM).
    17. Chikashi Tsuji, 2016. "Does the fear gauge predict downside risk more accurately than econometric models? Evidence from the US stock market," Cogent Economics & Finance, Taylor & Francis Journals, vol. 4(1), pages 1220711-122, December.
    18. Al-Shboul, Mohammad & Alsharari, Nizar, 2019. "The dynamic behavior of evolving efficiency: Evidence from the UAE stock markets," The Quarterly Review of Economics and Finance, Elsevier, vol. 73(C), pages 119-135.
    19. Melike Bildirici & Nilgun Guler Bayazit & Yasemen Ucan, 2020. "Analyzing Crude Oil Prices under the Impact of COVID-19 by Using LSTARGARCHLSTM," Energies, MDPI, vol. 13(11), pages 1-18, June.
    20. Blommestein, Hans & Eijffinger, Sylvester & Qian, Zongxin, 2016. "Regime-dependent determinants of Euro area sovereign CDS spreads," Journal of Financial Stability, Elsevier, vol. 22(C), pages 10-21.
    21. Dendramis, Yiannis & Kapetanios, George & Tzavalis, Elias, 2015. "Shifts in volatility driven by large stock market shocks," Journal of Economic Dynamics and Control, Elsevier, vol. 55(C), pages 130-147.
    22. Xu Gong & Boqiang Lin, 2021. "Effects of structural changes on the prediction of downside volatility in futures markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(7), pages 1124-1153, July.
    23. Pape, Katharina & Wied, Dominik & Galeano, Pedro, 2016. "Monitoring multivariate variance changes," Journal of Empirical Finance, Elsevier, vol. 39(PA), pages 54-68.
    24. Amélie Charles & Chew Lian Chua & Olivier Darné & Sandy Suardi, 2021. "Oil price shocks, real economic activity and uncertainty," Bulletin of Economic Research, Wiley Blackwell, vol. 73(3), pages 364-392, July.
    25. Amélie Charles & Olivier Darné & Zakaria Moussa, 2014. "The sensitivity of Fama-French factors to economic uncertainty," Working Papers hal-01015702, HAL.
    26. Charles, Amélie & Darné, Olivier & Pop, Adrian, 2015. "Risk and ethical investment: Empirical evidence from Dow Jones Islamic indexes," Research in International Business and Finance, Elsevier, vol. 35(C), pages 33-56.
    27. Kyriazis, Nikolaos A. & Papadamou, Stephanos & Tzeremes, Panayiotis, 2023. "Are benchmark stock indices, precious metals or cryptocurrencies efficient hedges against crises?," Economic Modelling, Elsevier, vol. 128(C).
    28. Carnero, M. Angeles & Pérez, Ana, 2019. "Leverage effect in energy futures revisited," Energy Economics, Elsevier, vol. 82(C), pages 237-252.
    29. Al-Yahyaee, Khamis Hamed & Mensi, Walid & Al-Jarrah, Idries Mohammad Wanas & Hamdi, Atef & Kang, Sang Hoon, 2019. "Volatility forecasting, downside risk, and diversification benefits of Bitcoin and oil and international commodity markets: A comparative analysis with yellow metal," The North American Journal of Economics and Finance, Elsevier, vol. 49(C), pages 104-120.
    30. Andrukovich, P., 2019. "The dynamics of stock price during their listing and delisting," Journal of the New Economic Association, New Economic Association, vol. 44(4), pages 50-76.
    31. Rai, Anish & Mahata, Ajit & Nurujjaman, Md & Majhi, Sushovan & Debnath, Kanish, 2022. "A sentiment-based modeling and analysis of stock price during the COVID-19: U- and Swoosh-shaped recovery," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 592(C).
    32. Wang, Lu & Zhao, Chenchen & Liang, Chao & Jiu, Song, 2022. "Predicting the volatility of China's new energy stock market: Deep insight from the realized EGARCH-MIDAS model," Finance Research Letters, Elsevier, vol. 48(C).

  26. Karim Barhoumi & Olivier Darné & Laurent Ferrara, 2013. "Une revue de la littérature des modèles à facteurs dynamiques," Post-Print hal-01385940, HAL.

    Cited by:

    1. Mouloud El Hafidi & Marouane Daoui, 2019. "Chocs de la politique monétaire et croissance économique au Maroc : une approche en terme de modèles FAVAR," Post-Print hal-03311354, HAL.

  27. Amélie Charles & Olivier Darné & Jessica Fouilloux, 2013. "Market efficiency in the European carbon markets," Post-Print halshs-00846679, HAL.

    Cited by:

    1. Chen, Yingqi & Ba, Shusong & Yang, Qing & Yuan, Tian & Zhao, Haibo & Zhou, Ming & Bartocci, Pietro & Fantozzi, Francesco, 2021. "Efficiency of China’s carbon market: A case study of Hubei pilot market," Energy, Elsevier, vol. 222(C).
    2. Sibanjan Mishra, 2019. "Testing Martingale Hypothesis Using Variance Ratio Tests: Evidence from High-frequency Data of NCDEX Soya Bean Futures," Global Business Review, International Management Institute, vol. 20(6), pages 1407-1422, December.
    3. Zhao, Xin-gang & Jiang, Gui-wu & Nie, Dan & Chen, Hao, 2016. "How to improve the market efficiency of carbon trading: A perspective of China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 59(C), pages 1229-1245.
    4. Yifei Hua & Feng Dong, 2019. "China’s Carbon Market Development and Carbon Market Connection: A Literature Review," Energies, MDPI, vol. 12(9), pages 1-25, May.
    5. Yuanfeng Hu & Yixiang Tian & Luping Zhang, 2023. "Green Bond Pricing and Optimization Based on Carbon Emission Trading and Subsidies: From the Perspective of Externalities," Sustainability, MDPI, vol. 15(10), pages 1-20, May.
    6. Wang, Wei & Zhang, Yue-Jun, 2022. "Does China's carbon emissions trading scheme affect the market power of high-carbon enterprises?," Energy Economics, Elsevier, vol. 108(C).
    7. Qiyun Cheng & Huiting Qiao & Yimiao Gu & Zhenxi Chen, 2023. "Price Dynamics and Interactions between the Chinese and European Carbon Emission Trading Markets," Energies, MDPI, vol. 16(4), pages 1-12, February.
    8. Anouk Faure & Marc Baudry & Simon Quemin, 2020. "Emissions Trading with Transaction Costs," EconomiX Working Papers 2020-19, University of Paris Nanterre, EconomiX.
    9. Anna Creti & Marc Joëts, 2017. "Multiple bubbles in the European Union Emission Trading Scheme," Post-Print hal-01549809, HAL.
    10. Wang, Xiao-Qing & Su, Chi-Wei & Lobonţ, Oana-Ramona & Li, Hao & Nicoleta-Claudia, Moldovan, 2022. "Is China's carbon trading market efficient? Evidence from emissions trading scheme pilots," Energy, Elsevier, vol. 245(C).
    11. Liangzheng Wu & Yan Huang & Yimiao Gu, 2023. "Fragmented or Unified? The State of China’s Carbon Emission Trading Market," Energies, MDPI, vol. 16(5), pages 1-11, March.
    12. Luis A. Gil-Alana & Fernando Perez de Gracia & Rangan Gupta, 2015. "Modeling Persistence of Carbon Emission Allowance Prices," Working Papers 201515, University of Pretoria, Department of Economics.
    13. Ibikunle, Gbenga & Gregoriou, Andros & Hoepner, Andreas G.F. & Rhodes, Mark, 2016. "Liquidity and market efficiency in the world's largest carbon market," The British Accounting Review, Elsevier, vol. 48(4), pages 431-447.
    14. Fan, Xinghua & Lv, Xiangxiang & Yin, Jiuli & Tian, Lixin & Liang, Jiaochen, 2019. "Multifractality and market efficiency of carbon emission trading market: Analysis using the multifractal detrended fluctuation technique," Applied Energy, Elsevier, vol. 251(C), pages 1-1.
    15. Feng, Ling & Wang, Jieyu, 2023. "Random sources correlations and carbon futures pricing," International Review of Financial Analysis, Elsevier, vol. 86(C).
    16. Schultz, Emma & Swieringa, John, 2014. "Catalysts for price discovery in the European Union Emissions Trading System," Journal of Banking & Finance, Elsevier, vol. 42(C), pages 112-122.
    17. Chang, Kai & Chen, Rongda & Chevallier, Julien, 2018. "Market fragmentation, liquidity measures and improvement perspectives from China's emissions trading scheme pilots," Energy Economics, Elsevier, vol. 75(C), pages 249-260.
    18. Andreas Karpf & Antoine Mandel & Stefano Battiston, 2018. "Price and network dynamics in the European carbon market," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-01905985, HAL.
    19. Yan, Kai & Zhang, Wei & Shen, Dehua, 2020. "Stylized facts of the carbon emission market in China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 555(C).
    20. Liu, Jian & Jiang, Ting & Ye, Ze, 2021. "Information efficiency research of China's carbon markets," Finance Research Letters, Elsevier, vol. 38(C).
    21. Palao, Fernando & Pardo, Ángel, 2021. "The inconvenience yield of carbon futures," Energy Economics, Elsevier, vol. 101(C).
    22. Elena Villar-Rubio & María-Dolores Huete-Morales & Federico Galán-Valdivieso, 2023. "Using EGARCH models to predict volatility in unconsolidated financial markets: the case of European carbon allowances," Journal of Environmental Studies and Sciences, Springer;Association of Environmental Studies and Sciences, vol. 13(3), pages 500-509, September.
    23. Hanif, Waqas & Arreola Hernandez, Jose & Mensi, Walid & Kang, Sang Hoon & Uddin, Gazi Salah & Yoon, Seong-Min, 2021. "Nonlinear dependence and connectedness between clean/renewable energy sector equity and European emission allowance prices," Energy Economics, Elsevier, vol. 101(C).
    24. Chunyu Pan & Anil Kumar Shrestha & Guangyu Wang & John L. Innes & Kevin Xinwei Wang & Nuyun Li & Jinliang Li & Yeyun He & Chunguang Sheng & John-O. Niles, 2021. "A Linkage Framework for the China National Emission Trading System (CETS): Insight from Key Global Carbon Markets," Sustainability, MDPI, vol. 13(13), pages 1-15, July.
    25. Friedrich, Marina & Mauer, Eva-Maria & Pahle, Michael & Tietjen, Oliver, 2020. "From fundamentals to financial assets: the evolution of understanding price formation in the EU ETS," EconStor Preprints 225210, ZBW - Leibniz Information Centre for Economics.
    26. Chia-Lin Chang & Jukka Ilomäki & Hannu Laurila & Michael McAleer, 2018. "Moving Average Market Timing in European Energy Markets: Production Versus Emissions," Energies, MDPI, vol. 11(12), pages 1-24, November.
    27. Tan, Xue-Ping & Wang, Xin-Yu, 2017. "Dependence changes between the carbon price and its fundamentals: A quantile regression approach," Applied Energy, Elsevier, vol. 190(C), pages 306-325.

  28. Darne, O. & Levy-Rueff, O. & Pop, A., 2013. "Calibrating Initial Shocks in Bank Stress Test Scenarios: An Outlier Detection Based Approach," Working papers 426, Banque de France.

    Cited by:

    1. Zi-Yi Guo, 2017. "A Model of Plausible, Severe and Useful Stress Scenarios for VIX Shocks," Applied Economics and Finance, Redfame publishing, vol. 4(3), pages 155-163, May.

  29. Barhoumi, K. & Darné, O. & Ferrara, L., 2013. "Dynamic Factor Models: A review of the Literature ," Working papers 430, Banque de France.

    Cited by:

    1. Carlos Cesar Trucios-Maza & João H. G Mazzeu & Luis K. Hotta & Pedro L. Valls Pereira & Marc Hallin, 2019. "On the robustness of the general dynamic factor model with infinite-dimensional space: identification, estimation, and forecasting," Working Papers ECARES 2019-32, ULB -- Universite Libre de Bruxelles.
    2. Mattia Guerini & Duc Thi Luu & Mauro Napoletano, 2019. "Synchronization Patterns in the European Union," GREDEG Working Papers 2019-30, Groupe de REcherche en Droit, Economie, Gestion (GREDEG CNRS), Université Côte d'Azur, France.
    3. Hui ‘Fox’ Ling & Christian Franzen, 2017. "Online learning of time-varying stochastic factor structure by variational sequential Bayesian factor analysis," Quantitative Finance, Taylor & Francis Journals, vol. 17(8), pages 1277-1304, August.
    4. Carlos Trucíos & João H. G. Mazzeu & Marc Hallin & Luiz K. Hotta & Pedro L. Valls Pereira & Mauricio Zevallos, 2022. "Forecasting Conditional Covariance Matrices in High-Dimensional Time Series: A General Dynamic Factor Approach," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 41(1), pages 40-52, December.
    5. David Havrlant & Peter Tóth & Julia Wörz, 2016. "On the optimal number of indicators – nowcasting GDP growth in CESEE," Focus on European Economic Integration, Oesterreichische Nationalbank (Austrian Central Bank), issue 4, pages 54-72.
    6. Amélie Charles & Olivier Darné, 2022. "Backcasting world trade growth using data reduction methods," The World Economy, Wiley Blackwell, vol. 45(10), pages 3169-3191, October.
    7. Tóth, Peter, 2014. "Malý dynamický faktorový model na krátkodobé prognózovanie slovenského HDP [A Small Dynamic Factor Model for the Short-Term Forecasting of Slovak GDP]," MPRA Paper 63713, University Library of Munich, Germany.
    8. Poncela, Pilar & Ruiz, Esther & Miranda, Karen, 2021. "Factor extraction using Kalman filter and smoothing: This is not just another survey," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1399-1425.
    9. L. Ferrara. & G. Sestieri., 2014. "US labour market and monetary policy: current debates and challenges," Quarterly selection of articles - Bulletin de la Banque de France, Banque de France, issue 36, pages 111-129, winter.
    10. Trucíos Maza, Carlos César & Mazzeu, João H. G. & Hotta, Luiz Koodi & Pereira, Pedro L. Valls & Hallin, Marc, 2020. "Robustness and the general dynamic factor model with infinite-dimensional space: identification, estimation, and forecasting," Textos para discussão 521, FGV EESP - Escola de Economia de São Paulo, Fundação Getulio Vargas (Brazil).
    11. Catherine Doz & Peter Fuleky, 2019. "Dynamic Factor Models," Working Papers 2019-4, University of Hawaii Economic Research Organization, University of Hawaii at Manoa.
    12. Helmut Herwartz & Christian Ochsner & Hannes Rohloff, 2021. "The Credit Composition of Global Liquidity," MAGKS Papers on Economics 202115, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    13. Maximo Camacho & Gabriel Perez-Quiros & Pilar Poncela, 2012. "Markov-switching dynamic factor models in real time," Working Papers 1205, Banco de España.
    14. Amélie Charles & Olivier Darné & Fabien Tripier, 2017. "Uncertainty and the Macroeconomy," Post-Print hal-01549625, HAL.
    15. Poghosyan, Karen & Poghosyan, Ruben, 2021. "On the applicability of dynamic factor models for forecasting real GDP growth in Armenia," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 61, pages 28-46.
    16. Helmut Lütkepohl, 2014. "Structural Vector Autoregressive Analysis in a Data Rich Environment: A Survey," SFB 649 Discussion Papers SFB649DP2014-004, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    17. Catherine Doz & Peter Fuleky, 2019. "Dynamic Factor Models," PSE Working Papers halshs-02262202, HAL.
    18. Juan Laborda & Sonia Ruano & Ignacio Zamanillo, 2023. "Multi-Country and Multi-Horizon GDP Forecasting Using Temporal Fusion Transformers," Mathematics, MDPI, vol. 11(12), pages 1-26, June.
    19. Duangnate, Kannika & Mjelde, James W., 2017. "Comparison of data-rich and small-scale data time series models generating probabilistic forecasts: An application to U.S. natural gas gross withdrawals," Energy Economics, Elsevier, vol. 65(C), pages 411-423.
    20. Amélie Charles & Olivier Darné & Fabien Tripier, 2017. "Uncertainty and the Macroeconomy: Evidence from an Uncertainty Composite Indicator," Working Papers 2017-25, CEPII research center.
    21. Focardi, Sergio M. & Fabozzi, Frank J. & Mitov, Ivan K., 2016. "A new approach to statistical arbitrage: Strategies based on dynamic factor models of prices and their performance," Journal of Banking & Finance, Elsevier, vol. 65(C), pages 134-155.
    22. Ferrara , L. & Marsilli, C., 2016. "Nowcasting global economic growth," Rue de la Banque, Banque de France, issue 23, April..
    23. Catherine Doz & Peter Fuleky, 2019. "Dynamic Factor Models," Working Papers halshs-02262202, HAL.
    24. Marijn A. Bolhuis & Brett Rayner, 2020. "Deus ex Machina? A Framework for Macro Forecasting with Machine Learning," IMF Working Papers 2020/045, International Monetary Fund.
    25. Denisa BANULESCU-RADU & Laurent FERRARA & Clément MARSILLI, 2019. "Prévoir la volatilité d’un actif financier à l’aide d’un modèle à mélange de fréquences," LEO Working Papers / DR LEO 2710, Orleans Economics Laboratory / Laboratoire d'Economie d'Orleans (LEO), University of Orleans.
    26. Karmous, Aida & Boubaker, Heni & Belkacem, Lotfi, 2019. "A dynamic factor model with stylized facts to forecast volatility for an optimal portfolio," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 534(C).

  30. Karim Barhoumi & Olivier Darné & Laurent Ferrara, 2013. "Testing the number of factors: An empirical assessment for forecasting purposes," Post-Print hal-01385876, HAL.

    Cited by:

    1. GUO-FITOUSSI, Liang, 2013. "A Comparison of the Finite Sample Properties of Selection Rules of Factor Numbers in Large Datasets," MPRA Paper 50005, University Library of Munich, Germany.
    2. Francisco Corona & Pilar Poncela & Esther Ruiz, 2017. "Determining the number of factors after stationary univariate transformations," Empirical Economics, Springer, vol. 53(1), pages 351-372, August.
    3. Mahmut Günay, 2015. "Forecasting Turkish Industrial Production Growth With Static Factor Models," International Econometric Review (IER), Econometric Research Association, vol. 7(2), pages 64-78, September.
    4. Laurent Ferrara & Clément Marsilli, 2019. "Nowcasting global economic growth: A factor‐augmented mixed‐frequency approach," The World Economy, Wiley Blackwell, vol. 42(3), pages 846-875, March.
    5. Karim Barhoumi & Laurent Ferrara, 2015. "A World Trade Leading Index (WTLI)," IMF Working Papers 2015/020, International Monetary Fund.
    6. Berg, Tim Oliver & Henzel, Steffen, 2013. "Point and Density Forecasts for the Euro Area Using Many Predictors: Are Large BVARs Really Superior?," VfS Annual Conference 2013 (Duesseldorf): Competition Policy and Regulation in a Global Economic Order 79783, Verein für Socialpolitik / German Economic Association.
    7. Barhoumi, K. & Darné, O. & Ferrara, L., 2013. "Dynamic Factor Models: A review of the Literature ," Working papers 430, Banque de France.
    8. Karen Miranda & Pilar Poncela & Esther Ruiz, 2022. "Dynamic factor models: Does the specification matter?," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 13(1), pages 397-428, May.
    9. António Rua, 2016. "A wavelet-based multivariate multiscale approach for forecasting," Working Papers w201612, Banco de Portugal, Economics and Research Department.
    10. Dalibor Stevanovic & Charles Olivier Mao Takongmo, 2014. "Selection of the number of factors in presence of structural instability: a Monte Carlo study," CIRANO Working Papers 2014s-44, CIRANO.
    11. Kappler, Marcus & Schleer, Frauke, 2017. "A financially stressed euro area," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 11, pages 1-37.
    12. Tim Oliver Berg & Steffen Henzel, 2014. "Point and Density Forecasts for the Euro Area Using Bayesian VARs," CESifo Working Paper Series 4711, CESifo.
    13. Kappler, Marcus & Schleer, Frauke, 2013. "How many factors and shocks cause financial stress?," ZEW Discussion Papers 13-100, ZEW - Leibniz Centre for European Economic Research.

  31. Marie-Sophie Hervieux & Olivier Darné, 2013. "Environmental Kuznets Curve and Ecological Footprint: A Time Series Analysis," Working Papers hal-00781958, HAL.

    Cited by:

    1. Shokoohi, Zeinab & Dehbidi, Navid Kargar & Tarazkar, Mohammad Hassan, 2022. "Energy intensity, economic growth and environmental quality in populous Middle East countries," Energy, Elsevier, vol. 239(PC).
    2. Selim J rgen Ergun & Maria Fernanda Rivas, 2020. "Testing the Environmental Kuznets Curve Hypothesis in Uruguay using Ecological Footprint as a Measure of Environmental Degradation," International Journal of Energy Economics and Policy, Econjournals, vol. 10(4), pages 473-485.
    3. Koç, Pınar & Gülmez, Ahmet, 2021. "Analysis of relationships between nanotechnology applications, mineral saving and ecological footprint: Evidence from panel fourier cointegration and causality tests," Resources Policy, Elsevier, vol. 74(C).
    4. Iftikhar Yasin & Nawaz Ahmad & M. Aslam Chaudhary, 2020. "Catechizing the Environmental-Impression of Urbanization, Financial Development, and Political Institutions: A Circumstance of Ecological Footprints in 110 Developed and Less-Developed Countries," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 147(2), pages 621-649, January.

  32. Amélie Charles & Olivier Darné, 2012. "Volatility Persistence in Crude Oil Markets," Working Papers hal-00719387, HAL.

    Cited by:

    1. Duong T Le, 2015. "Ex-ante Determinants of Volatility in the Crude Oil Market," International Journal of Financial Research, International Journal of Financial Research, Sciedu Press, vol. 6(1), pages 1-13, January.
    2. Wang, Yudong & Hao, Xianfeng, 2022. "Forecasting the real prices of crude oil: A robust weighted least squares approach," Energy Economics, Elsevier, vol. 116(C).
    3. Wang, Fan & Tian, Lixin & Du, Ruijin & Dong, Gaogao, 2021. "Universal law in the crude oil market based on visibility graph algorithm and network structure," Resources Policy, Elsevier, vol. 70(C).
    4. Zavadska, Miroslava & Morales, Lucía & Coughlan, Joseph, 2020. "Brent crude oil prices volatility during major crises," Finance Research Letters, Elsevier, vol. 32(C).
    5. Gaoke Liao & Zhenghui Li & Ziqing Du & Yue Liu, 2019. "The Heterogeneous Interconnections between Supply or Demand Side and Oil Risks," Energies, MDPI, vol. 12(11), pages 1-17, June.
    6. Ra l De Jes s Guti rrez & Lidia E. Carvajal Guti rrez & Oswaldo Garcia Salgado, 2023. "Value at Risk and Expected Shortfall Estimation for Mexico s Isthmus Crude Oil Using Long-Memory GARCH-EVT Combined Approaches," International Journal of Energy Economics and Policy, Econjournals, vol. 13(4), pages 467-480, July.
    7. Ma, Feng & Liu, Jing & Huang, Dengshi & Chen, Wang, 2017. "Forecasting the oil futures price volatility: A new approach," Economic Modelling, Elsevier, vol. 64(C), pages 560-566.
    8. Liu, Jing & Wei, Yu & Ma, Feng & Wahab, M.I.M., 2017. "Forecasting the realized range-based volatility using dynamic model averaging approach," Economic Modelling, Elsevier, vol. 61(C), pages 12-26.
    9. Luis A. Gil-Alana & Rangan Gupta & Olusanya E. Olubusoye & OlaOluwa S. Yaya, 2015. "Time Series Analysis of Persistence in Crude Oil Price Volatility across Bull and Bear Regimes," Working Papers 201580, University of Pretoria, Department of Economics.
    10. Amélie Charles & Chew Lian Chua & Olivier Darné & Sandy Suardi, 2020. "On the Pernicious Effects of Oil Price Uncertainty on U.S. Real Economic Activities," Post-Print hal-03040689, HAL.
    11. Dennis Alvaro & Ángel Guillén & Gabriel Rodríguez, 2017. "Modelling the volatility of commodities prices using a stochastic volatility model with random level shifts," Review of World Economics (Weltwirtschaftliches Archiv), Springer;Institut für Weltwirtschaft (Kiel Institute for the World Economy), vol. 153(1), pages 71-103, February.
    12. Lynda Khalaf & Beatriz Peraza López, 2020. "Simultaneous Indirect Inference, Impulse Responses and ARMA Models," Econometrics, MDPI, vol. 8(2), pages 1-26, April.
    13. Olusanya E. Olubusoye & OlaOluwa S. Yaya, 2016. "Time series analysis of volatility in the petroleum pricing markets: the persistence, asymmetry and jumps in the returns series," OPEC Energy Review, Organization of the Petroleum Exporting Countries, vol. 40(3), pages 235-262, September.
    14. Salisu, Afees A. & Fasanya, Ismail O., 2013. "Modelling oil price volatility with structural breaks," Energy Policy, Elsevier, vol. 52(C), pages 554-562.
    15. Behmiri, Niaz Bashiri & Manera, Matteo, 2015. "The Role of Outliers and Oil Price Shocks on Volatility of Metal Prices," Energy: Resources and Markets 208768, Fondazione Eni Enrico Mattei (FEEM).
    16. Rice, Gregory & Wirjanto, Tony & Zhao, Yuqian, 2023. "Exploring volatility of crude oil intraday return curves: A functional GARCH-X model," Journal of Commodity Markets, Elsevier, vol. 32(C).
    17. Tarek Bouazizi & Mongi Lassoued & Zouhaier Hadhek, 2021. "Oil Price Volatility Models during Coronavirus Crisis: Testing with Appropriate Models Using Further Univariate GARCH and Monte Carlo Simulation Models," International Journal of Energy Economics and Policy, Econjournals, vol. 11(1), pages 281-292.
    18. Rice, Gregory & Wirjanto, Tony & Zhao, Yuqian, 2021. "Exploring volatility of crude oil intra-day return curves: a functional GARCH-X Model," MPRA Paper 109231, University Library of Munich, Germany.
    19. Charles, Amélie & Darné, Olivier, 2017. "Forecasting crude-oil market volatility: Further evidence with jumps," Energy Economics, Elsevier, vol. 67(C), pages 508-519.
    20. Dutta, Anupam & Soytas, Ugur & Das, Debojyoti & Bhattacharyya, Asit, 2022. "In search of time-varying jumps during the turmoil periods: Evidence from crude oil futures markets," Energy Economics, Elsevier, vol. 114(C).
    21. Mehmet Balcilar & Zeynel Abidin Ozdemir, 2017. "The nexus between the oil price and its volatility in a stochastic volatility in mean model with time-varying parameters," Working Papers 15-33, Eastern Mediterranean University, Department of Economics.
    22. Jean Pierre Fernández Prada Saucedo & Gabriel Rodríguez, 2020. "Modeling the Volatility of Returns on Commodities: An Application and Empirical Comparison of GARCH and SV Models," Documentos de Trabajo / Working Papers 2020-484, Departamento de Economía - Pontificia Universidad Católica del Perú.
    23. Charfeddine, Lanouar, 2016. "Breaks or long range dependence in the energy futures volatility: Out-of-sample forecasting and VaR analysis," Economic Modelling, Elsevier, vol. 53(C), pages 354-374.
    24. Peng-Fei Dai & Xiong Xiong & Wei-Xing Zhou, 2020. "The role of global economic policy uncertainty in predicting crude oil futures volatility: Evidence from a two-factor GARCH-MIDAS model," Papers 2007.12838, arXiv.org.
    25. Alaba, Oluwayemisi O. & Ojo, Oluwadare O. & Yaya, OlaOluwa S & Abu, Nurudeen & Ajobo, Saheed A., 2021. "Comparative Analysis of Market Efficiency and Volatility of Energy Prices Before and During COVID-19 Pandemic Periods," MPRA Paper 109825, University Library of Munich, Germany.
    26. Steve J. Bickley & Martin Brumpton & Ho Fai Chan & Richard Colthurst & Benno Torgler, 2020. "Turbulence in the financial markets: Cross-country differences in market volatility in response to COVID-19 pandemic policies," CREMA Working Paper Series 2020-15, Center for Research in Economics, Management and the Arts (CREMA).
    27. Zied Ftiti & Fredj Jawadi & Waël Louhichi, 2017. "Modelling the relationship between future energy intraday volatility and trading volume with wavelet," Applied Economics, Taylor & Francis Journals, vol. 49(20), pages 1981-1993, April.
    28. Michael D. Plante, 2018. "OPEC in the News," Working Papers 1802, Federal Reserve Bank of Dallas.
    29. Liu, Jing & Ma, Feng & Tang, Yingkai & Zhang, Yaojie, 2019. "Geopolitical risk and oil volatility: A new insight," Energy Economics, Elsevier, vol. 84(C).
    30. Wei, Yu & Liu, Jing & Lai, Xiaodong & Hu, Yang, 2017. "Which determinant is the most informative in forecasting crude oil market volatility: Fundamental, speculation, or uncertainty?," Energy Economics, Elsevier, vol. 68(C), pages 141-150.
    31. Zhao, Yuan & Zhang, Weiguo & Gong, Xue & Wang, Chao, 2021. "A novel method for online real-time forecasting of crude oil price," Applied Energy, Elsevier, vol. 303(C).
    32. Miroslava Zavadska & Lucía Morales & Joseph Coughlan, 2018. "The Lead–Lag Relationship between Oil Futures and Spot Prices—A Literature Review," IJFS, MDPI, vol. 6(4), pages 1-22, October.
    33. Anupam Dutta & Elie Bouri & David Roubaud, 2021. "Modelling the volatility of crude oil returns: Jumps and volatility forecasts," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(1), pages 889-897, January.
    34. Teti, Emanuele & Dallocchio, Maurizio & De Sanctis, Daniele, 2020. "Effects of oil price fall on the betas in the Unconventional Oil & Gas Industry," Energy Policy, Elsevier, vol. 144(C).
    35. Feng Ma & Yu Wei & Wang Chen & Feng He, 2018. "Forecasting the volatility of crude oil futures using high-frequency data: further evidence," Empirical Economics, Springer, vol. 55(2), pages 653-678, September.
    36. Mensi, Walid & Hammoudeh, Shawkat & Nguyen, Duc Khuong & Kang, Sang Hoon, 2016. "Global financial crisis and spillover effects among the U.S. and BRICS stock markets," International Review of Economics & Finance, Elsevier, vol. 42(C), pages 257-276.
    37. Carnero, M. Angeles & Pérez, Ana, 2019. "Leverage effect in energy futures revisited," Energy Economics, Elsevier, vol. 82(C), pages 237-252.
    38. Balcilar, Mehmet & Ozdemir, Zeynel Abidin, 2019. "The nexus between the oil price and its volatility risk in a stochastic volatility in the mean model with time-varying parameters," Resources Policy, Elsevier, vol. 61(C), pages 572-584.
    39. Mansour Khalili Araghi & Majid Mirzaee Ghazani, 2015. "Abrupt Changes in Volatility: Evidence from TEPIX Index in Tehran Stock Exchange," Iranian Economic Review (IER), Faculty of Economics,University of Tehran.Tehran,Iran, vol. 19(3), pages 377-393, Autumn.
    40. Kais Tissaoui & Taha Zaghdoudi & Abdelaziz Hakimi & Mariem Nsaibi, 2023. "Do Gas Price and Uncertainty Indices Forecast Crude Oil Prices? Fresh Evidence Through XGBoost Modeling," Computational Economics, Springer;Society for Computational Economics, vol. 62(2), pages 663-687, August.
    41. Xie, Qiwei & Liu, Ranran & Qian, Tao & Li, Jingyu, 2021. "Linkages between the international crude oil market and the Chinese stock market: A BEKK-GARCH-AFD approach," Energy Economics, Elsevier, vol. 102(C).
    42. Mhd Ruslan, Siti Marsila & Mokhtar, Kasypi, 2021. "Stock market volatility on shipping stock prices: GARCH models approach," The Journal of Economic Asymmetries, Elsevier, vol. 24(C).
    43. Gao, Xiangyun & Fang, Wei & An, Feng & Wang, Yue, 2017. "Detecting method for crude oil price fluctuation mechanism under different periodic time series," Applied Energy, Elsevier, vol. 192(C), pages 201-212.

  33. Amélie Charles & Olivier Darné, 2012. "Trends and random walks in macroeconomic time series: A reappraisal," Post-Print hal-00956937, HAL.

    Cited by:

    1. Gary Cornwall & Jeff Chen & Beau Sauley, 2021. "Standing on the Shoulders of Machine Learning: Can We Improve Hypothesis Testing?," Papers 2103.01368, arXiv.org.
    2. Christian Balcells, 2022. "Determinants of firm boundaries and organizational performance: an empirical investigation of the Chilean truck market," Journal of Evolutionary Economics, Springer, vol. 32(2), pages 423-461, April.

  34. Amélie Charles & Olivier Darné & Jean-François Hoarau, 2012. "Convergence of real per capita GDP within COMESA countries: A panel unit root evidence," Post-Print hal-00956938, HAL.

    Cited by:

    1. Serge Rey & Florent Deisting, 2012. "GDP per Capita among African Countries over the Period 1950-2008: Highlights of Convergence Clubs," Post-Print hal-01881912, HAL.
    2. J. Paul Dunne & Nicholas Masiyandima, 2017. "Bilateral FDI from South Africa and Income Convergence in SADC," School of Economics Macroeconomic Discussion Paper Series 2017-04, School of Economics, University of Cape Town.
    3. Desli, Evangelia & Gkoulgkoutsika, Alexandra, 2021. "Economic convergence among the world’s top-income economies," The Quarterly Review of Economics and Finance, Elsevier, vol. 80(C), pages 841-853.
    4. Burcu Ozcan, 2014. "Does Income Converge among EU Member Countries following the Post-War Period? Evidence from the PANKPSS Test," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(3), pages 22-38, October.
    5. Aweng Peter Majok Garang & Hatice Erkekoglu, 2021. "Convergence Triggers in Africa: Evidence from Convergence Clubs and Panel Models," South African Journal of Economics, Economic Society of South Africa, vol. 89(2), pages 218-245, June.

  35. Antipa, P. & Barhoumi, K. & Brunhes-Lesage, V. & Darné, O., 2012. "Nowcasting German GDP: A comparison of bridge and factor models," Working papers 401, Banque de France.

    Cited by:

    1. Lamprou, Dimitra, 2016. "Nowcasting GDP in Greece: The impact of data revisions and forecast origin on model selection and performance," The Journal of Economic Asymmetries, Elsevier, vol. 14(PA), pages 93-102.
    2. Jean Barthélemy & Magali Marx, 2012. "Generalizing the Taylor Principle: New Comment," Sciences Po publications 403, Sciences Po.
    3. Schwarzmüller, Tim, 2015. "Model pooling and changes in the informational content of predictors: An empirical investigation for the euro area," Kiel Working Papers 1982, Kiel Institute for the World Economy (IfW Kiel).
    4. A. Girardi & R. Golinelli & C. Pappalardo, 2014. "The Role of Indicator Selection in Nowcasting Euro Area GDP in Pseudo Real Time," Working Papers wp919, Dipartimento Scienze Economiche, Universita' di Bologna.
    5. Bosupeng, Mpho, 2015. "On Exports and Economic Growth-Multifarious Economies Perspective," MPRA Paper 77922, University Library of Munich, Germany, revised 2015.
    6. Katja Heinisch & Rolf Scheufele, 2018. "Bottom-up or direct? Forecasting German GDP in a data-rich environment," Empirical Economics, Springer, vol. 54(2), pages 705-745, March.
    7. Radoslaw Sobko & Maria Klonowska-Matynia, 2021. "The Relationship between the Purchasing Managers’ Index (PMI) and Economic Growth: The Case for Poland," European Research Studies Journal, European Research Studies Journal, vol. 0(Special 1), pages 198-219.
    8. Bosupeng, Mpho, 2015. "The Export-Led Growth Hypothesis: New Evidence and Implications," MPRA Paper 77917, University Library of Munich, Germany, revised Jun 2015.
    9. Petralias, Athanassios & Petros, Sotirios & Prodromídis, Pródromos, 2013. "Greece in recession: economic predictions, mispredictions and policy implications," LSE Research Online Documents on Economics 52626, London School of Economics and Political Science, LSE Library.
    10. Abdić Ademir & Resić Emina & Abdić Adem, 2020. "Modelling and forecasting GDP using factor model: An empirical study from Bosnia and Herzegovina," Croatian Review of Economic, Business and Social Statistics, Sciendo, vol. 6(1), pages 10-26, May.
    11. Abdić Ademir & Resić Emina & Abdić Adem & Rovčanin Adnan, 2020. "Nowcasting GDP of Bosnia and Herzegovina: A Comparison of Forecast Accuracy Models," South East European Journal of Economics and Business, Sciendo, vol. 15(2), pages 1-14, December.
    12. Priscila Espinosa & Jose M. Pavía, 2023. "Automation in Regional Economic Synthetic Index Construction with Uncertainty Measurement," Forecasting, MDPI, vol. 5(2), pages 1-19, April.
    13. Müller-Kademann Christian, 2015. "Internal Validation of Temporal Disaggregation: A Cloud Chamber Approach," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 235(3), pages 298-319, June.
    14. Pinkwart, Nicolas, 2018. "Short-term forecasting economic activity in Germany: A supply and demand side system of bridge equations," Discussion Papers 36/2018, Deutsche Bundesbank.
    15. Tomas Adam & Filip Novotny, 2018. "Assessing the External Demand of the Czech Economy: Nowcasting Foreign GDP Using Bridge Equations," Working Papers 2018/18, Czech National Bank.
    16. Cobb, Marcus P A, 2018. "Improving Underlying Scenarios for Aggregate Forecasts: A Multi-level Combination Approach," MPRA Paper 88593, University Library of Munich, Germany.
    17. Eric W. K. See-To & Eric W. T. Ngai, 2018. "Customer reviews for demand distribution and sales nowcasting: a big data approach," Annals of Operations Research, Springer, vol. 270(1), pages 415-431, November.
    18. Stavros Degiannakis, 2023. "The D-model for GDP nowcasting," Working Papers 317, Bank of Greece.
    19. Porshakov, Alexey & Deryugina, Elena & Ponomarenko, Alexey & Sinyakov, Andrey, 2015. "Nowcasting and short-term forecasting of Russian GDP with a dynamic factor model," BOFIT Discussion Papers 19/2015, Bank of Finland Institute for Emerging Economies (BOFIT).
    20. Dimitra Lamprou, 2015. "Nowcasting GDP in Greece: A Note on Forecasting Improvements from the Use of Bridge Models," South-Eastern Europe Journal of Economics, Association of Economic Universities of South and Eastern Europe and the Black Sea Region, vol. 13(1), pages 85-100.
    21. Konstantin Kuck & Karsten Schweikert, 2021. "Forecasting Baden‐Württemberg's GDP growth: MIDAS regressions versus dynamic mixed‐frequency factor models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(5), pages 861-882, August.
    22. Kitlinski, Tobias, 2015. "With or without you: Do financial data help to forecast industrial production?," Ruhr Economic Papers 558, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    23. Kitlinski, Tobias & an de Meulen, Philipp, 2015. "The role of targeted predictors for nowcasting GDP with bridge models: Application to the Euro area," Ruhr Economic Papers 559, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.

  36. Karim Barhoumi & Olivier Darné & Laurent Ferrara & Bertrand Pluyaud, 2012. "Monthly GDP forecasting using bridge models: Comparison from the supply and demand sides for the French economy," Post-Print hal-01385807, HAL.

    Cited by:

    1. Robert Lehmann, 2016. "Economic Growth and Business Cycle Forecasting at the Regional Level," ifo Beiträge zur Wirtschaftsforschung, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 65.
    2. Olivier Darne & Amelie Charles, 2020. "Nowcasting GDP growth using data reduction methods: Evidence for the French economy," Economics Bulletin, AccessEcon, vol. 40(3), pages 2431-2439.
    3. Katja Heinisch & Rolf Scheufele, 2018. "Bottom-up or direct? Forecasting German GDP in a data-rich environment," Empirical Economics, Springer, vol. 54(2), pages 705-745, March.
    4. Soybilgen, Barış & Yazgan, Ege, 2018. "Evaluating nowcasts of bridge equations with advanced combination schemes for the Turkish unemployment rate," Economic Modelling, Elsevier, vol. 72(C), pages 99-108.
    5. Frédérique Savignac & Erwan Gautier & Yuriy Gorodnichenko & Olivier Coibion, 2021. "Firms’ Inflation Expectations: New Evidence from France," Working papers 840, Banque de France.
    6. Dr. Gregor Bäurle & Elizabeth Steiner & Dr. Gabriel Züllig, 2018. "Forecasting the production side of GDP," Working Papers 2018-16, Swiss National Bank.
    7. Nicoletta Pashourtidou & Christos Papamichael & Charalampos Karagiannakis, 2018. "Forecasting economic activity in sectors of the Cypriot economy," Cyprus Economic Policy Review, University of Cyprus, Economics Research Centre, vol. 12(2), pages 24-66, December.

  37. Amélie Charles & Olivier Darné & Adrian Pop, 2012. "Are Islamic Indexes more Volatile than Conventional Indexes? Evidence from Dow Jones Indexes," Working Papers hal-00678895, HAL.

    Cited by:

    1. Shumi Akhtar & Maria Jahromi & Tom Smith, 2017. "Risk, return and mean-variance efficiency of Islamic and non-Islamic stocks: evidence from a unique Malaysian data set," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 57(1), pages 3-46, March.
    2. Achraf Ghorbel & Mouna Abdelhedi & Younes Boujelbene, 2014. "Assessing the Impact of Crude Oil Price and Investor Sentiment on Islamic Indices: Subprime Crisis," Journal of African Business, Taylor & Francis Journals, vol. 15(1), pages 13-24, April.
    3. Majdoub, Jihed & Mansour, Walid & Jouini, Jamel, 2016. "Market integration between conventional and Islamic stock prices," The North American Journal of Economics and Finance, Elsevier, vol. 37(C), pages 436-457.
    4. Safika Praveen Sheikh & Shafkat Shafi Dar & Sajad Ahmad Rather, 2020. "Volatility Contagion and Portfolio Diversification among Shariah and Conventional Indices: An Evidence by MGARCH Models عدوى التقلبات و تنوع التصورات في أحكام الشريعة الإسلامية والأحكام التقليدية: إثب," Journal of King Abdulaziz University: Islamic Economics, King Abdulaziz University, Islamic Economics Institute., vol. 33(1), pages 35-55, January.
    5. Audi, Marc & Sadiq, Azhar & Ali, Amjad, 2021. "Performance Evaluation of Islamic and Non-Islamic Equity and Bonds Indices: Evidence from selected Emerging and Developed Countries," MPRA Paper 109866, University Library of Munich, Germany.

  38. Amélie Charles & Olivier Darné & Adrian Pop, 2011. "Is the Islamic Finance Model More Resilient than the Conventional Finance Model? Evidence from sudden changes in the volatility of Dow Jones indexes," Post-Print hal-00763015, HAL.

    Cited by:

    1. Abu-Alkheil, Ahmad & Khan, Walayet A. & Parikh, Bhavik & Mohanty, Sunil K., 2017. "Dynamic co-integration and portfolio diversification of Islamic and conventional indices: Global evidence," The Quarterly Review of Economics and Finance, Elsevier, vol. 66(C), pages 212-224.
    2. Rizvi, Syed Aun R. & Arshad, Shaista, 2018. "Understanding time-varying systematic risks in Islamic and conventional sectoral indices," Economic Modelling, Elsevier, vol. 70(C), pages 561-570.
    3. Yildirim, Ramazan & Masih, Mansur, 2013. "Relationship between regional Shariah stock markets: The cointegration and causality," MPRA Paper 76281, University Library of Munich, Germany.
    4. Fakhfekh, Mohamed & Hachicha, Nejib & Jawadi, Fredj & Selmi, Nadhem & Idi Cheffou, Abdoulkarim, 2016. "Measuring volatility persistence for conventional and Islamic banks: An FI-EGARCH approach," Emerging Markets Review, Elsevier, vol. 27(C), pages 84-99.
    5. Ali, Sajid & Shahzad, Syed Jawad Hussain & Raza, Naveed & Al-Yahyaee, Khamis Hamed, 2018. "Stock market efficiency: A comparative analysis of Islamic and conventional stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 503(C), pages 139-153.
    6. Yildirim, Ramazan & Masih, Mansur, 2018. "Investigating International Portfolio Diversification Opportunities for the Asian Islamic Stock Market Investors," MPRA Paper 90281, University Library of Munich, Germany.
    7. Yildirim, Ramazan & Masih, A. Mansur M., 2014. "The Effect of Recent Financial Crisis over Global Portfolio Diversification Opportunities – Empirical Evidence A Comparative Multivariate GARCH-DCC, MODWT and Wavelet Correlation Analysis," MPRA Paper 58269, University Library of Munich, Germany.

  39. Amélie Charles & Olivier Darné & Adrian Pop, 2011. "Is the Islamic Finance Model More Resilient than the Conventional Model," Post-Print hal-00763013, HAL.

    Cited by:

    1. Abu-Alkheil, Ahmad & Khan, Walayet A. & Parikh, Bhavik & Mohanty, Sunil K., 2017. "Dynamic co-integration and portfolio diversification of Islamic and conventional indices: Global evidence," The Quarterly Review of Economics and Finance, Elsevier, vol. 66(C), pages 212-224.
    2. Yildirim, Ramazan & Masih, Mansur, 2013. "Relationship between regional Shariah stock markets: The cointegration and causality," MPRA Paper 76281, University Library of Munich, Germany.
    3. Fakhfekh, Mohamed & Hachicha, Nejib & Jawadi, Fredj & Selmi, Nadhem & Idi Cheffou, Abdoulkarim, 2016. "Measuring volatility persistence for conventional and Islamic banks: An FI-EGARCH approach," Emerging Markets Review, Elsevier, vol. 27(C), pages 84-99.
    4. Ali, Sajid & Shahzad, Syed Jawad Hussain & Raza, Naveed & Al-Yahyaee, Khamis Hamed, 2018. "Stock market efficiency: A comparative analysis of Islamic and conventional stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 503(C), pages 139-153.
    5. Yildirim, Ramazan & Masih, Mansur, 2018. "Investigating International Portfolio Diversification Opportunities for the Asian Islamic Stock Market Investors," MPRA Paper 90281, University Library of Munich, Germany.
    6. Yildirim, Ramazan & Masih, A. Mansur M., 2014. "The Effect of Recent Financial Crisis over Global Portfolio Diversification Opportunities – Empirical Evidence A Comparative Multivariate GARCH-DCC, MODWT and Wavelet Correlation Analysis," MPRA Paper 58269, University Library of Munich, Germany.

  40. Charles Amélie & Darné Olivier & Claude Diebolt, 2011. "A Revision of the US Business-Cycles Chronology 1790–1928," Working Papers 11-01, Association Française de Cliométrie (AFC).

    Cited by:

    1. Kamel Helali, 2022. "Markov Switching-Vector AutoRegression Model Analysis of the Economic and Growth Cycles in Tunisia and Its Main European Partners," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 13(1), pages 656-686, March.
    2. Dezhbakhsh, Hashem & Levy, Daniel, 2022. "Interpolation and shock persistence of prewar U.S. macroeconomic time series: A reconsideration," Economics Letters, Elsevier, vol. 213(C).

  41. Amélie Charles & Olivier Darné & Claude Diebolt & Laurent Ferrara, 2011. "A new monthly chronology of the US industrial cycles in the prewar economy," EconomiX Working Papers 2011-27, University of Paris Nanterre, EconomiX.

    Cited by:

    1. Sipan Aslan & Ceylan Yozgatligil & Cem Iyigun, 2018. "Temporal clustering of time series via threshold autoregressive models: application to commodity prices," Annals of Operations Research, Springer, vol. 260(1), pages 51-77, January.
    2. Claude Diebolt & Mamoudou Toure & Jamel Trabelsi, 2012. "Monetary Credibility Effects on Inflation Dynamics: A Macrohistorical Case Study," Working Papers 12-04, Association Française de Cliométrie (AFC).
    3. Antonin Aviat & Frédérique Bec & Claude Diebolt & Catherine Doz & Denis Ferrand & Laurent Ferrara & Eric Heyer & Valérie Mignon & Pierre-Alain Pionnier, 2021. "Dating business cycles in France: A reference chronology," Working Papers of BETA 2021-33, Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg.
    4. Claude Diebolt, 2020. "L’idée de régulation dans les sciences : hommage à l’épistémologue Jean Piaget," Working Papers 01-20, Association Française de Cliométrie (AFC).
    5. Thi Hong Van Hoang, 2012. "Has gold been a hedge against inflation in France from 1949 to 2011? Empirical evidence of the French specificity," Working Papers 12-05, Association Française de Cliométrie (AFC).

  42. Amélie Charles & Olivier Darné & Jessica Fouilloux, 2011. "Testing the martingale difference hypothesis in CO2 emission allowances," Post-Print halshs-00600724, HAL.

    Cited by:

    1. Sattarhoff, Cristina & Gronwald, Marc, 2022. "Measuring informational efficiency of the European carbon market — A quantitative evaluation of higher order dependence," International Review of Financial Analysis, Elsevier, vol. 84(C).
    2. Ladislav Kristoufek & Miloslav Vosvrda, 2012. "Measuring capital market efficiency: Global and local correlations structure," Papers 1208.1298, arXiv.org.
    3. Yun-Jung Lee & Neung-Woo Kim & Ki-Hong Choi & Seong-Min Yoon, 2020. "Analysis of the Informational Efficiency of the EU Carbon Emission Trading Market: Asymmetric MF-DFA Approach," Energies, MDPI, vol. 13(9), pages 1-14, May.
    4. Carmen López-Martín & Sonia Benito Muela & Raquel Arguedas, 2021. "Efficiency in cryptocurrency markets: new evidence," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 11(3), pages 403-431, September.
    5. Zdeněk Hlávka & Marie Hušková & Claudia Kirch & Simos G. Meintanis, 2017. "Fourier--type tests involving martingale difference processes," Econometric Reviews, Taylor & Francis Journals, vol. 36(4), pages 468-492, April.
    6. Cristina Sattarhoff & Marc Gronwald, 2018. "How to Measure Financial Market Efficiency? A Multifractality-Based Quantitative Approach with an Application to the European Carbon Market," CESifo Working Paper Series 7102, CESifo.
    7. Eunyoung Kim & Youngcheul Ahn & Doojin Ryu, 2014. "Application of the Carbon Emission Pricing Model in the Korean Market," Energy & Environment, , vol. 25(1), pages 63-78, February.
    8. Zhang, Wei & Li, Jing & Li, Guoxiang & Guo, Shucen, 2020. "Emission reduction effect and carbon market efficiency of carbon emissions trading policy in China," Energy, Elsevier, vol. 196(C).
    9. Todea, Alexandru & Pleşoianu, Anita, 2013. "The influence of foreign portfolio investment on informational efficiency: Empirical evidence from Central and Eastern European stock markets," Economic Modelling, Elsevier, vol. 33(C), pages 34-41.
    10. Chau, Frankie & Kuo, Jing-Ming & Shi, Yukun, 2015. "Arbitrage opportunities and feedback trading in emissions and energy markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 36(C), pages 130-147.
    11. Afees A. Salisu & Taofeek O. Ayinde, 2016. "Testing the Martingale Difference Hypothesis (MDH) with Structural Breaks: Evidence from Foreign Exchanges of Nigeria and South Africa," Journal of African Business, Taylor & Francis Journals, vol. 17(3), pages 342-359, September.

  43. Amélie Charles & Olivier Darné & Jae H Kim, 2010. "Small Sample Properties of Alternative Tests for Martingale Difference Hypothesis," Working Papers 2010.07, School of Economics, La Trobe University.

    Cited by:

    1. Graham Smith & Aneta Dyakova, 2014. "African Stock Markets: Efficiency and Relative Predictability," South African Journal of Economics, Economic Society of South Africa, vol. 82(2), pages 258-275, June.
    2. Ozkan, Oktay, 2021. "Impact of COVID-19 on stock market efficiency: Evidence from developed countries," Research in International Business and Finance, Elsevier, vol. 58(C).
    3. Cesar Rufino, 2013. "Random walks in the different sectoral submarkets of the Philippine Stock Exchange amid modernization," Philippine Review of Economics, University of the Philippines School of Economics and Philippine Economic Society, vol. 50(1), pages 57-82, June.
    4. Amélie Charles & Olivier Darné & Jae H. Kim & Etienne Redor, 2016. "Stock Exchange Mergers and Market," Post-Print hal-01238707, HAL.
    5. João A. Bastos & Jorge Caiado, 2014. "Clustering financial time series with variance ratio statistics," Quantitative Finance, Taylor & Francis Journals, vol. 14(12), pages 2121-2133, December.
    6. Amélie Charles & Olivier Darné & Jae H Kim, 2017. "Adaptive Markets Hypothesis for Islamic Stock Portfolios: Evidence from Dow Jones Size and Sector-Indices," Post-Print hal-01526483, HAL.
    7. Lazăr, Dorina & Todea, Alexandru & Filip, Diana, 2012. "Martingale difference hypothesis and financial crisis: Empirical evidence from European emerging foreign exchange markets," Economic Systems, Elsevier, vol. 36(3), pages 338-350.
    8. Amélie Charles & Olivier Darné & Jae H. Kim, 2010. "Exchange-Rate Return Predictability and the Adaptive Markets Hypothesis: Evidence from Major Foreign Exchange Rates," Working Papers hal-00547722, HAL.
    9. Jacek Karasinski, 2022. "The Impact of the COVID-19 Outbreak on the Weak-Form Informational Efficiency of the Warsaw Stock Exchange (Wplyw wybuchu epidemii COVID-19 na efektywnosc informacyjna Gieldy Papierow Wartosciowych w ," Research Reports, University of Warsaw, Faculty of Management, vol. 2(37), pages 15-28.
    10. Camilo González & Luisa Silva & Carmiña Vargas & Andrés M. Velasco, 2014. "Uncertainty in the Money Supply Mechanism and Interbank Markets in Colombia," Revista ESPE - Ensayos Sobre Política Económica, Banco de la República, vol. 32(73), pages 36-49, July.
    11. Verheyden, Tim & De Moor, Lieven & Van den Bossche, Filip, 2015. "Towards a new framework on efficient markets," Research in International Business and Finance, Elsevier, vol. 34(C), pages 294-308.
    12. Amélie Charles & Olivier Darné & Jae H Kim, 2017. "Adaptive markets hypothesis for Islamic stock indices: Evidence from Dow Jones size and sector-indices," Post-Print hal-01579718, HAL.
    13. Alexandru Todea & Dorina Lazar, 2012. "Global Crisis and Relative Efficiency: Empirical Evidence from Central and Eastern European Stock Markets," The Review of Finance and Banking, Academia de Studii Economice din Bucuresti, Romania / Facultatea de Finante, Asigurari, Banci si Burse de Valori / Catedra de Finante, vol. 4(1), pages 045-053, June.
    14. Peter C.B. Phillips & Sainan Jin, 2013. "Testing the Martingale Hypothesis," Cowles Foundation Discussion Papers 1912, Cowles Foundation for Research in Economics, Yale University.
    15. Köchling, Gerrit & Müller, Janis & Posch, Peter N., 2019. "Does the introduction of futures improve the efficiency of Bitcoin?," Finance Research Letters, Elsevier, vol. 30(C), pages 367-370.
    16. Amélie Charles & Olivier Darné & Jae H. Kim & Etienne Redor, 2014. "Stock Exchange Mergers and Market Efficiency," Working Papers hal-00940105, HAL.
    17. Camilo González & Luisa F. Silva & Carmiña O. Vargas & Andrés M. Velasco, 2013. "An exploration on interbank markets and the operational framework of monetary policy in Colombia," Borradores de Economia 10982, Banco de la Republica.
    18. Carmen López-Martín & Sonia Benito Muela & Raquel Arguedas, 2021. "Efficiency in cryptocurrency markets: new evidence," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 11(3), pages 403-431, September.
    19. Zdeněk Hlávka & Marie Hušková & Claudia Kirch & Simos G. Meintanis, 2017. "Fourier--type tests involving martingale difference processes," Econometric Reviews, Taylor & Francis Journals, vol. 36(4), pages 468-492, April.
    20. Vidal-Tomás, David, 2022. "Which cryptocurrency data sources should scholars use?," International Review of Financial Analysis, Elsevier, vol. 81(C).
    21. Linton, Oliver & Smetanina, Ekaterina, 2016. "Testing the martingale hypothesis for gross returns," Journal of Empirical Finance, Elsevier, vol. 38(PB), pages 664-689.
    22. Amélie Charles & Olivier Darné & Jae H. Kim, 2015. "Will precious metals shine ? A market efficiency perspective," Post-Print hal-01238706, HAL.
    23. Amélie Charles & Olivier Darné & Jae H. Kim, 2014. "Precious metals shine? A market efficiency perspective," Working Papers hal-01010516, HAL.
    24. Oktay Ozkan, 2020. "Time-varying return predictability and adaptive markets hypothesis: Evidence on MIST countries from a novel wild bootstrap likelihood ratio approach," Bogazici Journal, Review of Social, Economic and Administrative Studies, Bogazici University, Department of Economics, vol. 34(2), pages 101-113.
    25. Huai-Long Shi & Zhi-Qiang Jiang & Wei-Xing Zhou, 2016. "Time-varying return predictability in the Chinese stock market," Papers 1611.04090, arXiv.org.
    26. Biswabhusan Bhuyan & Subhamitra Patra & Ranjan Kumar Bhuian, 2020. "Market Adaptability and Evolving Predictability of Stock Returns: An Evidence from India," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 27(4), pages 605-619, December.
    27. Pedro L. P. Chaim & Márcio P. Laurini, 2019. "Foreign Exchange Expectation Errors and Filtration Enlargements," Stats, MDPI, vol. 2(2), pages 1-16, April.
    28. Sashikanta Khuntia & J. K. Pattanayak, 2020. "Evolving Efficiency of Exchange Rate Movement: An Evidence from Indian Foreign Exchange Market," Global Business Review, International Management Institute, vol. 21(4), pages 956-969, August.
    29. Graham Smith & Aneta Dyakova, 2016. "The Relative Predictability of Stock Markets in the Americas," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 21(2), pages 131-142, April.
    30. Eva Regnier, 2018. "Probability Forecasts Made at Multiple Lead Times," Management Science, INFORMS, vol. 64(5), pages 2407-2426, May.
    31. Todea, Alexandru & Pleşoianu, Anita, 2013. "The influence of foreign portfolio investment on informational efficiency: Empirical evidence from Central and Eastern European stock markets," Economic Modelling, Elsevier, vol. 33(C), pages 34-41.
    32. Bhatia, Madhur, 2023. "On the efficiency of the gold returns: An econometric exploration for India, USA and Brazil," Resources Policy, Elsevier, vol. 82(C).
    33. Kian-Ping Lim & Weiwei Luo & Jae H. Kim, 2013. "Are US stock index returns predictable? Evidence from automatic autocorrelation-based tests," Applied Economics, Taylor & Francis Journals, vol. 45(8), pages 953-962, March.
    34. Righi, Marcelo Brutti & Ceretta, Paulo Sergio, 2013. "Risk prediction management and weak form market efficiency in Eurozone financial crisis," International Review of Financial Analysis, Elsevier, vol. 30(C), pages 384-393.
    35. Afees A. Salisu & Taofeek O. Ayinde, 2016. "Testing the Martingale Difference Hypothesis (MDH) with Structural Breaks: Evidence from Foreign Exchanges of Nigeria and South Africa," Journal of African Business, Taylor & Francis Journals, vol. 17(3), pages 342-359, September.
    36. Stéphane Goutte & David Guerreiro & Bilel Sanhaji & Sophie Saglio & Julien Chevallier, 2019. "International Financial Markets," Post-Print halshs-02183053, HAL.

  44. Amélie Charles & Olivier Darné & Jae H. Kim, 2010. "Exchange-Rate Return Predictability and the Adaptive Markets Hypothesis: Evidence from Major Foreign Exchange Rates," Working Papers hal-00547722, HAL.

    Cited by:

    1. Sattarhoff, Cristina & Gronwald, Marc, 2022. "Measuring informational efficiency of the European carbon market — A quantitative evaluation of higher order dependence," International Review of Financial Analysis, Elsevier, vol. 84(C).
    2. Yamani, Ehab, 2019. "Diversification role of currency momentum for carry trade: Evidence from financial crises," Journal of Multinational Financial Management, Elsevier, vol. 49(C), pages 1-19.
    3. Iyke, Bernard Njindan & Phan, Dinh Hoang Bach & Narayan, Paresh Kumar, 2022. "Exchange rate return predictability in times of geopolitical risk," International Review of Financial Analysis, Elsevier, vol. 81(C).
    4. Hiremath, Gourishankar S & Kumari, Jyoti, 2014. "Stock returns predictability and the adaptive market hypothesis in emerging markets: evidence from India," MPRA Paper 58378, University Library of Munich, Germany.
    5. Lazăr, Dorina & Todea, Alexandru & Filip, Diana, 2012. "Martingale difference hypothesis and financial crisis: Empirical evidence from European emerging foreign exchange markets," Economic Systems, Elsevier, vol. 36(3), pages 338-350.
    6. Okoroafor, Ugochi Chibuzor & Leirvik, Thomas, 2022. "Time varying market efficiency in the Brent and WTI crude market," Finance Research Letters, Elsevier, vol. 45(C).
    7. Ma, T. & Fraser-Mackenzie, P.A.F. & Sung, M. & Kansara, A.P. & Johnson, J.E.V., 2022. "Are the least successful traders those most likely to exit the market? A survival analysis contribution to the efficient market debate," European Journal of Operational Research, Elsevier, vol. 299(1), pages 330-345.
    8. Rodriguez, E. & Aguilar-Cornejo, M. & Femat, R. & Alvarez-Ramirez, J., 2014. "US stock market efficiency over weekly, monthly, quarterly and yearly time scales," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 413(C), pages 554-564.
    9. Narayan, Paresh Kumar & Sharma, Susan Sunila & Phan, Dinh Hoang Bach & Liu, Guangqiang, 2020. "Predicting exchange rate returns," Emerging Markets Review, Elsevier, vol. 42(C).
    10. Green, Lawrence & Sung, Ming-Chien & Ma, Tiejun & Johnson, Johnnie E. V., 2019. "To what extent can new web-based technology improve forecasts? Assessing the economic value of information derived from Virtual Globes and its rate of diffusion in a financial market," European Journal of Operational Research, Elsevier, vol. 278(1), pages 226-239.
    11. Ladislav Kristoufek & Miloslav Vosvrda, 2015. "Gold, currencies and market efficiency," Papers 1510.08615, arXiv.org.
    12. Ali Almail & Fahad Almudhaf, 2017. "Adaptive Market Hypothesis: Evidence from three centuries of UK data," Economics and Business Letters, Oviedo University Press, vol. 6(2), pages 48-53.
    13. Boya, Christophe M., 2019. "From efficient markets to adaptive markets: Evidence from the French stock exchange," Research in International Business and Finance, Elsevier, vol. 49(C), pages 156-165.
    14. Hiremath, Gourishankar S & Kumari, Jyoti, 2013. "Stock Returns Predictability and the Adaptive Market Hypothesis: Evidence from India," MPRA Paper 52581, University Library of Munich, Germany.
    15. Osman Kilic & Joseph M. Marks & Kiseok Nam, 2022. "Predictable asset price dynamics, risk-return tradeoff, and investor behavior," Review of Quantitative Finance and Accounting, Springer, vol. 59(2), pages 749-791, August.
    16. Asif, Raheel & Frömmel, Michael, 2022. "Testing Long memory in exchange rates and its implications for the adaptive market hypothesis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 593(C).
    17. Kuck, Konstantin & Maderitsch, Robert, 2019. "Intra-day dynamics of exchange rates: New evidence from quantile regression," The Quarterly Review of Economics and Finance, Elsevier, vol. 71(C), pages 247-257.
    18. Pu, Yingjian & Yang, Baochen, 2022. "The commodity futures' historical basis in trading strategy and portfolio investment," Energy Economics, Elsevier, vol. 105(C).
    19. Siddique, Maryam, 2023. "Does the Adaptive Market Hypothesis Exist in Equity Market? Evidence from Pakistan Stock Exchange," OSF Preprints 9b5dx, Center for Open Science.
    20. Semei Coronado-Ram'irez & Pedro Celso-Arellano & Omar Rojas, 2014. "Adaptive Market Efficiency of Agricultural Commodity Futures Contracts," Papers 1412.8017, arXiv.org, revised Mar 2015.
    21. Bianchi, Robert J. & Drew, Michael E. & Fan, John Hua, 2016. "Commodities momentum: A behavioral perspective," Journal of Banking & Finance, Elsevier, vol. 72(C), pages 133-150.
    22. de Resende, Charlene C. & Pereira, Adriano C.M. & Cardoso, Rodrigo T.N. & de Magalhães, A.R. Bosco, 2017. "Investigating market efficiency through a forecasting model based on differential equations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 474(C), pages 199-212.
    23. Peter A. F. Fraser‐Mackenzie & Tiejun Ma & Ming‐Chien Sung & Johnnie E. V. Johnson, 2019. "Let's Call it Quits: Break‐Even Effects in the Decision to Stop Taking Risks," Risk Analysis, John Wiley & Sons, vol. 39(7), pages 1560-1581, July.
    24. Andrew Urquhart, 2017. "How predictable are precious metal returns?," The European Journal of Finance, Taylor & Francis Journals, vol. 23(14), pages 1390-1413, November.
    25. Yamani, Ehab, 2021. "Foreign exchange market efficiency and the global financial crisis: Fundamental versus technical information," The Quarterly Review of Economics and Finance, Elsevier, vol. 79(C), pages 74-89.
    26. Yamani, Ehab, 2021. "Can technical trading beat the foreign exchange market in times of crisis?," Global Finance Journal, Elsevier, vol. 48(C).
    27. Subhamitra Patra & Gourishankar S. Hiremath, 2022. "An Entropy Approach to Measure the Dynamic Stock Market Efficiency," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 20(2), pages 337-377, June.
    28. Chu, Jeffrey & Zhang, Yuanyuan & Chan, Stephen, 2019. "The adaptive market hypothesis in the high frequency cryptocurrency market," International Review of Financial Analysis, Elsevier, vol. 64(C), pages 221-231.
    29. Rangan Gupta & Vasilios Plakandaras, 2018. "Efficiency in BRICS Currency Markets using Long-Spans of Data: Evidence from Model-Free Tests of Directional Predictability," Working Papers 201836, University of Pretoria, Department of Economics.
    30. Xiong, Xiong & Meng, Yongqiang & Li, Xiao & Shen, Dehua, 2019. "An empirical analysis of the Adaptive Market Hypothesis with calendar effects:Evidence from China," Finance Research Letters, Elsevier, vol. 31(C).
    31. Sehrish Kayani & Usman Ayub & Imran Abbas Jadoon, 2019. "Adaptive Market Hypothesis and Artificial Neural Networks: Evidence from Pakistan," Global Regional Review, Humanity Only, vol. 4(2), pages 190-203, June.
    32. Ioana-Andreea Boboc & Mihai-Cristian Dinică, 2013. "An Algorithm for Testing the Efficient Market Hypothesis," PLOS ONE, Public Library of Science, vol. 8(10), pages 1-11, October.
    33. Biswabhusan Bhuyan & Subhamitra Patra & Ranjan Kumar Bhuian, 2020. "Market Adaptability and Evolving Predictability of Stock Returns: An Evidence from India," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 27(4), pages 605-619, December.
    34. Garcia, M.M. & Machado Pereira, A.C. & Acebal, J.L. & Bosco de Magalhães, A.R., 2020. "Forecast model for financial time series: An approach based on harmonic oscillators," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 549(C).
    35. Ferreira, Joaquim & Morais, Flávio, 2023. "Predict or to be predicted? A transfer entropy view between adaptive green markets, structural shocks and sentiment index," Finance Research Letters, Elsevier, vol. 56(C).
    36. Pınar Evrim Mandacı & F. Dilvin Taskın & Zeliha Can Ergun, 2019. "Adaptive Market Hypothesis," International Journal of Economics & Business Administration (IJEBA), International Journal of Economics & Business Administration (IJEBA), vol. 0(4), pages 84-101.
    37. Ghazani, Majid Mirzaee & Ebrahimi, Seyed Babak, 2019. "Testing the adaptive market hypothesis as an evolutionary perspective on market efficiency: Evidence from the crude oil prices," Finance Research Letters, Elsevier, vol. 30(C), pages 60-68.
    38. Majid Mirzaee Ghazani & Mohammad Ali Jafari, 2021. "Cryptocurrencies, gold, and WTI crude oil market efficiency: a dynamic analysis based on the adaptive market hypothesis," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-26, December.
    39. Adeyeye Patrick Olufemi & Aluko Olufemi Adewale & Migiro Stephen Oseko, 2017. "Efficiency of Foreign Exchange Markets in Sub-Saharan Africa in the Presence of Structural Break: A Linear and Non-Linear Testing Approach," Journal of Economics and Behavioral Studies, AMH International, vol. 9(4), pages 122-131.
    40. Bartsch, Zachary, 2019. "Economic policy uncertainty and dollar-pound exchange rate return volatility," Journal of International Money and Finance, Elsevier, vol. 98(C), pages 1-1.
    41. Mostafa Raeisi Sarkandiz & Robabeh Bahlouli, 2019. "The Stock Market between Classical and Behavioral Hypotheses: An Empirical Investigation of the Warsaw Stock Exchange," Econometric Research in Finance, SGH Warsaw School of Economics, Collegium of Economic Analysis, vol. 4(2), pages 67-88, December.
    42. Panopoulou, Ekaterini & Souropanis, Ioannis, 2019. "The role of technical indicators in exchange rate forecasting," Journal of Empirical Finance, Elsevier, vol. 53(C), pages 197-221.
    43. Khuntia, Sashikanta & Pattanayak, J.K., 2018. "Adaptive market hypothesis and evolving predictability of bitcoin," Economics Letters, Elsevier, vol. 167(C), pages 26-28.
    44. Yang, Yan-Hong & Shao, Ying-Hui & Shao, Hao-Lin & Stanley, H. Eugene, 2019. "Revisiting the weak-form efficiency of the EUR/CHF exchange rate market: Evidence from episodes of different Swiss franc regimes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 523(C), pages 734-746.
    45. Katusiime, Lorna & Shamsuddin, Abul & Agbola, Frank W., 2015. "Foreign exchange market efficiency and profitability of trading rules: Evidence from a developing country," International Review of Economics & Finance, Elsevier, vol. 35(C), pages 315-332.
    46. Okorie, David Iheke & Lin, Boqiang, 2021. "Adaptive market hypothesis: The story of the stock markets and COVID-19 pandemic," The North American Journal of Economics and Finance, Elsevier, vol. 57(C).
    47. Urquhart, Andrew & McGroarty, Frank, 2016. "Are stock markets really efficient? Evidence of the adaptive market hypothesis," International Review of Financial Analysis, Elsevier, vol. 47(C), pages 39-49.
    48. Bernard Njindan Iyke, 2019. "A Test Of The Efficiency Of The Foreign Exchange Market In Indonesia," Bulletin of Monetary Economics and Banking, Bank Indonesia, vol. 0(12th BMEB), pages 1-26, January.

  45. Amélie Charles & Olivier Darné, 2010. "A note on the uncertain trend in US real GNP: Evidence from robust unit root test," Working Papers hal-00547737, HAL.

    Cited by:

    1. WenShwo Fang & Stephen M. Miller, 2012. "Output Growth and Its Volatility: The Gold Standard through the Great Moderation," Working papers 2012-11, University of Connecticut, Department of Economics.
    2. Dezhbakhsh, Hashem & Levy, Daniel, 2022. "Interpolation and shock persistence of prewar U.S. macroeconomic time series: A reconsideration," Economics Letters, Elsevier, vol. 213(C).

  46. Amélie Charles & Olivier Darné & Jessica Fouilloux, 2010. "Testing the Martingale Difference Hypothesis in the EU ETS Markets for the CO2 Emission Allowances: Evidence from Phase I and Phase II," Working Papers hal-00473727, HAL.

    Cited by:

    1. Ciumas Cristina & Chis Diana-Maria & Botos Horia Mircea, 2012. "Global Financial Crisis And Unit-Linked Insurance Markets Efficiency: Empirical Evidence From Central And Eastern European Countries," Annals of Faculty of Economics, University of Oradea, Faculty of Economics, vol. 1(2), pages 443-448, December.
    2. Xiting Gong & Sean X. Zhou, 2013. "Optimal Production Planning with Emissions Trading," Operations Research, INFORMS, vol. 61(4), pages 908-924, August.

  47. Amélie Charles & Olivier Darné & Jean-François Hoarau & Philippe Jean-Pierre, 2010. "La persistance des écarts de richesse entre La Réunion et les standards français et européens : l'apport des tests de racine unitaire," Post-Print hal-00761933, HAL.

    Cited by:

    1. Michaël GOUJON & François HERMET, 2012. "L’Indice De Développement Humain : Une Évaluation Pour Mayotte," Region et Developpement, Region et Developpement, LEAD, Universite du Sud - Toulon Var, vol. 36, pages 229-244.
    2. Françoise RIVIERE & Michel DIMOU, 2017. "Modèles et stratégies de développement des petites économies insulaires. Revue de la littérature et nouveaux paradigmes," Working Paper 0bd96404-7210-4678-93d6-4, Agence française de développement.

  48. Amélie Charles & Olivier Darné, 2009. "Variance ratio tests of random walk: An overview," Post-Print hal-00771078, HAL.

    Cited by:

    1. Amélie Charles & Olivier Darné & Jessica Fouilloux, 2010. "Testing the Martingale Difference Hypothesis in the EU ETS Markets for the CO2 Emission Allowances: Evidence from Phase I and Phase II," Post-Print hal-00797491, HAL.
    2. Sibanjan Mishra, 2019. "Testing Martingale Hypothesis Using Variance Ratio Tests: Evidence from High-frequency Data of NCDEX Soya Bean Futures," Global Business Review, International Management Institute, vol. 20(6), pages 1407-1422, December.
    3. Giuseppe Pernagallo & Benedetto Torrisi, 2019. "Blindfolded monkeys or financial analysts: who is worth your money? New evidence on informational inefficiencies in the U.S. stock market," Papers 1904.03488, arXiv.org, revised Oct 2019.
    4. Ana Rita Gonzaga & Helder Sebastião, 2012. "As Ações Portuguesas Seguem um Random Walk? Implicações para a Eficiência de Mercado e para a Definição de Estratégias de Transação," GEMF Working Papers 2012-02, GEMF, Faculty of Economics, University of Coimbra.
    5. Tiwari, Aviral Kumar & Kumar, Satish & Pathak, Rajesh & Roubaud, David, 2019. "Testing the oil price efficiency using various measures of long-range dependence," Energy Economics, Elsevier, vol. 84(C).
    6. Yang, Chen & Lv, Fei & Fang, Libing & Shang, Xingxing, 2020. "The pricing efficiency of crude oil futures in the Shanghai International Exchange," Finance Research Letters, Elsevier, vol. 36(C).
    7. Palani-Rajan Kadapakkam & Timothy Krause & Yiuman Tse, 2015. "Exchange traded funds, size-based portfolios, and market efficiency," Review of Quantitative Finance and Accounting, Springer, vol. 45(1), pages 89-110, July.
    8. Mobarek, Asma & Fiorante, Angelo, 2014. "The prospects of BRIC countries: Testing weak-form market efficiency," Research in International Business and Finance, Elsevier, vol. 30(C), pages 217-232.
    9. Amélie Charles & Olivier Darné, 2009. "The random walk hypothesis for Chinese stock markets: Evidence from variance ratio tests," Post-Print hal-00771080, HAL.
    10. Charles, Amélie & Darné, Olivier & Fouilloux, Jessica, 2011. "Testing the martingale difference hypothesis in CO2 emission allowances," Economic Modelling, Elsevier, vol. 28(1-2), pages 27-35, January.
    11. Ashok Chanabasangouda Patil & Shailesh Rastogi, 2019. "Time-Varying Price–Volume Relationship and Adaptive Market Efficiency: A Survey of the Empirical Literature," JRFM, MDPI, vol. 12(2), pages 1-18, June.
    12. Lazăr, Dorina & Todea, Alexandru & Filip, Diana, 2012. "Martingale difference hypothesis and financial crisis: Empirical evidence from European emerging foreign exchange markets," Economic Systems, Elsevier, vol. 36(3), pages 338-350.
    13. Ayoub Ammy-Driss & Matthieu Garcin, 2021. "Efficiency of the financial markets during the COVID-19 crisis: time-varying parameters of fractional stable dynamics," Working Papers hal-02903655, HAL.
    14. Amélie Charles & Olivier Darné & Jae H. Kim, 2010. "Exchange-Rate Return Predictability and the Adaptive Markets Hypothesis: Evidence from Major Foreign Exchange Rates," Working Papers hal-00547722, HAL.
    15. Amira Akl Ahmed, 2014. "Evolving and relative efficiency of MENA stock markets: evidence from rolling joint variance ratio tests," Ensayos Revista de Economia, Universidad Autonoma de Nuevo Leon, Facultad de Economia, vol. 0(1), pages 91-126, May.
    16. Ayoub Ammy-Driss & Matthieu Garcin, 2020. "Efficiency of the financial markets during the COVID-19 crisis: time-varying parameters of fractional stable dynamics," Papers 2007.10727, arXiv.org, revised Nov 2021.
    17. Marc Lamphiere & Jonathan Blackledge & Derek Kearney, 2021. "Carbon Futures Trading and Short-Term Price Prediction: An Analysis Using the Fractal Market Hypothesis and Evolutionary Computing," Mathematics, MDPI, vol. 9(9), pages 1-32, April.
    18. Jean-Philippe Bouchaud & Damien Challet, 2016. "Why have asset price properties changed so little in 200 years," Papers 1605.00634, arXiv.org.
    19. Verheyden, Tim & De Moor, Lieven & Van den Bossche, Filip, 2015. "Towards a new framework on efficient markets," Research in International Business and Finance, Elsevier, vol. 34(C), pages 294-308.
    20. Samuel Showalter & Jeffrey Gropp, 2019. "Validating Weak-form Market Efficiency in United States Stock Markets with Trend Deterministic Price Data and Machine Learning," Papers 1909.05151, arXiv.org.
    21. Syeda Tayyaba Ijaz & Rabia Komal, 2015. "Role Of Hurst Exponent In Prediction Of Market Efficiency In Kse-100 Index," IBT Journal of Business Studies (JBS), Ilma University, Faculty of Management Science, vol. 11(2), pages 41-54.
    22. Ciumas Cristina & Chis Diana-Maria & Botos Horia Mircea, 2012. "Global Financial Crisis And Unit-Linked Insurance Markets Efficiency: Empirical Evidence From Central And Eastern European Countries," Annals of Faculty of Economics, University of Oradea, Faculty of Economics, vol. 1(2), pages 443-448, December.
    23. Seok Young Hong & Oliver Linton & Hui Jun Zhang, 2014. "Multivariate Variance Ratio Statistics," Cambridge Working Papers in Economics 1459, Faculty of Economics, University of Cambridge.
    24. Emilian DOBRESCU, 2016. "Controversies over the Size of the Public Budget," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(4), pages 5-34, December.
    25. Takeshi Inoue & Shigeyuki Hamori, 2011. "An empirical analysis on the efficiency of the microfinance investment market," Economics Bulletin, AccessEcon, vol. 31(3), pages 2725-2735.
    26. Charfeddine, Lanouar & Khediri, Karim Ben, 2016. "Time varying market efficiency of the GCC stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 444(C), pages 487-504.
    27. Mirzaee Ghazani, Majid & Khalili Araghi, Mansour, 2014. "Evaluation of the adaptive market hypothesis as an evolutionary perspective on market efficiency: Evidence from the Tehran stock exchange," Research in International Business and Finance, Elsevier, vol. 32(C), pages 50-59.
    28. Kerry Liu, 2022. "The Chinese Government Bond Markets: Foreign Investments and Market Efficiency," Global Journal of Emerging Market Economies, Emerging Markets Forum, vol. 14(1), pages 93-104, January.
    29. Seok Young Hong & Oliver Linton & Hui Jun Zhang, 2014. "Multivariate variance ratio statistics," CeMMAP working papers 29/14, Institute for Fiscal Studies.
    30. Liesivaara, Petri & Myyrä, Sami, 2016. "Income stabilisation tool and the pig gross margin index for the Finnish pig sector," 90th Annual Conference, April 4-6, 2016, Warwick University, Coventry, UK 236360, Agricultural Economics Society.
    31. Carmen López-Martín & Sonia Benito Muela & Raquel Arguedas, 2021. "Efficiency in cryptocurrency markets: new evidence," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 11(3), pages 403-431, September.
    32. Hill, Jonathan B. & Motegi, Kaiji, 2019. "Testing the white noise hypothesis of stock returns," Economic Modelling, Elsevier, vol. 76(C), pages 231-242.
    33. Palani-Rajan Kadapakkam & Timothy Krause & Yiuman Tse, 2013. "Exchange Traded Funds, Size-Based Portfolios, And Market Efficiency," Working Papers 0214fin, College of Business, University of Texas at San Antonio.
    34. Min Bai & Feng Bai & Yafeng Qin, 2022. "Emerging economies openness and efficiency," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 43(3), pages 659-672, April.
    35. Eckhard Platen & Renata Rendek, 2019. "Dynamics of a Well-Diversified Equity Index," Research Paper Series 398, Quantitative Finance Research Centre, University of Technology, Sydney.
    36. Seok Young Hong & Oliver Linton & Hui Jun Zhang, 2015. "An investigation into multivariate variance ratio statistics and their application to stock market predictability," CeMMAP working papers 13/15, Institute for Fiscal Studies.
    37. Michael Buchner & Tobias A. Jopp, 2019. "Full steam ahead: Insider knowledge, stock trading and the nationalization of the railways in Prussia around 1879," Working Papers 0151, European Historical Economics Society (EHES).
    38. Lim, Kian-Ping & Kim, Jae H., 2011. "Trade openness and the informational efficiency of emerging stock markets," Economic Modelling, Elsevier, vol. 28(5), pages 2228-2238, September.
    39. Victor Dragotă & Elena Ţilică, 2014. "Market efficiency of the Post Communist East European stock markets," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 22(2), pages 307-337, June.
    40. Charles, Amélie & Darné, Olivier, 2009. "The efficiency of the crude oil markets: Evidence from variance ratio tests," Energy Policy, Elsevier, vol. 37(11), pages 4267-4272, November.
    41. Mohanty, Sunil K. & Mishra, Sibanjan, 2020. "Regulatory reform and market efficiency: The case of Indian agricultural commodity futures markets," Research in International Business and Finance, Elsevier, vol. 52(C).
    42. Halser, Christoph & Paraschiv, Florentina & Russo, Marianna, 2023. "Oil–gas price relationships on three continents: Disruptions and equilibria," Journal of Commodity Markets, Elsevier, vol. 31(C).
    43. Seok Young Hong & Oliver Linton & Hui Jun Zhang, 2015. "An investigation into multivariate variance ratio statistics and their application to stock market predictability," CeMMAP working papers CWP13/15, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    44. Ryu, Inug & Jang, Hanwool & Kim, Dongshin & Ahn, Kwangwon, 2021. "Market Efficiency of US REITs: A Revisit," Chaos, Solitons & Fractals, Elsevier, vol. 150(C).
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    49. Graham Smith & Aneta Dyakova, 2016. "The Relative Predictability of Stock Markets in the Americas," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 21(2), pages 131-142, April.
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    54. Righi, Marcelo Brutti & Ceretta, Paulo Sergio, 2013. "Risk prediction management and weak form market efficiency in Eurozone financial crisis," International Review of Financial Analysis, Elsevier, vol. 30(C), pages 384-393.
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  49. Barhoumi, K. & Darné, O. & Ferrara, L., 2009. "Are disaggregate data useful for factor analysis in forecasting French GDP?," Working papers 232, Banque de France.

    Cited by:

    1. Lamprou, Dimitra, 2016. "Nowcasting GDP in Greece: The impact of data revisions and forecast origin on model selection and performance," The Journal of Economic Asymmetries, Elsevier, vol. 14(PA), pages 93-102.
    2. Marie Bessec, 2013. "Short‐Term Forecasts of French GDP: A Dynamic Factor Model with Targeted Predictors," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 32(6), pages 500-511, September.
    3. António Rua & Carlos Melo Gouveia & Nuno Lourenço, 2020. "Forecasting tourism with targeted predictors in a data-rich environment," Working Papers w202005, Banco de Portugal, Economics and Research Department.
    4. Chien-jung Ting & Yi-Long Hsiao & Rui-jun Su, 2022. "Application of the Real-Time Tourism Data in Nowcasting the Service Consumption in Taiwan," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 12(4), pages 1-4.
    5. Reichlin, Lucrezia & Giannone, Domenico & Modugno, Michele & Banbura, Marta, 2012. "Now-casting and the real-time data flow," CEPR Discussion Papers 9112, C.E.P.R. Discussion Papers.
    6. Branimir, Jovanovic & Magdalena, Petrovska, 2010. "Forecasting Macedonian GDP: Evaluation of different models for short-term forecasting," MPRA Paper 43162, University Library of Munich, Germany.
    7. Doz, Catherine & Giannone, Domenico & Reichlin, Lucrezia, 2011. "A two-step estimator for large approximate dynamic factor models based on Kalman filtering," Journal of Econometrics, Elsevier, vol. 164(1), pages 188-205, September.
    8. Mahmut Günay, 2015. "Forecasting Turkish Industrial Production Growth With Static Factor Models," International Econometric Review (IER), Econometric Research Association, vol. 7(2), pages 64-78, September.
    9. Luciani, Matteo & Pundit, Madhavi & Ramayandi, Arief & Veronese , Giovanni, 2015. "Nowcasting Indonesia," ADB Economics Working Paper Series 471, Asian Development Bank.
    10. Lombardi, Marco J. & Maier, Philipp, 2011. "Forecasting economic growth in the euro area during the Great Moderation and the Great Recession," Working Paper Series 1379, European Central Bank.
    11. Christian Glocker & Philipp Wegmüller, 2017. "Business Cycle Dating and Forecasting with Real-time Swiss GDP Data," WIFO Working Papers 542, WIFO.
    12. Dahlhaus, Tatjana & Guénette, Justin-Damien & Vasishtha, Garima, 2017. "Nowcasting BRIC+M in real time," International Journal of Forecasting, Elsevier, vol. 33(4), pages 915-935.
    13. Tony Chernis & Rodrigo Sekkel, 2017. "A dynamic factor model for nowcasting Canadian GDP growth," Empirical Economics, Springer, vol. 53(1), pages 217-234, August.
    14. Karen Poghosyan, 2015. "Alternative models for forecasting the key macroeconomic variables in Armenia (in Russian)," Quantile, Quantile, issue 13, pages 25-39, May.
    15. Danilo Cascaldi-Garcia & Thiago Revil T. Ferreira & Domenico Giannone & Michele Modugno, 2021. "Back to the Present: Learning about the Euro Area through a Now-casting Model," International Finance Discussion Papers 1313, Board of Governors of the Federal Reserve System (U.S.).
    16. Matteo Luciani & Lorenzo Ricci, 2014. "Nowcasting Norway," International Journal of Central Banking, International Journal of Central Banking, vol. 10(4), pages 215-248, December.
    17. Laurent Ferrara & Anna Simoni, 2019. "When are Google data useful to nowcast GDP? An approach via pre-selection and shrinkage," Working Papers 2019-04, Center for Research in Economics and Statistics.
    18. Garnitz, Johanna & Lehmann, Robert & Wohlrabe, Klaus, 2019. "Forecasting GDP all over the world using leading indicators based on comprehensive survey data," Munich Reprints in Economics 78264, University of Munich, Department of Economics.
    19. Alexander Chudik & Valerie Grossman & M. Hashem Pesaran, 2014. "A multi-country approach to forecasting output growth using PMIs," Globalization Institute Working Papers 213, Federal Reserve Bank of Dallas.
    20. Jason Angelopoulos, 2017. "Creating and assessing composite indicators: Dynamic applications for the port industry and seaborne trade," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 19(1), pages 126-159, March.
    21. Zubarev Andrey & Rybak Konstantin, 2021. "GDP Nowcasting: Dynamic Factor Model vs. Official Forecasts [Наукастинг Ввп: Динамическая Факторная Модель И Официальные Прогнозы]," Russian Economic Development, Gaidar Institute for Economic Policy, issue 12, pages 34-40, December.
    22. Soybilgen, Barış & Yazgan, Ege, 2018. "Evaluating nowcasts of bridge equations with advanced combination schemes for the Turkish unemployment rate," Economic Modelling, Elsevier, vol. 72(C), pages 99-108.
    23. Bušs, Ginters, 2009. "Comparing forecasts of Latvia's GDP using simple seasonal ARIMA models and direct versus indirect approach," MPRA Paper 16684, University Library of Munich, Germany.
    24. , 2020. "Forecasting U.S. Economic Growth in Downturns Using Cross-Country Data," Research Working Paper RWP 20-09, Federal Reserve Bank of Kansas City.
    25. Andreas Karatahansopoulos & Georgios Sermpinis & Jason Laws & Christian Dunis, 2014. "Modelling and Trading the Greek Stock Market with Gene Expression and Genetic Programing Algorithms," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 33(8), pages 596-610, December.
    26. Barış Soybilgen & Ege Yazgan, 2021. "Nowcasting US GDP Using Tree-Based Ensemble Models and Dynamic Factors," Computational Economics, Springer;Society for Computational Economics, vol. 57(1), pages 387-417, January.
    27. Evzen Kocenda & Karen Poghosyan, 2018. "Nowcasting real GDP growth with business tendency surveys data: A cross country analysis," KIER Working Papers 1002, Kyoto University, Institute of Economic Research.
    28. Charalampos Stasinakis & Georgios Sermpinis & Konstantinos Theofilatos & Andreas Karathanasopoulos, 2016. "Forecasting US Unemployment with Radial Basis Neural Networks, Kalman Filters and Support Vector Regressions," Computational Economics, Springer;Society for Computational Economics, vol. 47(4), pages 569-587, April.
    29. Baris Soybilgen, 2017. "Identifying Us Business Cycle Regimes Using Factor Augmented Neural Network Models," Working Papers 1703, The Center for Financial Studies (CEFIS), Istanbul Bilgi University.
    30. Branimir Jovanovic & Magdalena Petrovska, 2010. "Forecasting Macedonian GDP: Evaluation of different models for short-term forecasting," Working Papers 2010-02, National Bank of the Republic of North Macedonia, revised Aug 2010.
    31. Tjeerd M. Boonman & Jan P. A. M. Jacobs & Gerard H. Kuper, 2017. "An Early Warning System for currency crises in Argentina and Brazil 1990-2009," EconoQuantum, Revista de Economia y Finanzas, Universidad de Guadalajara, Centro Universitario de Ciencias Economico Administrativas, Departamento de Metodos Cuantitativos y Maestria en Economia., vol. 14(2), pages 47-68, Julio-Dic.
    32. Chien-jung Ting & Yi-Long Hsiao, 2022. "Nowcasting the GDP in Taiwan and the Real-Time Tourism Data," Advances in Management and Applied Economics, SCIENPRESS Ltd, vol. 12(3), pages 1-2.
    33. Lourenço, Nuno & Gouveia, Carlos Melo & Rua, António, 2021. "Forecasting tourism with targeted predictors in a data-rich environment," Economic Modelling, Elsevier, vol. 96(C), pages 445-454.
    34. Brunhes-Lesage, Véronique & Darné, Olivier, 2012. "Nowcasting the French index of industrial production: A comparison from bridge and factor models," Economic Modelling, Elsevier, vol. 29(6), pages 2174-2182.
    35. Zhang, Qin & Ni, He & Xu, Hao, 2023. "Nowcasting Chinese GDP in a data-rich environment: Lessons from machine learning algorithms," Economic Modelling, Elsevier, vol. 122(C).
    36. Anna Norin, 2011. "Nowcasting of the Gross Regional Product," ERSA conference papers ersa10p768, European Regional Science Association.
    37. Caruso, Alberto, 2019. "Macroeconomic news and market reaction: Surprise indexes meet nowcasting," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1725-1734.
    38. Barhoumi, K. & Darné, O. & Ferrara, L., 2013. "Dynamic Factor Models: A review of the Literature ," Working papers 430, Banque de France.
    39. Zubarev Andrey & Rybak Konstantin, 2021. "Наукастинг Ввп: Динамическая Факторная Модель И Официальные Прогнозы," Russian Economic Development (in Russian), Gaidar Institute for Economic Policy, issue 12, pages 34-40, December.
    40. Tjeerd M. Boonman & Jan P.A.M. Jacobs & Gerard H. Kuper, 2011. "Why didn't the Global Financial Crisis hit Latin America?," CIRANO Working Papers 2011s-63, CIRANO.
    41. Françoise Charpin, 2011. "Réévaluation des modèles d’estimation précoce de la croissance," Post-Print hal-03461522, HAL.
    42. Dias, Francisco & Pinheiro, Maximiano & Rua, António, 2015. "Forecasting Portuguese GDP with factor models: Pre- and post-crisis evidence," Economic Modelling, Elsevier, vol. 44(C), pages 266-272.
    43. Ibarra, Raul, 2012. "Do disaggregated CPI data improve the accuracy of inflation forecasts?," Economic Modelling, Elsevier, vol. 29(4), pages 1305-1313.
    44. Antipa, Pamfili & Barhoumi, Karim & Brunhes-Lesage, Véronique & Darné, Olivier, 2012. "Nowcasting German GDP: A comparison of bridge and factor models," Journal of Policy Modeling, Elsevier, vol. 34(6), pages 864-878.
    45. Konstantin S. Rybak, 2023. "Анализ Важности Глобальных Факторов Для Наукастинга Ввп," Russian Economic Development (in Russian), Gaidar Institute for Economic Policy, issue 12, pages 18-23, December.
    46. Danilo Cascaldi-Garcia & Matteo Luciani & Michele Modugno, 2023. "Lessons from Nowcasting GDP across the World," International Finance Discussion Papers 1385, Board of Governors of the Federal Reserve System (U.S.).
    47. Daniela Bragoli & Michele Modugno, 2016. "A Nowcasting Model for Canada: Do U.S. Variables Matter?," Finance and Economics Discussion Series 2016-036, Board of Governors of the Federal Reserve System (U.S.).
    48. Bragoli, Daniela, 2017. "Now-casting the Japanese economy," International Journal of Forecasting, Elsevier, vol. 33(2), pages 390-402.
    49. Bantis, Evripidis & Clements, Michael P. & Urquhart, Andrew, 2023. "Forecasting GDP growth rates in the United States and Brazil using Google Trends," International Journal of Forecasting, Elsevier, vol. 39(4), pages 1909-1924.
    50. Bellégo, C. & Ferrara, L., 2009. "Forecasting Euro-area recessions using time-varying binary response models for financial," Working papers 259, Banque de France.
    51. Bellégo, C. & Ferrara, L., 2012. "Macro-financial linkages and business cycles: A factor-augmented probit approach," Economic Modelling, Elsevier, vol. 29(5), pages 1793-1797.
    52. Zdeněk Zmeškal & Dana Dluhošová & Karolina Lisztwanová & Antonín Pončík & Iveta Ratmanová, 2023. "Distribution Prediction of Decomposed Relative EVA Measure with Levy-Driven Mean-Reversion Processes: The Case of an Automotive Sector of a Small Open Economy," Forecasting, MDPI, vol. 5(2), pages 1-19, May.
    53. Françoise Charpin, 2011. "Réévaluation des modèles d’estimation précoce de la croissance," SciencePo Working papers Main hal-03461522, HAL.
    54. Jason Angelopoulos & Costas I. Chlomoudis, 2017. "A Generalized Dynamic Factor Model for the U.S. Port Sector," SPOUDAI Journal of Economics and Business, SPOUDAI Journal of Economics and Business, University of Piraeus, vol. 67(1), pages 22-37, January-M.
    55. Chatelais, Nicolas & Stalla-Bourdillon, Arthur & Chinn, Menzie D., 2023. "Forecasting real activity using cross-sectoral stock market information," Journal of International Money and Finance, Elsevier, vol. 131(C).
    56. Porshakov, Alexey & Deryugina, Elena & Ponomarenko, Alexey & Sinyakov, Andrey, 2015. "Nowcasting and short-term forecasting of Russian GDP with a dynamic factor model," BOFIT Discussion Papers 19/2015, Bank of Finland Institute for Emerging Economies (BOFIT).
    57. António Rua, 2016. "A wavelet-based multivariate multiscale approach for forecasting," Working Papers w201612, Banco de Portugal, Economics and Research Department.
    58. Nicolas Chatelais & Arthur Stalla-Bourdillon & Menzie D. Chinn, 2022. "Macroeconomic Forecasting using Filtered Signals from a Stock Market Cross Section," NBER Working Papers 30305, National Bureau of Economic Research, Inc.
    59. Monica Defend & Aleksey Min & Lorenzo Portelli & Franz Ramsauer & Francesco Sandrini & Rudi Zagst, 2021. "Quantifying Drivers of Forecasted Returns Using Approximate Dynamic Factor Models for Mixed-Frequency Panel Data," Forecasting, MDPI, vol. 3(1), pages 1-35, February.
    60. Stéphanie Guichard & Elena Rusticelli, 2011. "A Dynamic Factor Model for World Trade Growth," OECD Economics Department Working Papers 874, OECD Publishing.
    61. Dimitra Lamprou, 2015. "Nowcasting GDP in Greece: A Note on Forecasting Improvements from the Use of Bridge Models," South-Eastern Europe Journal of Economics, Association of Economic Universities of South and Eastern Europe and the Black Sea Region, vol. 13(1), pages 85-100.
    62. Modugno, Michele & Soybilgen, Barış & Yazgan, Ege, 2016. "Nowcasting Turkish GDP and news decomposition," International Journal of Forecasting, Elsevier, vol. 32(4), pages 1369-1384.
    63. Caruso, Alberto, 2018. "Nowcasting with the help of foreign indicators: The case of Mexico," Economic Modelling, Elsevier, vol. 69(C), pages 160-168.
    64. Daniel Armeanu & Jean Vasile Andrei & Leonard Lache & Mirela Panait, 2017. "A multifactor approach to forecasting Romanian gross domestic product (GDP) in the short run," PLOS ONE, Public Library of Science, vol. 12(7), pages 1-23, July.
    65. Alberto Caruso, 2015. "Nowcasting Mexican GDP," Working Papers ECARES ECARES 2015-40, ULB -- Universite Libre de Bruxelles.
    66. Alain Kabundi & Elmarie Nel & Franz Ruch, 2016. "Nowcasting Real GDP growth in South Africa," Working Papers 581, Economic Research Southern Africa.
    67. Мекенбаева Камила // Mekenbayeva Kamila & Karel Musil, 2017. "Система прогнозирования в Национальном Банке Казахстана: наукаст на основа опросов // Forecasting system at the National Bank of Kazakhstan: survey-based nowcasting," Working Papers #2017-1, National Bank of Kazakhstan.
    68. Christophe Bellégo & Laurent Ferrara, 2010. "A factor-augmented probit model for business cycle analysis," EconomiX Working Papers 2010-14, University of Paris Nanterre, EconomiX.
    69. Michael H. Breitner & Christian Dunis & Hans-Jörg Mettenheim & Christopher Neely & Georgios Sermpinis & Georgios Sermpinis & Charalampos Stasinakis & Konstantinos Theofilatos & Andreas Karathanasopoul, 2014. "Inflation and Unemployment Forecasting with Genetic Support Vector Regression," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 33(6), pages 471-487, September.
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    71. C. Marsilli, 2014. "Variable Selection in Predictive MIDAS Models," Working papers 520, Banque de France.
    72. Konstantin S. Rybak, 2023. "Evaluating the Role of Global Factors in GDP Nowcasting [Анализ Важности Глобальных Факторов Для Наукастинга Ввп]," Russian Economic Development, Gaidar Institute for Economic Policy, issue 12, pages 18-23, December.
    73. Ard Reijer & Andreas Johansson, 2019. "Nowcasting Swedish GDP with a large and unbalanced data set," Empirical Economics, Springer, vol. 57(4), pages 1351-1373, October.
    74. Urasawa, Satoshi, 2014. "Real-time GDP forecasting for Japan: A dynamic factor model approach," Journal of the Japanese and International Economies, Elsevier, vol. 34(C), pages 116-134.

  50. Amélie Charles & Olivier Darné, 2009. "The random walk hypothesis for Chinese stock markets: Evidence from variance ratio tests," Post-Print hal-00771080, HAL.

    Cited by:

    1. Andrea Beltratti & Bernardo Bortolotti & Marianna Caccavaio, 2014. "Stock market efficiency in China: evidence from the split-share reform," Temi di discussione (Economic working papers) 969, Bank of Italy, Economic Research and International Relations Area.
    2. Dinabandhu Bag & Saurabh Goel, 2023. "Weak Form of Call Auction Prices: Simulation Using Monte Carlo Variants," Capital Markets Review, Malaysian Finance Association, vol. 31(1), pages 59-71.
    3. Feyyaz Zeren & Filiz Konuk, 2013. "Testing The Random Walk Hypothesis For Emerging Markets: Evidence From Linear And Non-Linear Unit Root Tests," Romanian Economic Business Review, Romanian-American University, vol. 8(4), pages 61-71, december.
    4. Hiremath, Gourishankar S & Bandi, Kamaiah, 2012. "Variance ratios, structural breaks and nonrandom walk behaviour in the Indian stock returns," MPRA Paper 48710, University Library of Munich, Germany.
    5. Chen, Jing & Buckland, Roger & Williams, Julian, 2011. "Regulatory changes, market integration and spillover effects in the Chinese A, B and Hong Kong equity markets," Pacific-Basin Finance Journal, Elsevier, vol. 19(4), pages 351-373, September.
    6. Chuo Chang, 2020. "Dynamic correlations and distributions of stock returns on China's stock markets," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 10(1), pages 1-6.
    7. Guidi, Francesco & Gupta, Rakesh & Maheshwari, Suneel, 2010. "Weak-form market efficiency and calendar anomalies for Eastern Europe equity markets," MPRA Paper 21984, University Library of Munich, Germany.
    8. Guidi, Francesco & Gupta, Rakesh, 2011. "Are ASEAN stock markets efficients? Evidence from univariate and multivariate variance ratio tests," Greenwich Papers in Political Economy 7278, University of Greenwich, Greenwich Political Economy Research Centre.
    9. Zhian Chen & Hai Jiang & Donghui Li & Ah Boon Sim, 2010. "Regulation Change and Volatility Spillovers: Evidence from China's Stock Markets," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 46(6), pages 140-157, November.
    10. Huang, Ying Sophie & Wang, Yizhong, 2013. "Asset price, risk transfer and economic activities: Firm-level evidence from China," The North American Journal of Economics and Finance, Elsevier, vol. 26(C), pages 663-676.
    11. Tourani-Rad, Alireza & Gilbert, Aaron & Chen, Jun, 2016. "Are foreign IPOs really foreign? Price efficiency and information asymmetry of Chinese foreign IPOs," Journal of Banking & Finance, Elsevier, vol. 63(C), pages 95-106.
    12. Musarrat SHAMSHIR & Mirza Jawwad BAIG & Khalid MUSTAFA, 2018. "Evidence of random walk in Pakistan stock exchange: An emerging stock market study," Journal of Economics Library, KSP Journals, vol. 5(1), pages 103-117, March.
    13. Ruan, Qingsong & Yang, Haiquan & Lv, Dayong & Zhang, Shuhua, 2018. "Cross-correlations between individual investor sentiment and Chinese stock market return: New perspective based on MF-DCCA," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 503(C), pages 243-256.
    14. Senarathne Chamil W., 2020. "Are Religious Believers Irrational: A Direct Test from an Efficient Market Hypothesis," Financial Sciences. Nauki o Finansach, Sciendo, vol. 25(1), pages 35-53, March.
    15. Ioana-Andreea Boboc & Mihai-Cristian Dinică, 2013. "An Algorithm for Testing the Efficient Market Hypothesis," PLOS ONE, Public Library of Science, vol. 8(10), pages 1-11, October.
    16. de Bondt, Gabe & Peltonen, Tuomas A. & Santabárbara, Daniel, 2010. "Booms and busts in China's stock market: Estimates based on fundamentals," Working Paper Series 1190, European Central Bank.
    17. Sánchez-Granero, M.A. & Balladares, K.A. & Ramos-Requena, J.P. & Trinidad-Segovia, J.E., 2020. "Testing the efficient market hypothesis in Latin American stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 540(C).
    18. Abdul Razak Abdul Hadi & Eddy Tat Hiung Yap & Zalina Zainudin, 2019. "The Effects of Relative Strength of USD and Overnight Policy Rate on Performance of Malaysian Stock Market – Evidence from 1980 through 2015," Contemporary Economics, University of Economics and Human Sciences in Warsaw., vol. 13(2), June.
    19. Hiremath, Gourishankar S & Bandi, Kamaiah, 2009. "On the random walk characteristics of stock returns in India," MPRA Paper 46499, University Library of Munich, Germany.
    20. Zhou, Zhongbao & Gao, Meng & Xiao, Helu & Wang, Rui & Liu, Wenbin, 2021. "Big data and portfolio optimization: A novel approach integrating DEA with multiple data sources," Omega, Elsevier, vol. 104(C).
    21. Luis A. Gil-Alana & Yun Cao, 2011. "Stock market prices in China. Efficiency, mean reversion, long memory volatility and other implicit dynamics," Faculty Working Papers 12/11, School of Economics and Business Administration, University of Navarra.
    22. Pu, Yun & Zulauf, Carl, 2021. "Where are the fundamental traders? A model application based on the Shanghai Stock Exchange," Emerging Markets Review, Elsevier, vol. 49(C).
    23. Karen Balladares & José Pedro Ramos-Requena & Juan Evangelista Trinidad-Segovia & Miguel Angel Sánchez-Granero, 2021. "Statistical Arbitrage in Emerging Markets: A Global Test of Efficiency," Mathematics, MDPI, vol. 9(2), pages 1-20, January.
    24. Janet Jyothi Dsouza & T. Mallikarjunappa, 2015. "Does the Indian Stock Market Exhibit Random Walk?," Paradigm, , vol. 19(1), pages 1-20, June.
    25. Jyoti Gupta & Sardana Sankalp, 2017. "The Impact of Global Financial Crisis on Market Efficiency: An Empirical Analysis of the Indian Stock Market," International Journal of Economics and Finance, Canadian Center of Science and Education, vol. 9(4), pages 225-252, April.
    26. Vijay Kumar Vishwakarma & Ohannes George Paskelian, 2012. "Bubble In The Indian Real Estate Markets: Identification Using Regime-Switching Methodology," The International Journal of Business and Finance Research, The Institute for Business and Finance Research, vol. 6(3), pages 27-40.

  51. Amélie Charles & Olivier Darné, 2009. "Testing for random walk behavior in euro exchange rates," Post-Print hal-00771082, HAL.

    Cited by:

    1. Lazăr, Dorina & Todea, Alexandru & Filip, Diana, 2012. "Martingale difference hypothesis and financial crisis: Empirical evidence from European emerging foreign exchange markets," Economic Systems, Elsevier, vol. 36(3), pages 338-350.
    2. Amélie Charles & Olivier Darné & Jae H. Kim, 2010. "Exchange-Rate Return Predictability and the Adaptive Markets Hypothesis: Evidence from Major Foreign Exchange Rates," Working Papers hal-00547722, HAL.
    3. Kuck, Konstantin & Maderitsch, Robert, 2019. "Intra-day dynamics of exchange rates: New evidence from quantile regression," The Quarterly Review of Economics and Finance, Elsevier, vol. 71(C), pages 247-257.
    4. Fahad Almudhaf, 2014. "Testing for random walk behaviour in CIVETS exchange rates," Applied Economics Letters, Taylor & Francis Journals, vol. 21(1), pages 60-63, January.
    5. Petr Zeman & Martin Maršík, 2013. "High-frequency data and the effectiveness of the spot exchange rate EUR/USD," Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis, Mendel University Press, vol. 61(7), pages 2965-2971.
    6. Agus Salim & Kai Shi, 2019. "A Cointegration of the Exchange Rate and Macroeconomic Fundamentals: The Case of the Indonesian Rupiah vis-á-vis Currencies of Primary Trade Partners," JRFM, MDPI, vol. 12(2), pages 1-17, May.
    7. Adeyeye Patrick Olufemi & Aluko Olufemi Adewale & Migiro Stephen Oseko, 2017. "Efficiency of Foreign Exchange Markets in Sub-Saharan Africa in the Presence of Structural Break: A Linear and Non-Linear Testing Approach," Journal of Economics and Behavioral Studies, AMH International, vol. 9(4), pages 122-131.
    8. Ismael Orquín-Serrano, 2020. "Predictive Power of Adaptive Candlestick Patterns in Forex Market. Eurusd Case," Mathematics, MDPI, vol. 8(5), pages 1-34, May.
    9. Yang, Yan-Hong & Shao, Ying-Hui & Shao, Hao-Lin & Stanley, H. Eugene, 2019. "Revisiting the weak-form efficiency of the EUR/CHF exchange rate market: Evidence from episodes of different Swiss franc regimes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 523(C), pages 734-746.

  52. Amélie Charles & Olivier Darné, 2009. "The efficiency of the crude oil markets: Evidence from variance ratio tests," Post-Print hal-00771081, HAL.

    Cited by:

    1. Chen, Yingqi & Ba, Shusong & Yang, Qing & Yuan, Tian & Zhao, Haibo & Zhou, Ming & Bartocci, Pietro & Fantozzi, Francesco, 2021. "Efficiency of China’s carbon market: A case study of Hubei pilot market," Energy, Elsevier, vol. 222(C).
    2. Tiwari, Aviral Kumar & Umar, Zaghum & Alqahtani, Faisal, 2021. "Existence of long memory in crude oil and petroleum products: Generalised Hurst exponent approach," Research in International Business and Finance, Elsevier, vol. 57(C).
    3. Choi, Gahyun & Park, Kwangyeol & Yi, Eojin & Ahn, Kwangwon, 2023. "Price fairness: Clean energy stocks and the overall market," Chaos, Solitons & Fractals, Elsevier, vol. 168(C).
    4. Ortiz-Cruz, Alejandro & Rodriguez, Eduardo & Ibarra-Valdez, Carlos & Alvarez-Ramirez, Jose, 2012. "Efficiency of crude oil markets: Evidences from informational entropy analysis," Energy Policy, Elsevier, vol. 41(C), pages 365-373.
    5. Aurelio F. Bariviera & Luciano Zunino & M. Belen Guercio & Lisana B. Martinez & Osvaldo A. Rosso, 2015. "Efficiency and credit ratings: a permutation-information-theory analysis," Papers 1509.01839, arXiv.org.
    6. Auer, Benjamin R., 2014. "Daily seasonality in crude oil returns and volatilities," Energy Economics, Elsevier, vol. 43(C), pages 82-88.
    7. Go, You-How & Lau, Wee-Yeap, 2017. "Investor demand, market efficiency and spot-futures relation: Further evidence from crude palm oil," Resources Policy, Elsevier, vol. 53(C), pages 135-146.
    8. Jamal Bouoiyour & Refk Selmi & Shawkat Hammoudeh & Mark E Wohar, 2019. "What are the categories of geopolitical risks that could drive oil prices higher? Acts or threats?," Post-Print hal-02409062, HAL.
    9. Arouri, Mohamed El Hédi & Lahiani, Amine & Lévy, Aldo & Nguyen, Duc Khuong, 2012. "Forecasting the conditional volatility of oil spot and futures prices with structural breaks and long memory models," Energy Economics, Elsevier, vol. 34(1), pages 283-293.
    10. Okoroafor, Ugochi Chibuzor & Leirvik, Thomas, 2022. "Time varying market efficiency in the Brent and WTI crude market," Finance Research Letters, Elsevier, vol. 45(C).
    11. Alvarez-Ramirez, Jose & Alvarez, Jesus & Solis, Ricardo, 2010. "Crude oil market efficiency and modeling: Insights from the multiscaling autocorrelation pattern," Energy Economics, Elsevier, vol. 32(5), pages 993-1000, September.
    12. Górska, Anna & Krawiec, Monika, 2017. "Analiza efektywności informacyjnej w formie słabej na rynkach „soft commodities” z wykorzystaniem wybranych testów statystycznych," Problems of World Agriculture / Problemy Rolnictwa Światowego, Warsaw University of Life Sciences, vol. 17(32, Part ), September.
    13. Zhi-Qiang Jiang & Wen-Jie Xie & Wei-Xing Zhou, 2012. "Testing the weak-form efficiency of the WTI crude oil futures market," Papers 1211.4686, arXiv.org.
    14. George P. Papaioannou & Christos Dikaiakos & Akylas C. Stratigakos & Panos C. Papageorgiou & Konstantinos F. Krommydas, 2019. "Testing the Efficiency of Electricity Markets Using a New Composite Measure Based on Nonlinear TS Tools," Energies, MDPI, vol. 12(4), pages 1-30, February.
    15. Faisal, Faisal & Rahman, Sami Ur & Chander, Rajnesh & Ali, Adnan & Ramakrishnan, Suresh & Ozatac, Nesrin & Ullah, Mr Noor & Tursoy, Turgut, 2021. "Investigating the nexus between GDP, oil prices, FDI, and tourism for emerging economy: Empirical evidence from the novel fourier ARDL and hidden cointegration," Resources Policy, Elsevier, vol. 74(C).
    16. Luis A. Gil-Alana & Rangan Gupta & Olusanya E. Olubusoye & OlaOluwa S. Yaya, 2015. "Time Series Analysis of Persistence in Crude Oil Price Volatility across Bull and Bear Regimes," Working Papers 201580, University of Pretoria, Department of Economics.
    17. Martina, Esteban & Rodriguez, Eduardo & Escarela-Perez, Rafael & Alvarez-Ramirez, Jose, 2011. "Multiscale entropy analysis of crude oil price dynamics," Energy Economics, Elsevier, vol. 33(5), pages 936-947, September.
    18. Igor LEBRUN & Ludovic DOBBELAERE, 2010. "A Macro-econometric Model for the Economy of Lesotho," EcoMod2010 259600102, EcoMod.
    19. Montagnoli, Alberto & de Vries, Frans P., 2010. "Carbon trading thickness and market efficiency," Energy Economics, Elsevier, vol. 32(6), pages 1331-1336, November.
    20. Agya Atabani Adi & Samuel Paabu Adda & Amadi Kingsley Wobilor, 2022. "Shocks and volatility transmission between oil price and Nigeria’s exchange rate," SN Business & Economics, Springer, vol. 2(6), pages 1-17, June.
    21. Halil Åžen & Mehmet Fatih Demiral, 2016. "Hospital Location Selection with Grey System Theory," European Journal of Economics and Business Studies Articles, Revistia Research and Publishing, vol. 2, May - Aug.
    22. Clement Moyo & Izunna Anyikwa & Andrew Phiri, 2023. "The Impact of Covid-19 on Oil Market Returns: Has Market Efficiency Being Violated?," International Journal of Energy Economics and Policy, Econjournals, vol. 13(1), pages 118-127, January.
    23. Sensoy, Ahmet & Hacihasanoglu, Erk, 2014. "Time-varying long range dependence in energy futures markets," Energy Economics, Elsevier, vol. 46(C), pages 318-327.
    24. Zhang, Bing, 2013. "Are the crude oil markets becoming more efficient over time? New evidence from a generalized spectral test," Energy Economics, Elsevier, vol. 40(C), pages 875-881.
    25. Chkili, Walid & Aloui, Chaker & Nguyen, Duc Khuong, 2014. "Instabilities in the relationships and hedging strategies between crude oil and US stock markets: Do long memory and asymmetry matter?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 33(C), pages 354-366.
    26. Ibarra-Valdez, C. & Alvarez, J. & Alvarez-Ramirez, J., 2016. "Randomness confidence bands of fractal scaling exponents for financial price returns," Chaos, Solitons & Fractals, Elsevier, vol. 83(C), pages 119-124.
    27. Goodness C. Aye & Luis A. Gil-Alana & Rangan Gupta & Mark Wohar, 2016. "The Efficiency of the Art Market: Evidence from Variance Ratio Tests, Linear and Nonlinear Fractional Integration Approaches," Working Papers 201610, University of Pretoria, Department of Economics.
    28. Mensi, Walid & Hammoudeh, Shawkat & Yoon, Seong-Min, 2014. "How do OPEC news and structural breaks impact returns and volatility in crude oil markets? Further evidence from a long memory process," Energy Economics, Elsevier, vol. 42(C), pages 343-354.
    29. Mensi, Walid & Sensoy, Ahmet & Vo, Xuan Vinh & Kang, Sang Hoon, 2020. "Impact of COVID-19 outbreak on asymmetric multifractality of gold and oil prices," Resources Policy, Elsevier, vol. 69(C).
    30. James Ming Chen & Mobeen Ur Rehman, 2021. "A Pattern New in Every Moment: The Temporal Clustering of Markets for Crude Oil, Refined Fuels, and Other Commodities," Energies, MDPI, vol. 14(19), pages 1-58, September.
    31. de, Vries Frans & Montagnoli, Alberto, 2009. "Carbon trading thickness and market efficiency: A non-parametric test," Stirling Economics Discussion Papers 2009-22, University of Stirling, Division of Economics.
    32. Jia, Xiaoliang & An, Haizhong & Sun, Xiaoqi & Huang, Xuan & Wang, Lijun, 2017. "Evolution of world crude oil market integration and diversification: A wavelet-based complex network perspective," Applied Energy, Elsevier, vol. 185(P2), pages 1788-1798.
    33. Komijani, Akbar & Naderi, Esmaeil & Gandali Alikhani, Nadiya, 2013. "A Hybrid Approach for Forecasting of Oil Prices Volatility," MPRA Paper 44654, University Library of Munich, Germany.
    34. Qianjie Geng & Xianfeng Hao & Yudong Wang, 2024. "Forecasting the volatility of crude oil futures: A time‐dependent weighted least squares with regularization constraint," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(2), pages 309-325, March.
    35. Yudong Wang & Chongfeng Wu, 2013. "Efficiency of Crude Oil Futures Markets: New Evidence from Multifractal Detrending Moving Average Analysis," Computational Economics, Springer;Society for Computational Economics, vol. 42(4), pages 393-414, December.
    36. Dong, Yang & Wen, Shu-hui & Hu, Xiao-bing & Li, Jiang-Cheng, 2020. "Stochastic resonance of drawdown risk in energy market prices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 540(C).
    37. Mohanty, Sunil K. & Mishra, Sibanjan, 2020. "Regulatory reform and market efficiency: The case of Indian agricultural commodity futures markets," Research in International Business and Finance, Elsevier, vol. 52(C).
    38. Tokic, Damir, 2015. "The 2014 oil bust: Causes and consequences," Energy Policy, Elsevier, vol. 85(C), pages 162-169.
    39. Ghazani, Majid Mirzaee & Ebrahimi, Seyed Babak, 2019. "Testing the adaptive market hypothesis as an evolutionary perspective on market efficiency: Evidence from the crude oil prices," Finance Research Letters, Elsevier, vol. 30(C), pages 60-68.
    40. Kristoufek, Ladislav & Vosvrda, Miloslav, 2014. "Commodity futures and market efficiency," Energy Economics, Elsevier, vol. 42(C), pages 50-57.
    41. Chen, Shyh-Wei & Lin, Shih-Mo, 2014. "Non-linear dynamics in international resource markets: Evidence from regime switching approach," Research in International Business and Finance, Elsevier, vol. 30(C), pages 233-247.
    42. Kristoufek, Ladislav, 2019. "Are the crude oil markets really becoming more efficient over time? Some new evidence," Energy Economics, Elsevier, vol. 82(C), pages 253-263.
    43. Bhatia, Madhur, 2023. "On the efficiency of the gold returns: An econometric exploration for India, USA and Brazil," Resources Policy, Elsevier, vol. 82(C).
    44. Li, Jiang-Cheng & Leng, Na & Zhong, Guang-Yan & Wei, Yu & Peng, Jia-Sheng, 2020. "Safe marginal time of crude oil price via escape problem of econophysics," Chaos, Solitons & Fractals, Elsevier, vol. 133(C).
    45. Zhang, Bing & Li, Xiao-Ming & He, Fei, 2014. "Testing the evolution of crude oil market efficiency: Data have the conn," Energy Policy, Elsevier, vol. 68(C), pages 39-52.
    46. Okorie, David Iheke & Lin, Boqiang, 2021. "Adaptive market hypothesis: The story of the stock markets and COVID-19 pandemic," The North American Journal of Economics and Finance, Elsevier, vol. 57(C).
    47. Hachmi Ben Ameur & Zied Ftiti & Eric Le Fur, 2024. "What can we learn from the analysis of the fine wines market efficiency?," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 29(1), pages 703-718, January.
    48. Lang, Korbinian & Auer, Benjamin R., 2020. "The economic and financial properties of crude oil: A review," The North American Journal of Economics and Finance, Elsevier, vol. 52(C).
    49. Alper Kara & Dilem Yildirim & G. Ipek Tunc, 2023. "Market efficiency in non-renewable resource markets: evidence from stationarity tests with structural changes," Mineral Economics, Springer;Raw Materials Group (RMG);Luleå University of Technology, vol. 36(2), pages 279-290, June.
    50. Alper Kara & Dilem Yıldırım & Gül İpek Tunç, 2021. "Market Efficiency In Non-Renewable Resource Markets: Evidence From Stationarity Tests With Structural Changes," ERC Working Papers 2103, ERC - Economic Research Center, Middle East Technical University, revised Apr 2021.

  53. Amélie Charles & Olivier Darné & Jean-François Hoarau, 2009. "Does the real GDP per capita convergence hold in the Common Market for Eastern and Southern Africa?," Working Papers hal-00422522, HAL.

    Cited by:

    1. Gil-Alana, Luis A. & Yaya, OlaOluwa S & Shittu, Olanrewaju I, 2014. "GDP Per Capita in Africa before the Global Financial Crisis: Persistence, Mean Reversion and Long Memory Features," MPRA Paper 88758, University Library of Munich, Germany.
    2. Kisu Simwaka, 2016. "Macroeconomic Convergence in Southern Africa Development Community," Working Papers 325, African Economic Research Consortium, Research Department.
    3. Wolassa Lawisso Kumo, 2011. "Working Paper 130 - Growth and Macroeconomic Convergence in Southern Africa," Working Paper Series 314, African Development Bank.

  54. Olivier Darné & Amélie Charles, 2009. "Large shocks in U.S. macroeconomic time series: 1860–1988," Working Papers hal-00422502, HAL.

    Cited by:

    1. Charles, Amélie & Darné, Olivier, 2014. "Large shocks in the volatility of the Dow Jones Industrial Average index: 1928–2013," Journal of Banking & Finance, Elsevier, vol. 43(C), pages 188-199.
    2. Amélie Charles & Olivier Darné, 2012. "Trends and random walks in macroeconomic time series: A reappraisal," Post-Print hal-00956937, HAL.
    3. Claude DIEBOLT & Karine PELLIER, 2018. "Patents in the Long Run: Theory, History and Statistics," Working Papers of BETA 2018-20, Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg.
    4. Vides, José Carlos & Golpe, Antonio A. & Iglesias, Jesús, 2021. "The impact of the term spread in US monetary policy from 1870 to 2013," Journal of Policy Modeling, Elsevier, vol. 43(1), pages 230-251.

  55. Darné, O. & Ferrara, L., 2009. "Identification of slowdowns and accelerations for the euro area economy," Working papers 239, Banque de France.

    Cited by:

    1. Patrick Fève & Julien Matheron & Jean‐Guillaume Sahuc, 2009. "Minimum Distance Estimation and Testing of DSGE Models from Structural VARs," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 71(6), pages 883-894, December.
    2. Amélie Charles & Olivier Darné & Claude Diebolt & Laurent Ferrara, 2012. "A new monthly chronology of the US industrial cycles in the prewar economy," Working Papers 12-02, Association Française de Cliométrie (AFC).
    3. Aastveit, Knut Are & Jore, Anne Sofie & Ravazzolo, Francesco, 2016. "Identification and real-time forecasting of Norwegian business cycles," International Journal of Forecasting, Elsevier, vol. 32(2), pages 283-292.
    4. Monfort, A., 2009. "Optimal Portfolio Allocation under Asset and Surplus VaR Constraints," Working papers 251, Banque de France.
    5. Monica Billio & Roberto Casarin, 2010. "Bayesian Estimation of Stochastic-Transition Markov-Switching Models for Business Cycle Analysis," Working Papers 1002, University of Brescia, Department of Economics.
    6. Aastveit, Knut Are & Anundsen, André K. & Herstad, Eyo I., 2019. "Residential investment and recession predictability," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1790-1799.
    7. Karim Barhoumi & Laurent Ferrara, 2015. "A World Trade Leading Index (WTLI)," IMF Working Papers 2015/020, International Monetary Fund.
    8. Catherine Doz & Anna Petronevich, 2015. "Dating Business Cycle Turning Points for the French Economy: a MS-DFM approach," Documents de travail du Centre d'Economie de la Sorbonne 15009, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    9. Barhoumi, K. & Darné, O. & Ferrara, L., 2013. "Dynamic Factor Models: A review of the Literature ," Working papers 430, Banque de France.
    10. Amélie Charles & Olivier Darné, 2015. "Identifying and characterizing business and acceleration cycles of French jobseekers Identifying and characterizing business and acceleration cycles of French jobseekers," Working Papers hal-01160090, HAL.
    11. Ferrara, L. & Vigna, O., 2009. "Cyclical relationships between GDP and housing market in France: Facts and factors at play," Working papers 268, Banque de France.
    12. Ataman Ozyildirim & Brian Schaitkin & Victor Zarnowitz, 2008. "Business Cycles in the Euro Area Defined with Coincident Economic Indicators and Predicted with Leading Economic Indicators," Economics Program Working Papers 08-04, The Conference Board, Economics Program.
    13. Christian R. Proaño & Artur Tarassow, 2017. "Evaluating the predicting power of ordered probit models for multiple business cycle phases in the U.S. and Japan," IMK Working Paper 188-2017, IMK at the Hans Boeckler Foundation, Macroeconomic Policy Institute.
    14. Shiu-Sheng, Chen, 2012. "Predicting swings in exchange rates with macro fundamentals," MPRA Paper 35772, University Library of Munich, Germany.
    15. Proaño, Christian R. & Theobald, Thomas, 2014. "Predicting recessions with a composite real-time dynamic probit model," International Journal of Forecasting, Elsevier, vol. 30(4), pages 898-917.

  56. Olivier DARNÉ & Jean-François HOARAU, 2008. "La parité des pouvoirs d’achat pour l’économie chinoise : Une nouvelle analyse par les tests de racine unitaire," Discussion Papers (REL - Recherches Economiques de Louvain) 2008025, Université catholique de Louvain, Institut de Recherches Economiques et Sociales (IRES).

    Cited by:

    1. Jean-François Hoarau, 2013. "Un modèle NATREX synthétique pour une petite économie «développée» ouverte contrainte sur les marchés internationaux de capitaux," Post-Print hal-01243429, HAL.
    2. Jean-François Hoarau, 2021. "État des lieux, menaces et perspectives futures pour le tourisme à La Réunion : un regard macroéconomique," Post-Print hal-03546567, HAL.

  57. Olivier Darné & Jean-François Hoarau, 2008. "The purchasing power parity in Australia: evidence from unit root test with structural break," Post-Print hal-01243482, HAL.

    Cited by:

    1. Cuestas, Juan C. & Gil-Alana, Luís A., 2009. "Further evidence on the PPP analysis of the Australian dollar: Non-linearities, fractional integration and structural changes," Economic Modelling, Elsevier, vol. 26(6), pages 1184-1192, November.
    2. Juan Carlos Cuestas & Paulo José Regis, 2008. "Testing for PPP in Australia: Evidence from unit root test against nonlinear trend stationarity alternatives," Economics Bulletin, AccessEcon, vol. 3(27), pages 1-8.
    3. Mubariz Hasanov, 2014. "Testing for a unit root in the presence of a nonlinear trend: The case of Australian Reel Exchange Rate," Econometrics Letters, Bilimsel Mektuplar Organizasyonu (Scientific letters), vol. 1(1), pages 10-17.
    4. Ahmad Zubaidi Baharumshah & Siew-Voon Soon, 2012. "Mean reversion in bilateral real exchange rates: evidence from the Malaysian ringgit," Applied Economics, Taylor & Francis Journals, vol. 44(22), pages 2921-2933, August.
    5. Yutaka Kurihara, 2009. "Is Purchasing Power Parity Hypothesis Reasonable from the View of Trade Blocks and Currency Zones?," European Research Studies Journal, European Research Studies Journal, vol. 0(3), pages 3-14.
    6. Xie, Zixiong & Chen, Shyh-Wei & Hsieh, Chun-Kuei, 2021. "Facing up to the polysemy of purchasing power parity: New international evidence," Economic Modelling, Elsevier, vol. 98(C), pages 247-265.

  58. Olivier Darné & Amélie Charles, 2008. "The impact of outliers on transitory and permanent components in macroeconomic time series," Post-Print hal-00765362, HAL.

    Cited by:

    1. Rainer Metz, 2011. "Do Kondratieff waves exist? How time series techniques can help to solve the problem," Cliometrica, Journal of Historical Economics and Econometric History, Association Française de Cliométrie (AFC), vol. 5(3), pages 205-238, October.

  59. Barhoumi, K. & Brunhes-Lesage, V. & Darné, O. & Ferrara, L. & Pluyaud, B. & Rouvreau, B., 2008. "Monthly forecasting of French GDP: A revised version of the OPTIM model," Working papers 222, Banque de France.

    Cited by:

    1. Robert Lehmann, 2016. "Economic Growth and Business Cycle Forecasting at the Regional Level," ifo Beiträge zur Wirtschaftsforschung, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 65.
    2. Marie Bessec, 2013. "Short‐Term Forecasts of French GDP: A Dynamic Factor Model with Targeted Predictors," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 32(6), pages 500-511, September.
    3. Guido Bulligan & Massimiliano Marcellino & Fabrizio Venditti, 2012. "Forecasting economic activity with higher frequency targeted predictors," Temi di discussione (Economic working papers) 847, Bank of Italy, Economic Research and International Relations Area.
    4. Katja Heinisch & Rolf Scheufele, 2018. "Bottom-up or direct? Forecasting German GDP in a data-rich environment," Empirical Economics, Springer, vol. 54(2), pages 705-745, March.
    5. Esteves, Paulo Soares, 2013. "Direct vs bottom–up approach when forecasting GDP: Reconciling literature results with institutional practice," Economic Modelling, Elsevier, vol. 33(C), pages 416-420.
    6. Marie Bessec, 2010. "Étalonnages du taux de croissance du PIB français sur la base des enquêtes de conjoncture," Économie et Prévision, Programme National Persée, vol. 193(2), pages 77-99.
    7. Patrick C. Higgins, 2014. "GDPNow: A Model for GDP \"Nowcasting\"," FRB Atlanta Working Paper 2014-7, Federal Reserve Bank of Atlanta.
    8. Robert Lehmann & Klaus Wohlrabe, 2013. "Forecasting gross value-added at the regional level: Are sectoral disaggregated predictions superior to direct ones?," ifo Working Paper Series 171, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    9. Marie Adanero-Donderis & Olivier Darné & Laurent Ferrara, 2009. "Un indicateur probabiliste du cycle d’accélération pour l’économie française," Économie et Prévision, Programme National Persée, vol. 189(3), pages 95-114.
    10. Ferrara, L., 2008. "The contribution of cyclical turning point indicators to business cycle analysis," Quarterly selection of articles - Bulletin de la Banque de France, Banque de France, issue 13, pages 49-61, Autumn.
    11. Tomasz Jasiński & Paweł Mielcarz, 2013. "Consumption as a Factor of Polish Economic Growth During the Global Recession of 2008/2009: A Comparison with Spain and Hungary," Contemporary Economics, University of Economics and Human Sciences in Warsaw., vol. 7(2), June.
    12. Barhoumi, K. & Brunhes-Lesage, V. & Ferrara, L. & Pluyaud, B. & Rouvreau, B. & Darné, O., 2008. "OPTIM: a quarterly forecasting tool for French GDP," Quarterly selection of articles - Bulletin de la Banque de France, Banque de France, issue 13, pages 31-47, Autumn.
    13. Bulligan, Guido & Marcellino, Massimiliano & Venditti, Fabrizio, 2015. "Forecasting economic activity with targeted predictors," International Journal of Forecasting, Elsevier, vol. 31(1), pages 188-206.

  60. Adanero-Donderis , M. & Darné, O. & Ferrara, L., 2007. "Deux indicateurs probabilistes de retournement cyclique pour l’économie française," Working papers 187, Banque de France.

    Cited by:

    1. Ferrara, L., 2008. "The contribution of cyclical turning point indicators to business cycle analysis," Quarterly selection of articles - Bulletin de la Banque de France, Banque de France, issue 13, pages 49-61, Autumn.

  61. Darné, O. & Brunhes-Lesage, V., 2007. "L’Indicateur Synthétique Mensuel d’Activité (ISMA) : une révision," Working papers 171, Banque de France.

    Cited by:

    1. Mogliani, Matteo & Darné, Olivier & Pluyaud, Bertrand, 2017. "The new MIBA model: Real-time nowcasting of French GDP using the Banque de France's monthly business survey," Economic Modelling, Elsevier, vol. 64(C), pages 26-39.

  62. Olivier Darné & Claude Diebolt, 2006. "Cliometrics of Academic Careers and the Impact of Infrequent Large Shocks in Germany before 1945," Working Papers 06-01, Association Française de Cliométrie (AFC).

    Cited by:

    1. Claude Diebolt, 2008. "Croissance et éducation," Post-Print hal-00279592, HAL.
    2. Rainer Metz, 2011. "Do Kondratieff waves exist? How time series techniques can help to solve the problem," Cliometrica, Journal of Historical Economics and Econometric History, Association Française de Cliométrie (AFC), vol. 5(3), pages 205-238, October.

  63. Claude Diebolt & Olivier Darné, 2005. "Chocs temporaires et permanents dans le PIB de la France, du Royaume-Uni et des Etats-Unis," Working Papers 05-06, Association Française de Cliométrie (AFC).

    Cited by:

    1. Claude Diebolt & Magali Jaoul-Grammare, 2014. "Econometric history of wages in France [Économétrie historique des salaires en France]," Post-Print halshs-03394949, HAL.
    2. Claude Diebolt & Magali Jaoul-Grammare, 2014. "The payroll of the Germany: 1810-1989 [La masse salariale de l'Allemagne: 1810-1989]," Post-Print hal-01744546, HAL.
    3. Claude Diebolt & Cédric Doliger, 2008. "New international evidence on the cyclical behaviour of output : Kuznets swings reconsidered," Post-Print hal-00278967, HAL.
    4. Claude Diebolt & Olivier Darné, 2005. "Cliometrics of Academic Careers and the Impact of Infrequent Large Shocks in Germany before 1945," Post-Print hal-00279246, HAL.
    5. Jean-Daniel Boyer & Magali Jaoul-Grammare & Sylvie Rivot, 2017. "Prix du blé, régulations et croissance économique : L’analyse cliométrique permet-elle de trancher le débat sur les bleds des années 1750 ?," Working Papers 11-17, Association Française de Cliométrie (AFC).
    6. Claude Diebolt & Magali Jaoul-Grammare & Faustine Perrin, 2022. "A Cliometric Reading of the Development of Primary Education in France in the Nineteenth Century," Working Papers 02-22, Association Française de Cliométrie (AFC).
    7. Claude Diebolt & Magali Jaoul-Grammare, 2008. "Econométrie historique des salaires en France : une relecture des années charnières," Working Papers 08-08, Association Française de Cliométrie (AFC).
    8. Claude Diebolt & Magali Jaoul-Grammare, 2007. "La masse salariale de l’Allemagne : 1810-1989. Nouvelle mesure et analyse cliométrique des chocs," Working Papers 07-02, Association Française de Cliométrie (AFC).
    9. Magali Jaoul-Grammare, 2013. "L’évolution des inégalités dans l’enseignement supérieur universitaire français au XXème siècle," Post-Print hal-01753405, HAL.
    10. Claude Diebolt & Antoine Parent, 2006. "Were there Anomalies in the Sterling-Franc Exchange Rate Regulation during the Mid-19th Century?," Working Papers 06-08, Association Française de Cliométrie (AFC).
    11. Claude Diebolt & Magali Jaoul-Grammare & Faustine Perrin, 2020. "Scolarisation de masse des garçons et des filles. Financement public de l’instruction primaire et croissance économique en France au XIXème siècle," Working Papers of BETA 2020-51, Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg.
    12. Claude Diebolt, 2020. "L’idée de régulation dans les sciences : hommage à l’épistémologue Jean Piaget," Working Papers 01-20, Association Française de Cliométrie (AFC).
    13. Jean Luc de Meulemeester & Claude Diebolt & Magali Jaoul-Grammare, 2007. "Aggregate Wage Earnings in Germany: 1810-1989. New Measurement and Cliometric Analysis of Shocks," Working Papers 07-11, Association Française de Cliométrie (AFC).
    14. Diebolt, Claude & Parent, Antoine, 2008. "Bimetallism: The "rules of the game"," Explorations in Economic History, Elsevier, vol. 45(3), pages 288-302, July.
    15. Magali Jaoul-Grammare, 2011. "L’évolution des inégalités dans l’enseignement supérieur universitaire français. L’influence des réformes institutionnelles et des ruptures économiques," Working Papers 11-06, Association Française de Cliométrie (AFC).

  64. Olivier Darné & Claude Diebolt, 2005. "Non-stationarity Tests in Macroeconomic Time Series," Post-Print hal-00279447, HAL.

    Cited by:

    1. Claude Diebolt & Magali Jaoul-Grammare, 2014. "The payroll of the Germany: 1810-1989 [La masse salariale de l'Allemagne: 1810-1989]," Post-Print hal-01744546, HAL.
    2. Claude Diebolt & Olivier Darné, 2005. "Cliometrics of Academic Careers and the Impact of Infrequent Large Shocks in Germany before 1945," Post-Print hal-00279246, HAL.
    3. Claude Diebolt & Magali Jaoul-Grammare, 2007. "La masse salariale de l’Allemagne : 1810-1989. Nouvelle mesure et analyse cliométrique des chocs," Working Papers 07-02, Association Française de Cliométrie (AFC).
    4. Jean Luc de Meulemeester & Claude Diebolt & Magali Jaoul-Grammare, 2007. "Aggregate Wage Earnings in Germany: 1810-1989. New Measurement and Cliometric Analysis of Shocks," Working Papers 07-11, Association Française de Cliométrie (AFC).
    5. Diebolt, Claude & Parent, Antoine, 2008. "Bimetallism: The "rules of the game"," Explorations in Economic History, Elsevier, vol. 45(3), pages 288-302, July.

  65. Olivier Darné & Claude Diebolt, 2004. "Unit Roots and Infrequent Large Shocks : New International Evidence on Output," Post-Print hal-00279015, HAL.

    Cited by:

    1. José Luis Cendejas & Félix-Fernando Muñoz & Nadia Fernández-de-Pinedo, 2017. "A contribution to the analysis of historical economic fluctuations (1870–2010): filtering, spurious cycles, and unobserved component modeling," Cliometrica, Springer;Cliometric Society (Association Francaise de Cliométrie), vol. 11(1), pages 93-125, January.
    2. WenShwo Fang & Stephen M. Miller, 2012. "Output Growth and Its Volatility: The Gold Standard through the Great Moderation," Working papers 2012-11, University of Connecticut, Department of Economics.
    3. Amélie Charles & Olivier Darné & Laurent Ferrara, 2014. "Does the Great Recession imply the end of the Great Moderation? International evidence," Working Papers hal-04141344, HAL.
    4. Antonio Focacci, 2023. "A Wavelet Investigation of Periodic Long Swings in the Economy: The Original Data of Kondratieff and Some Important Series of GDP per Capita," Economies, MDPI, vol. 11(9), pages 1-21, September.
    5. Claude Diebolt & Magali Jaoul-Grammare, 2014. "Econometric history of wages in France [Économétrie historique des salaires en France]," Post-Print halshs-03394949, HAL.
    6. Haiyan Song & Egon Smeral & Gang Li & Jason L. Chen, 2008. "Tourism Forecasting: Accuracy of Alternative Econometric Models Revisited," WIFO Working Papers 326, WIFO.
    7. Claude Diebolt & Michael Haupert, 2017. "A Cliometric Counterfactual: What if There Had Been Neither Fogel nor North?," Working Papers 05-17, Association Française de Cliométrie (AFC).
    8. Claude Diebolt & Magali Jaoul-Grammare, 2014. "The payroll of the Germany: 1810-1989 [La masse salariale de l'Allemagne: 1810-1989]," Post-Print hal-01744546, HAL.
    9. Claude Diebolt & Cédric Doliger, 2008. "New international evidence on the cyclical behaviour of output : Kuznets swings reconsidered," Post-Print hal-00278967, HAL.
    10. Amélie Charles & Olivier Darné, 2012. "Trends and random walks in macroeconomic time series: A reappraisal," Post-Print hal-00956937, HAL.
    11. Diebolt, Claude, 2009. "Editorial introduction: Advances in historical macroeconomics," Journal of Macroeconomics, Elsevier, vol. 31(1), pages 1-4, March.
    12. Claude Diebolt & Olivier Darné, 2005. "Cliometrics of Academic Careers and the Impact of Infrequent Large Shocks in Germany before 1945," Post-Print hal-00279246, HAL.
    13. Claude Diebolt & Magali Jaoul-Grammare, 2018. "Mesure du temps et temps de la mesure. Cliométrie des prix de gros en Allemagne avant la Première Guerre mondiale," Working Papers 08-18, Association Française de Cliométrie (AFC).
    14. Magali Jaoul-Grammare, 2022. "Quoi de neuf dans l’accès aux classes préparatoires ? Une perspective historique centrée sur l’ouverture sociale et l’accès des filles aux formations élitistes françaises," Working Papers 01-22, Association Française de Cliométrie (AFC).
    15. Tapas Mishra & Claude Diebolt, 2010. "Demographic volatility and economic growth: convention and beyond," Quality & Quantity: International Journal of Methodology, Springer, vol. 44(1), pages 25-45, January.
    16. Jean-Daniel Boyer & Magali Jaoul-Grammare & Sylvie Rivot, 2017. "Prix du blé, régulations et croissance économique : L’analyse cliométrique permet-elle de trancher le débat sur les bleds des années 1750 ?," Working Papers 11-17, Association Française de Cliométrie (AFC).
    17. Olivier Darné & Jean-François Hoarau, 2006. "Testing the purchasing power parity in China," EconomiX Working Papers 2006-18, University of Paris Nanterre, EconomiX.
    18. Charles, Amelie & Darne, Olivier, 2006. "Large shocks and the September 11th terrorist attacks on international stock markets," Economic Modelling, Elsevier, vol. 23(4), pages 683-698, July.
    19. Olivier Darné & Claude Diebolt, 2006. "Chocs temporaires et permanents dans le PIB de la France, du Royaume-Uni et des États-Unis," Revue d'économie politique, Dalloz, vol. 116(1), pages 65-78.
    20. Claude Diebolt, 2015. "Comment appréhender les temporalités de l’histoire économique ? Plaidoyer pour une cliométrie des événements rares," Working Papers of BETA 2015-12, Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg.
    21. Amélie Charles & Olivier Darné, 0. "Econometric history of the growth–volatility relationship in the USA: 1919–2017," Cliometrica, Springer;Cliometric Society (Association Francaise de Cliométrie), vol. 0, pages 1-24.
    22. Kufenko, Vadim & Prettner, Klaus & Geloso, Vincent, 2017. "Divergence, convergence, and the history-augmented Solow model," Hohenheim Discussion Papers in Business, Economics and Social Sciences 11-2017, University of Hohenheim, Faculty of Business, Economics and Social Sciences.
    23. Claude DIEBOLT & Karine PELLIER, 2018. "Patents in the Long Run: Theory, History and Statistics," Working Papers of BETA 2018-20, Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg.
    24. Geoffrey J. Warren, 2008. "Implications for Asset Pricing Puzzles of a Roll‐over Assumption for the Risk‐Free Asset," International Review of Finance, International Review of Finance Ltd., vol. 8(3‐4), pages 125-157, September.
    25. Thai-Ha Le & Donghyun Park & Cong-Phu-Khanh Tran & Binh Tran-Nam, 2018. "The Impact of the Hai Yang Shi You 981 Event on Vietnam’s Stock Markets," Journal of Emerging Market Finance, Institute for Financial Management and Research, vol. 17(3_suppl), pages 344-375, December.
    26. Darne, O. & Levy-Rueff, O. & Pop, A., 2013. "Calibrating Initial Shocks in Bank Stress Test Scenarios: An Outlier Detection Based Approach," Working papers 426, Banque de France.
    27. Olivier Darné & Jean‐François Hoarau, 2007. "Further Evidence On Mean Reversion In The Australian Exchange Rate," Bulletin of Economic Research, Wiley Blackwell, vol. 59(4), pages 383-395, October.
    28. Claude Diebolt & Cédric Doliger, 2005. "Becker vs. Easterlin. Education, Fertility and Growth in France after World War II," Working Papers 05-03, Association Française de Cliométrie (AFC).
    29. Claude Diebolt & Magali Jaoul-Grammare, 2008. "Econométrie historique des salaires en France : une relecture des années charnières," Working Papers 08-08, Association Française de Cliométrie (AFC).
    30. Claude Diebolt & Karine Pellier, 2010. "La dynamique structurelle et spatiale des systèmes de brevets. Une comparaison France, Allemagne, Royaume-Uni, Etats-Unis et Japon : 1617-2006," Working Papers 10-05, Association Française de Cliométrie (AFC).
    31. Rainer Metz, 2011. "Do Kondratieff waves exist? How time series techniques can help to solve the problem," Cliometrica, Journal of Historical Economics and Econometric History, Association Française de Cliométrie (AFC), vol. 5(3), pages 205-238, October.
    32. Claude Diebolt & Magali Jaoul-Grammare, 2007. "La masse salariale de l’Allemagne : 1810-1989. Nouvelle mesure et analyse cliométrique des chocs," Working Papers 07-02, Association Française de Cliométrie (AFC).
    33. Magali Jaoul-Grammare, 2013. "L’évolution des inégalités dans l’enseignement supérieur universitaire français au XXème siècle," Post-Print hal-01753405, HAL.
    34. Claude Diebolt, 2005. "Long Cycles Revisited. An Essay in Econometric History," Working Papers 05-05, Association Française de Cliométrie (AFC).
    35. Amélie Charles & Olivier Darné & Jean-François Hoarau, 2019. "How resilient is La Réunion in terms of international tourism attractiveness: an assessment from unit root tests with structural breaks from 1981-2015," Applied Economics, Taylor & Francis Journals, vol. 51(24), pages 2639-2653, May.
    36. Claude Diebolt & Karine Pellier, 2008. "Analyse spectrale de l’évolution de longue période des brevets en France, en Allemagne, en Grande-Bretagne, aux Etats-Unis et au Japon (17ème-20ème siècles)," Working Papers 08-09, Association Française de Cliométrie (AFC).
    37. Jinzhao Chen, 2009. "Beyond Cheap Talks: Assessing the Undervaluation of the Chinese Currency Between 1994 and 2007," Economie Internationale, CEPII research center, issue 119, pages 47-82.
    38. Théophile Azomahou & Claude Diebolt & Tapas Mishra, 2007. "Spatial Persistence of Demographic Shocks and Economic Growth," Working Papers 07-04, Association Française de Cliométrie (AFC).
    39. Darné, Olivier, 2009. "The uncertain unit root in real GNP: A re-examination," Journal of Macroeconomics, Elsevier, vol. 31(1), pages 153-166, March.
    40. Magali Jaoul-Grammare, 2022. "Quoi de neuf dans l’accès aux classes préparatoires ? Une perspective historique centrée sur l’ouverture sociale et l’accès des filles aux formations élitistes françaises," Working Papers of BETA 2022-01, Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg.
    41. Claude Diebolt & Antoine Parent, 2006. "Were there Anomalies in the Sterling-Franc Exchange Rate Regulation during the Mid-19th Century?," Working Papers 06-08, Association Française de Cliométrie (AFC).
    42. Claude Diebolt & Magali Jaoul-Grammare & Faustine Perrin, 2020. "Scolarisation de masse des garçons et des filles. Financement public de l’instruction primaire et croissance économique en France au XIXème siècle," Working Papers of BETA 2020-51, Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg.
    43. Sven Langedijk & Martin Larch, 2011. "Testing EU fiscal surveillance: how sensitive is it to variations in output gap estimates?," International Review of Applied Economics, Taylor & Francis Journals, vol. 25(1), pages 39-60.
    44. Claude Diebolt, 2020. "L’idée de régulation dans les sciences : hommage à l’épistémologue Jean Piaget," Working Papers 01-20, Association Française de Cliométrie (AFC).
    45. Peres-Cajías, José & Torregrosa-Hetland, Sara & Ducoing, Cristián, 2020. "Resource abundance and public finances in five peripheral economies, 1850-1939," Lund Papers in Economic History 216, Lund University, Department of Economic History.
    46. Joseph P. Byrne & Roger Perman, 2006. "Unit Roots and Structural Breaks: A Survey of the Literature," Working Papers 2006_10, Business School - Economics, University of Glasgow.
    47. Claude Diebolt & Antoine Parent, 2005. "86," Post-Print hal-00279247, HAL.
    48. Guillaume Morel & Magali Jaoul-Grammare, 2023. "Do Pandemics Impact Macroeconomic Variables? A Cliometric Approach," Working Papers 01-23, Association Française de Cliométrie (AFC).
    49. Mohitosh Kejriwal & Claude Lopez, 2013. "Unit Roots, Level Shifts, and Trend Breaks in Per Capita Output: A Robust Evaluation," Econometric Reviews, Taylor & Francis Journals, vol. 32(8), pages 892-927, November.
    50. Claude Diebolt & Tapas K. Mishra, 2006. "Cliometrics of the Abiding Nexus Between Demographic Components and Economic Development," Working Papers 06-06, Association Française de Cliométrie (AFC).
    51. Halkos, George & Managi, Shunsuke & Zisiadou, Argyro, 2017. "Analyzing the determinants of terrorist attacks and their market reactions," Economic Analysis and Policy, Elsevier, vol. 54(C), pages 57-73.
    52. Olivier Darné & Amélie Charles, 2011. "Large shocks in U.S. macroeconomic time series: 1860-1988," Cliometrica, Journal of Historical Economics and Econometric History, Association Française de Cliométrie (AFC), vol. 5(1), pages 79-100, January.
    53. Jennifer Castle & David Hendry, 2008. "The Long-Run Determinants of UK Wages, 1860-2004," Economics Series Working Papers 409, University of Oxford, Department of Economics.
    54. Claude Diebolt & Cédric Doliger, 2005. "Kuznets versus Kitchin, Juglar & Kondratieff. Renewed Spectral Analysis of Comparative Growth of Per Capita GDP series in the OECD Countries in the Nineteenth and Twentieth Centuries," Working Papers 05-02, Association Française de Cliométrie (AFC).
    55. Leitão, Alexandra, 2010. "Corruption and the environmental Kuznets Curve: Empirical evidence for sulfur," Ecological Economics, Elsevier, vol. 69(11), pages 2191-2201, September.
    56. Claude Diebolt, 2021. "Trend, Cycles and Chance," Working Papers of BETA 2021-14, Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg.
    57. Peres-Cajías, José & Torregrosa-Hetland, Sara & Ducoing, Cristián, 2022. "Resource abundance and public finances in five peripheral economies, 1850s–1930s," Resources Policy, Elsevier, vol. 76(C).
    58. Jean Luc de Meulemeester & Claude Diebolt & Magali Jaoul-Grammare, 2007. "Aggregate Wage Earnings in Germany: 1810-1989. New Measurement and Cliometric Analysis of Shocks," Working Papers 07-11, Association Française de Cliométrie (AFC).
    59. Diebolt, Claude & Parent, Antoine, 2008. "Bimetallism: The "rules of the game"," Explorations in Economic History, Elsevier, vol. 45(3), pages 288-302, July.
    60. Halkos, George & Zisiadou, Argyro, 2016. "Exploring the effect of terrorist attacks on markets," MPRA Paper 71877, University Library of Munich, Germany.
    61. Jean-François Goux, 2010. "Une approche déterministe du taux de change euro-dollar," Économie et Prévision, Programme National Persée, vol. 195(4), pages 35-51.
    62. Marco Gallegati & Mauro Gallegati & James B. Ramsey & Willi Semmler, 2017. "Long waves in prices: new evidence from wavelet analysis," Cliometrica, Springer;Cliometric Society (Association Francaise de Cliométrie), vol. 11(1), pages 127-151, January.
    63. Guillaume Morel & Magali Jaoul-Grammare, 2023. "Do Pandemics Impact Macroeconomic Variables? A Cliometric Approach," Working Papers of BETA 2023-01, Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg.
    64. Egon Smeral & Michael Wüger, 2006. "Methods for Measuring the Effects of the EU Presidency on International Tourism," WIFO Working Papers 282, WIFO.
    65. Claude Diebolt & Karine Pellier, 2022. "Patents in the Long Run : Theory, History and Statistics," Working Papers hal-02929514, HAL.
    66. Schüler, Yves S., 2018. "Detrending and financial cycle facts across G7 countries: mind a spurious medium term!," Working Paper Series 2138, European Central Bank.
    67. Magali Jaoul-Grammare, 2011. "L’évolution des inégalités dans l’enseignement supérieur universitaire français. L’influence des réformes institutionnelles et des ruptures économiques," Working Papers 11-06, Association Française de Cliométrie (AFC).
    68. Claude Diebolt & Catherine Kyrtsou, 2006. "Non-Linear Perspectives for Population and Output Dynamics: New Evidence for Cliometrics," Working Papers 06-02, Association Française de Cliométrie (AFC).

  66. Olivier Darne & Laetitia Ripoll-Bresson, 2004. "Exchange rate regime classification and real performances: new empirical evidence," Money Macro and Finance (MMF) Research Group Conference 2003 21, Money Macro and Finance Research Group.

    Cited by:

    1. Muhammad Naveed TAHIR & Faran ALI & Dawood MAMOON, 2016. "Appropriate Exchange Rate Regime for Economic Structure of Pakistan," Turkish Economic Review, KSP Journals, vol. 3(4), pages 629-641, December.

Articles

  1. Amélie Charles & Olivier Darné, 2022. "Backcasting world trade growth using data reduction methods," The World Economy, Wiley Blackwell, vol. 45(10), pages 3169-3191, October.

    Cited by:

    1. Chinn Menzie & Meunier Baptiste & Stumpner Sebastian, 2023. "Nowcasting world trade in real time with machine learning [Estimation du commerce mondial en temps réel grâce à l’apprentissage automatique]," Bulletin de la Banque de France, Banque de France, issue 248.

  2. Amélie Charles & Chew Lian Chua & Olivier Darné & Sandy Suardi, 2020. "On the pernicious effects of oil price uncertainty on US real economic activities," Empirical Economics, Springer, vol. 59(6), pages 2689-2715, December.
    See citations under working paper version above.
  3. Amélie Charles & Olivier Darné, 2019. "Volatility estimation for cryptocurrencies: Further evidence with jumps and structural breaks," Economics Bulletin, AccessEcon, vol. 39(2), pages 954-968.
    See citations under working paper version above.
  4. Charles, Amélie & Darné, Olivier, 2019. "Volatility estimation for Bitcoin: Replication and robustness," International Economics, Elsevier, vol. 157(C), pages 23-32.
    See citations under working paper version above.
  5. Amélie Charles & Olivier Darné & Jean-François Hoarau, 2019. "How resilient is La Réunion in terms of international tourism attractiveness: an assessment from unit root tests with structural breaks from 1981-2015," Applied Economics, Taylor & Francis Journals, vol. 51(24), pages 2639-2653, May.
    See citations under working paper version above.
  6. Zerbo, Eléazar & Darné, Olivier, 2019. "On the stationarity of CO2 emissions in OECD and BRICS countries: A sequential testing approach," Energy Economics, Elsevier, vol. 83(C), pages 319-332.

    Cited by:

    1. Sakiru Adebola Solarin, 2020. "Towards sustainable development: A multi‐country persistence analysis of forest products footprint using a stationarity test with smooth shifts," Sustainable Development, John Wiley & Sons, Ltd., vol. 28(5), pages 1465-1476, September.
    2. Awaworyi-Churchill, Sefa & Inekwe, John & Ivanovski, Kris & Smyth, Russell, 2022. "Breaks, trends and correlations in commodity prices in the very long-run," Energy Economics, Elsevier, vol. 108(C).
    3. Diego Romero-Ávila & Tolga Omay, 2023. "Convergence of GHGs emissions in the long-run: aerosol precursors, reactive gases and aerosols—a nonlinear panel approach," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 25(11), pages 12303-12337, November.
    4. Romero-Ávila, Diego & Omay, Tolga, 2022. "Convergence of per capita energy consumption around the world: New evidence from nonlinear panel unit root tests," Energy Economics, Elsevier, vol. 111(C).
    5. Awaworyi Churchill, Sefa & Inekwe, John & Ivanovski, Kris & Smyth, Russell, 2020. "Stationarity properties of per capita CO2 emissions in the OECD in the very long-run: A replication and extension analysis," Energy Economics, Elsevier, vol. 90(C).
    6. Ivanovski, Kris & Awaworyi Churchill, Sefa, 2020. "Convergence and determinants of greenhouse gas emissions in Australia: A regional analysis," Energy Economics, Elsevier, vol. 92(C).

  7. Charles, Amélie & Darné, Olivier, 2019. "The accuracy of asymmetric GARCH model estimation," International Economics, Elsevier, vol. 157(C), pages 179-202.

    Cited by:

    1. Neenu Chalissery & Suhaib Anagreh & Mohamed Nishad T. & Mosab I. Tabash, 2022. "Mapping the Trend, Application and Forecasting Performance of Asymmetric GARCH Models: A Review Based on Bibliometric Analysis," JRFM, MDPI, vol. 15(9), pages 1-23, September.
    2. Abuzayed, Bana & Bouri, Elie & Al-Fayoumi, Nedal & Jalkh, Naji, 2021. "Systemic risk spillover across global and country stock markets during the COVID-19 pandemic," Economic Analysis and Policy, Elsevier, vol. 71(C), pages 180-197.
    3. Yuyun Hidayat & Titi Purwandari & Sukono & Igif Gimin Prihanto & Rizki Apriva Hidayana & Riza Andrian Ibrahim, 2023. "Mean-Value-at-Risk Portfolio Optimization Based on Risk Tolerance Preferences and Asymmetric Volatility," Mathematics, MDPI, vol. 11(23), pages 1-26, November.
    4. Paul R. Dewick, 2022. "On Financial Distributions Modelling Methods: Application on Regression Models for Time Series," JRFM, MDPI, vol. 15(10), pages 1-15, October.
    5. Pal, Debdatta, 2022. "Does hospitality industry stock volatility react asymmetrically to health and economic crises?," Economic Modelling, Elsevier, vol. 108(C).
    6. Michael Graham & Jussi Nikkinen & Jarkko Peltomäki, 2020. "Web-Based Investor Fear Gauge and Stock Market Volatility: An Emerging Market Perspective," Journal of Emerging Market Finance, Institute for Financial Management and Research, vol. 19(2), pages 127-153, August.
    7. Abuzayed, Bana & Al-Fayoumi, Nedal, 2021. "Risk spillover from crude oil prices to GCC stock market returns: New evidence during the COVID-19 outbreak," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).
    8. Mateusz Tomal, 2021. "Modelling the Impact of Different COVID-19 Pandemic Waves on Real Estate Stock Returns and Their Volatility Using a GJR-GARCHX Approach: An International Perspective," JRFM, MDPI, vol. 14(8), pages 1-8, August.

  8. Amélie Charles & Olivier Darné & Fabien Tripier, 2018. "Uncertainty and the macroeconomy: evidence from an uncertainty composite indicator," Applied Economics, Taylor & Francis Journals, vol. 50(10), pages 1093-1107, February.
    See citations under working paper version above.
  9. Amélie Charles & Olivier Darné & Laurent Ferrara, 2018. "Does The Great Recession Imply The End Of The Great Moderation? International Evidence," Economic Inquiry, Western Economic Association International, vol. 56(2), pages 745-760, April.
    See citations under working paper version above.
  10. Eléazar Zerbo & Olivier Darné, 2018. "Unit root and trend breaks in per capita output: evidence from sub-Saharan African countries," Applied Economics, Taylor & Francis Journals, vol. 50(6), pages 634-658, February.

    Cited by:

    1. Luis A. Gil-Alana & Sakiru Adebola Solarin & Rangan Gupta, 2021. "Productivity and GDP: International Evidence of Persistence and Trends Over 130 Years of Data," Working Papers 202170, University of Pretoria, Department of Economics.
    2. Russo, Emanuele & Foster-McGregor, Neil & Verspagen, Bart, 2019. "Characterizing growth instability: new evidence on unit roots and structural breaks in long run time series," MERIT Working Papers 2019-026, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).
    3. Emanuele Russo & Neil Foster-McGregor, 2022. "Characterizing growth instability: new evidence on unit roots and structural breaks in countries’ long run trajectories," Journal of Evolutionary Economics, Springer, vol. 32(2), pages 713-756, April.

  11. Charles, Amélie & Darné, Olivier & Kim, Jae H., 2017. "Adaptive markets hypothesis for Islamic stock indices: Evidence from Dow Jones size and sector-indices," International Economics, Elsevier, vol. 151(C), pages 100-112.
    See citations under working paper version above.
  12. Charles, Amélie & Darné, Olivier & Kim, Jae H., 2017. "International stock return predictability: Evidence from new statistical tests," International Review of Financial Analysis, Elsevier, vol. 54(C), pages 97-113.
    See citations under working paper version above.
  13. Charles, Amélie & Darné, Olivier, 2017. "Forecasting crude-oil market volatility: Further evidence with jumps," Energy Economics, Elsevier, vol. 67(C), pages 508-519.
    See citations under working paper version above.
  14. Mogliani, Matteo & Darné, Olivier & Pluyaud, Bertrand, 2017. "The new MIBA model: Real-time nowcasting of French GDP using the Banque de France's monthly business survey," Economic Modelling, Elsevier, vol. 64(C), pages 26-39.
    See citations under working paper version above.
  15. Barhoumi, Karim & Darné, Olivier & Ferrara, Laurent, 2016. "A World Trade Leading Index (WTLI)," Economics Letters, Elsevier, vol. 146(C), pages 111-115.
    See citations under working paper version above.
  16. Amélie Charles & Olivier Darné, 2016. "Stock market reactions to FIFA World Cup announcements: An event study," Economics Bulletin, AccessEcon, vol. 36(4), pages 2028-2036.
    See citations under working paper version above.
  17. Am鬩e Charles & Olivier Darn頍 & Jae H. Kim & Etienne Redor, 2016. "Stock exchange mergers and market efficiency," Applied Economics, Taylor & Francis Journals, vol. 48(7), pages 576-589, February.
    See citations under working paper version above.
  18. Charlot, Philippe & Darné, Olivier & Moussa, Zakaria, 2016. "Commodity returns co-movements: Fundamentals or “style” effect?," Journal of International Money and Finance, Elsevier, vol. 68(C), pages 130-160.
    See citations under working paper version above.
  19. Amelie Charles & Olivier Darné, 2015. "Are the Islamic indexes size or sector oriented? evidence from Dow Jones Islamic indexes," Economics Bulletin, AccessEcon, vol. 35(3), pages 1897-1905.
    See citations under working paper version above.
  20. Charles, Amélie & Darné, Olivier & Diebolt, Claude & Ferrara, Laurent, 2015. "A new monthly chronology of the US industrial cycles in the prewar economy," Journal of Financial Stability, Elsevier, vol. 17(C), pages 3-9.
    See citations under working paper version above.
  21. Charles, Amélie & Darné, Olivier & Pop, Adrian, 2015. "Risk and ethical investment: Empirical evidence from Dow Jones Islamic indexes," Research in International Business and Finance, Elsevier, vol. 35(C), pages 33-56.
    See citations under working paper version above.
  22. Marie-Sophie Hervieux & Olivier Darné, 2015. "Environmental Kuznets Curve and ecological footprint: A time series analysis," Economics Bulletin, AccessEcon, vol. 35(1), pages 814-826.
    See citations under working paper version above.
  23. Charles, Amélie & Darné, Olivier & Kim, Jae H., 2015. "Will precious metals shine? A market efficiency perspective," International Review of Financial Analysis, Elsevier, vol. 41(C), pages 284-291.
    See citations under working paper version above.
  24. Olivier Darné & Amélie Charles & Claude Diebolt, 2014. "A revision of the US business-cycles chronology 1790-1928," Economics Bulletin, AccessEcon, vol. 34(1), pages 234-244.
    See citations under working paper version above.
  25. Charles, Amélie & Darné, Olivier, 2014. "Volatility persistence in crude oil markets," Energy Policy, Elsevier, vol. 65(C), pages 729-742.
    See citations under working paper version above.
  26. Karim Barhoumi & Olivier Darné & Laurent Ferrara, 2014. "Dynamic factor models: A review of the literature," OECD Journal: Journal of Business Cycle Measurement and Analysis, OECD Publishing, Centre for International Research on Economic Tendency Surveys, vol. 2013(2), pages 73-107.
    See citations under working paper version above.
  27. Charles, Amélie & Darné, Olivier, 2014. "Large shocks in the volatility of the Dow Jones Industrial Average index: 1928–2013," Journal of Banking & Finance, Elsevier, vol. 43(C), pages 188-199.
    See citations under working paper version above.
  28. Charles, Amélie & Darné, Olivier & Fouilloux, Jessica, 2013. "Market efficiency in the European carbon markets," Energy Policy, Elsevier, vol. 60(C), pages 785-792.
    See citations under working paper version above.
  29. Karim Barhoumi & Olivier Darné & Laurent Ferrara, 2013. "Testing the Number of Factors: An Empirical Assessment for a Forecasting Purpose," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 75(1), pages 64-79, February.
    See citations under working paper version above.
  30. Karim Barhoumi & Olivier Darné & Laurent Ferrara & Bertrand Pluyaud, 2012. "Monthly Gdp Forecasting Using Bridge Models: Application For The French Economy," Bulletin of Economic Research, Wiley Blackwell, vol. 64(Supplemen), pages 53-70, December.

    Cited by:

    1. Robert Lehmann, 2016. "Economic Growth and Business Cycle Forecasting at the Regional Level," ifo Beiträge zur Wirtschaftsforschung, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 65.
    2. Nyoni, Thabani, 2019. "Is the United States of America (USA) really being made great again? witty insights from the Box-Jenkins ARIMA approach," MPRA Paper 91353, University Library of Munich, Germany.
    3. Claudia Foroni & Massimiliano Marcellino, 2013. "A survey of econometric methods for mixed-frequency data," Working Paper 2013/06, Norges Bank.
    4. Laurent Ferrara & Clément Marsilli & Juan-Pablo Ortega, 2013. "Forecasting US growth during the Great Recession: Is the financial volatility the missing ingredient?," Working Papers hal-04141198, HAL.
    5. Christos Papamichael & Nicoletta Pashourtidou, 2016. "The Role of Survey Data in the Construction of Short-term GDP Growth Forecasts," Cyprus Economic Policy Review, University of Cyprus, Economics Research Centre, vol. 10(2), pages 77-109, December.
    6. Katja Heinisch & Rolf Scheufele, 2018. "Bottom-up or direct? Forecasting German GDP in a data-rich environment," Empirical Economics, Springer, vol. 54(2), pages 705-745, March.
    7. Soybilgen, Barış & Yazgan, Ege, 2018. "Evaluating nowcasts of bridge equations with advanced combination schemes for the Turkish unemployment rate," Economic Modelling, Elsevier, vol. 72(C), pages 99-108.
    8. Frédérique Savignac & Erwan Gautier & Yuriy Gorodnichenko & Olivier Coibion, 2021. "Firms’ Inflation Expectations: New Evidence from France," Working papers 840, Banque de France.
    9. Nikolay P. Pilnik & Igor Pospelov & Ivan P. Stankevich, 2015. "Multiproduct Model Decomposition of Components of Russian GDP," HSE Working papers WP BRP 111/EC/2015, National Research University Higher School of Economics.
    10. Petralias, Athanassios & Petros, Sotirios & Prodromídis, Pródromos, 2013. "Greece in recession: economic predictions, mispredictions and policy implications," LSE Research Online Documents on Economics 52626, London School of Economics and Political Science, LSE Library.
    11. Dr. Gregor Bäurle & Elizabeth Steiner & Dr. Gabriel Züllig, 2018. "Forecasting the production side of GDP," Working Papers 2018-16, Swiss National Bank.
    12. Nyoni, Thabani, 2019. "Is South Africa the South Africa we all desire? Insights from the Box-Jenkins ARIMA approach," MPRA Paper 92441, University Library of Munich, Germany.
    13. Antipa, Pamfili & Barhoumi, Karim & Brunhes-Lesage, Véronique & Darné, Olivier, 2012. "Nowcasting German GDP: A comparison of bridge and factor models," Journal of Policy Modeling, Elsevier, vol. 34(6), pages 864-878.
    14. Dées, Stéphane & Güntner, Jochen, 2014. "Analysing and forecasting price dynamics across euro area countries and sectors: a panel VAR approach," Working Paper Series 1724, European Central Bank.
    15. Christophe Piette, 2016. "Predicting Belgium’s GDP using targeted bridge models," Working Paper Research 290, National Bank of Belgium.
    16. Nicoletta Pashourtidou & Christos Papamichael & Charalampos Karagiannakis, 2018. "Forecasting economic activity in sectors of the Cypriot economy," Cyprus Economic Policy Review, University of Cyprus, Economics Research Centre, vol. 12(2), pages 24-66, December.
    17. Nyoni, Thabani, 2019. "Where is Kenya being headed to? Empirical evidence from the Box-Jenkins ARIMA approach," MPRA Paper 91395, University Library of Munich, Germany.

  31. Charles, Amélie & Darné, Olivier, 2012. "Trends and random walks in macroeconomic time series: A reappraisal," Journal of Macroeconomics, Elsevier, vol. 34(1), pages 167-180.
    See citations under working paper version above.
  32. Antipa, Pamfili & Barhoumi, Karim & Brunhes-Lesage, Véronique & Darné, Olivier, 2012. "Nowcasting German GDP: A comparison of bridge and factor models," Journal of Policy Modeling, Elsevier, vol. 34(6), pages 864-878.
    See citations under working paper version above.
  33. Amélie Charles & Olivier Darne & Jean-François Hoarau, 2012. "Convergence of real per capita GDP within COMESA countries: A panel unit root evidence," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 49(1), pages 53-71, August.
    See citations under working paper version above.
  34. Charles, Amélie & Darné, Olivier & Kim, Jae H., 2012. "Exchange-rate return predictability and the adaptive markets hypothesis: Evidence from major foreign exchange rates," Journal of International Money and Finance, Elsevier, vol. 31(6), pages 1607-1626.
    See citations under working paper version above.
  35. Olivier Darné & Amélie Charles, 2012. "A note on the uncertain trend in US real GNP: Evidence from robust unit root tests," Economics Bulletin, AccessEcon, vol. 32(3), pages 2399-2406.
    See citations under working paper version above.
  36. Karim Barhoumi & Olivier Darné & Laurent Ferrara, 2012. "Une revue de la littérature des modèles à facteurs dynamiques," Économie et Prévision, Programme National Persée, vol. 199(1), pages 51-77.
    See citations under working paper version above.
  37. Brunhes-Lesage, Véronique & Darné, Olivier, 2012. "Nowcasting the French index of industrial production: A comparison from bridge and factor models," Economic Modelling, Elsevier, vol. 29(6), pages 2174-2182.

    Cited by:

    1. Tian Wu & Mengbo Zhang & Xunmin Ou, 2014. "Analysis of Future Vehicle Energy Demand in China Based on a Gompertz Function Method and Computable General Equilibrium Model," Energies, MDPI, vol. 7(11), pages 1-29, November.
    2. Olivier Darne & Amelie Charles, 2020. "Nowcasting GDP growth using data reduction methods: Evidence for the French economy," Economics Bulletin, AccessEcon, vol. 40(3), pages 2431-2439.
    3. Mogliani, Matteo & Darné, Olivier & Pluyaud, Bertrand, 2017. "The new MIBA model: Real-time nowcasting of French GDP using the Banque de France's monthly business survey," Economic Modelling, Elsevier, vol. 64(C), pages 26-39.
    4. A. Girardi & R. Golinelli & C. Pappalardo, 2014. "The Role of Indicator Selection in Nowcasting Euro Area GDP in Pseudo Real Time," Working Papers wp919, Dipartimento Scienze Economiche, Universita' di Bologna.
    5. Enrico D’Elia & Francesca Faedda & Giacomo Giannone, 2020. "Un modello statistico per il monitoraggio delle entrate tributarie (MoME)," Working Papers wp2020-5, Ministry of Economy and Finance, Department of Finance.
    6. Soybilgen, Barış & Yazgan, Ege, 2018. "Evaluating nowcasts of bridge equations with advanced combination schemes for the Turkish unemployment rate," Economic Modelling, Elsevier, vol. 72(C), pages 99-108.
    7. Alejo Estavillo & Gabriela Mordecki, 2023. "Nowcasting del PIB para Uruguay en base a un modelo de ecuaciones puente," Documentos de Trabajo (working papers) 23-26, Instituto de Economía - IECON.
    8. Corradini, Riccardo, 2018. "A set of state space models at an high disaggregation level to forecast Italian Industrial Production," MPRA Paper 84558, University Library of Munich, Germany, revised 12 Feb 2018.
    9. Marek Rusnak, 2013. "Nowcasting Czech GDP in Real Time," Working Papers 2013/06, Czech National Bank.
    10. Amélie Charles & Chew Lian Chua & Olivier Darné & Sandy Suardi, 2021. "Oil price shocks, real economic activity and uncertainty," Bulletin of Economic Research, Wiley Blackwell, vol. 73(3), pages 364-392, July.
    11. Riccardo Corradini, 2019. "A Set of State–Space Models at a High Disaggregation Level to Forecast Italian Industrial Production," J, MDPI, vol. 2(4), pages 1-53, November.
    12. Fornaro, Paolo, 2020. "Nowcasting Industrial Production Using Uncoventional Data Sources," ETLA Working Papers 80, The Research Institute of the Finnish Economy.

  38. Charles, Amélie & Darné, Olivier & Kim, Jae H., 2011. "Small sample properties of alternative tests for martingale difference hypothesis," Economics Letters, Elsevier, vol. 110(2), pages 151-154, February.
    See citations under working paper version above.
  39. Olivier Darné & Laurent Ferrara, 2011. "Identification of Slowdowns and Accelerations for the Euro Area Economy," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 73(3), pages 335-364, June.
    See citations under working paper version above.
  40. Olivier Darné & Amélie Charles, 2011. "Large shocks in U.S. macroeconomic time series: 1860-1988," Cliometrica, Journal of Historical Economics and Econometric History, Association Française de Cliométrie (AFC), vol. 5(1), pages 79-100, January.
    See citations under working paper version above.
  41. Charles, Amélie & Darné, Olivier & Fouilloux, Jessica, 2011. "Testing the martingale difference hypothesis in CO2 emission allowances," Economic Modelling, Elsevier, vol. 28(1-2), pages 27-35, January.
    See citations under working paper version above.
  42. Karim Barhoumi & Olivier Darné & Laurent Ferrara, 2010. "Are disaggregate data useful for factor analysis in forecasting French GDP?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 29(1-2), pages 132-144.
    See citations under working paper version above.
  43. Marie Adanero-Donderis & Olivier Darné & Laurent Ferrara, 2009. "Un indicateur probabiliste du cycle d’accélération pour l’économie française," Économie et Prévision, Programme National Persée, vol. 189(3), pages 95-114.

    Cited by:

    1. Antonin Aviat & Frédérique Bec & Claude Diebolt & Catherine Doz & Denis Ferrand & Laurent Ferrara & Eric Heyer & Valérie Mignon & Pierre-Alain Pionnier, 2021. "Dating business cycles in France: A reference chronology," Working Papers of BETA 2021-33, Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg.

  44. Charles, Amélie & Darné, Olivier, 2009. "The random walk hypothesis for Chinese stock markets: Evidence from variance ratio tests," Economic Systems, Elsevier, vol. 33(2), pages 117-126, June.
    See citations under working paper version above.
  45. Amélie Charles & Olivier Darné, 2009. "Variance‐Ratio Tests Of Random Walk: An Overview," Journal of Economic Surveys, Wiley Blackwell, vol. 23(3), pages 503-527, July.
    See citations under working paper version above.
  46. Amelie Charles & Olivier Darne, 2009. "Testing for Random Walk Behavior in Euro Exchange Rates," Economie Internationale, CEPII research center, issue 119, pages 25-45.
    See citations under working paper version above.
  47. Charles, Amélie & Darné, Olivier, 2009. "The efficiency of the crude oil markets: Evidence from variance ratio tests," Energy Policy, Elsevier, vol. 37(11), pages 4267-4272, November.
    See citations under working paper version above.
  48. Darné, Olivier, 2009. "The uncertain unit root in real GNP: A re-examination," Journal of Macroeconomics, Elsevier, vol. 31(1), pages 153-166, March.

    Cited by:

    1. Rémy Herrera & Long Zhiming, 2020. "Spurious OLS Estimators of Detrending Method by Adding a Linear Trend in Difference-Stationary Processes - A Mathematical Proof and its Verification by Simulation," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-03083782, HAL.
    2. Amélie Charles & Olivier Darné, 0. "Econometric history of the growth–volatility relationship in the USA: 1919–2017," Cliometrica, Springer;Cliometric Society (Association Francaise de Cliométrie), vol. 0, pages 1-24.
    3. Rohan Best & Paul J Burke, 2017. "Macroeconomic impacts of the 2010 earthquake in Haiti," Departmental Working Papers 2017-15, The Australian National University, Arndt-Corden Department of Economics.
    4. Noriega Antonio E. & Ventosa-Santaulària Daniel, 2010. "Spurious Long-Horizon Regression in Econometrics," Working Papers 2010-06, Banco de México.
    5. Kim, Jae & Choi, In, 2015. "Unit Roots in Economic and Financial Time Series: A Re-Evaluation based on Enlightened Judgement," MPRA Paper 68411, University Library of Munich, Germany.
    6. Olivier Darné & Amélie Charles, 2012. "A note on the uncertain trend in US real GNP: Evidence from robust unit root tests," Economics Bulletin, AccessEcon, vol. 32(3), pages 2399-2406.
    7. Noriega Antonio E. & Rodríguez-Pérez Cid Alonso, 2011. "Stationarity, structural breaks, and economic growth in Mexico: 1895-2008," Working Papers 2011-11, Banco de México.
    8. David Grreasley, 2010. "Cliometrics and Time Series Econometrics: Some Theory and Applications," Working Papers in Economics 10/56, University of Canterbury, Department of Economics and Finance.
    9. Lyócsa, Štefan & Výrost, Tomáš & Baumöhl, Eduard, 2011. "Unit-root and stationarity testing with empirical application on industrial production of CEE-4 countries," MPRA Paper 29648, University Library of Munich, Germany.
    10. Czudaj, Robert & Hanck, Christoph, 2013. "Nonstationary-Volatility Robust Panel Unit Root Tests and the Great Moderation," VfS Annual Conference 2013 (Duesseldorf): Competition Policy and Regulation in a Global Economic Order 79734, Verein für Socialpolitik / German Economic Association.
    11. Jean-François Goux, 2010. "Une approche déterministe du taux de change euro-dollar," Économie et Prévision, Programme National Persée, vol. 195(4), pages 35-51.
    12. Krzysztof Bartosik & Jerzy Mycielski, 2016. "Dynamika płac a długotrwałe bezrobocie w polskiej gospodarce," Bank i Kredyt, Narodowy Bank Polski, vol. 47(5), pages 435-462.
    13. Ventosa-Santaulària, Daniel & Noriega, Antonio E., 2015. "Long-run monetary neutrality under stochastic and deterministic trends," Economic Modelling, Elsevier, vol. 47(C), pages 372-382.

  49. Olivier Darné & Amélie Charles, 2008. "The impact of outliers on transitory and permanent components in macroeconomic time series," Economics Bulletin, AccessEcon, vol. 3(60), pages 1-9.
    See citations under working paper version above.
  50. Brunhes-Lesage, V. & Darné, O., 2008. "Pourquoi calculer un indicateur du climat des affaires dans les services ?," Bulletin de la Banque de France, Banque de France, issue 171, pages 23-29.

    Cited by:

    1. Lise Pichette, 2012. "Extracting Information from the Business Outlook Survey Using Statistical Approaches," Discussion Papers 12-8, Bank of Canada.

  51. Olivier Darne, 2008. "Using business survey in industrial and services sector to nowcast GDP growth:The French case," Economics Bulletin, AccessEcon, vol. 3(32), pages 1-8.

    Cited by:

    1. Dominique Guégan & Patrick Rakotomarolahy, 2010. "A Short Note on the Nowcasting and the Forecasting of Euro-area GDP Using Non-Parametric Techniques," Economics Bulletin, AccessEcon, vol. 30(1), pages 508-518.
    2. Clément Bortoli & Stéphanie Combes & Thomas Renault, 2018. "Nowcasting GDP Growth by Reading Newspapers," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-03205161, HAL.
    3. Bhattacharya, Rudrani & Pandey, Radhika & Veronese, Giovanni, 2011. "Tracking India Growth in Real Time," Working Papers 11/90, National Institute of Public Finance and Policy.
    4. Abdić Ademir & Resić Emina & Abdić Adem & Rovčanin Adnan, 2020. "Nowcasting GDP of Bosnia and Herzegovina: A Comparison of Forecast Accuracy Models," South East European Journal of Economics and Business, Sciendo, vol. 15(2), pages 1-14, December.
    5. Sergey V. Arzhenovskiy, 2024. "Forecasting GDP Dynamics Based on the Bank of Russia’s Enterprise Monitoring Data," Finansovyj žhurnal — Financial Journal, Financial Research Institute, Moscow 125375, Russia, issue 1, pages 31-44, February.
    6. Dominique Guegan & Patrick Rakotomarolahy, 2010. "A Short Note on the Nowcasting and the Forecasting of Euro-area GDP Using Non-Parametric Techniques," PSE-Ecole d'économie de Paris (Postprint) halshs-00460472, HAL.
    7. Dominique Guegan & Patrick Rakotomarolahy, 2010. "Alternative methods for forecasting GDP," PSE-Ecole d'économie de Paris (Postprint) halshs-00511979, HAL.
    8. Guizzardi, Andrea & Stacchini, Annalisa, 2015. "Real-time forecasting regional tourism with business sentiment surveys," Tourism Management, Elsevier, vol. 47(C), pages 213-223.

  52. Olivier Darné & Jean-François Hoarau, 2008. "La parité des pouvoirs d'achat pour l'économie chinoise : une nouvelle analyse par les tests de racine unitaire," Recherches économiques de Louvain, De Boeck Université, vol. 74(2), pages 219-236.
    See citations under working paper version above.
  53. Darné, O. & Brunhes-Lesage, V., 2007. "L’indicateur synthétique mensuel d’activité (ISMA) : une révision," Bulletin de la Banque de France, Banque de France, issue 162, pages 21-36.
    See citations under working paper version above.
  54. Olivier Darne & Jean-Francois Hoarau, 2007. "The purchasing power parity in Australia: evidence from unit root test with structural break," Applied Economics Letters, Taylor & Francis Journals, vol. 15(3), pages 203-206.
    See citations under working paper version above.
  55. Olivier Darné & Jean‐François Hoarau, 2007. "Further Evidence On Mean Reversion In The Australian Exchange Rate," Bulletin of Economic Research, Wiley Blackwell, vol. 59(4), pages 383-395, October.

    Cited by:

    1. Jiranyakul, Komain & Batavia, Bala, 2009. "Does Purchasing Power Parity hold in Thailand?," MPRA Paper 47032, University Library of Munich, Germany.
    2. Chiang, Shu-Mei & Lee, Yen-Hsien & Su, Hsin-Mei & Tzou, Yi-Pin, 2010. "Efficiency tests of foreign exchange markets for four Asian Countries," Research in International Business and Finance, Elsevier, vol. 24(3), pages 284-294, September.

  56. Olivier Darné & Claude Diebolt, 2006. "Chocs temporaires et permanents dans le PIB de la France, du Royaume-Uni et des États-Unis," Revue d'économie politique, Dalloz, vol. 116(1), pages 65-78.
    See citations under working paper version above.
  57. Charles, Amelie & Darne, Olivier, 2006. "Large shocks and the September 11th terrorist attacks on international stock markets," Economic Modelling, Elsevier, vol. 23(4), pages 683-698, July.

    Cited by:

    1. Fang, WenShwo & Miller, Stephen M., 2009. "Modeling the volatility of real GDP growth: The case of Japan revisited," Japan and the World Economy, Elsevier, vol. 21(3), pages 312-324, August.
    2. Charles, Amélie & Darné, Olivier, 2014. "Large shocks in the volatility of the Dow Jones Industrial Average index: 1928–2013," Journal of Banking & Finance, Elsevier, vol. 43(C), pages 188-199.
    3. Park, Jin Suk & Newaz, Mohammad Khaleq, 2018. "Do terrorist attacks harm financial markets? A meta-analysis of event studies and the determinants of adverse impact," Global Finance Journal, Elsevier, vol. 37(C), pages 227-247.
    4. Zopiatis, A. & Savva, C.S. & Lambertides, N. & McAleer, M.J., 2016. "Tourism Stocks in Times of Crises: an Econometric Investigation of Non-macro Factors," Econometric Institute Research Papers TI 2016-104/III, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    5. Guangxi Cao & Wei Xu & Yu Guo, 2015. "Effects of climatic events on the Chinese stock market: applying event analysis," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 77(3), pages 1979-1992, July.
    6. Guidi, Francesco, 2010. "Cointegration relationship and time varying co-movements among Indian and Asian developed stock markets," MPRA Paper 19853, University Library of Munich, Germany.
    7. WenShwo Fang & Stephen M. Miller, 2012. "Output Growth and Its Volatility: The Gold Standard through the Great Moderation," Working papers 2012-11, University of Connecticut, Department of Economics.
    8. Paresh Kumar Narayan & Seema Narayan & Siroos Khademalomoom & Dinh Hoang Bach Phan, 2018. "Do Terrorist Attacks Impact Exchange Rate Behavior? New International Evidence," Economic Inquiry, Western Economic Association International, vol. 56(1), pages 547-561, January.
    9. Randall K. Filer & Dragana Stanisic, 2013. "The Effect of Terrorist Incidents on Capital Flows," CERGE-EI Working Papers wp480, The Center for Economic Research and Graduate Education - Economics Institute, Prague.
    10. Gazi Salah Uddin & Mohamed Arouri & Aviral Kumar Tiwari, 2014. "Co-movements between Germany and International Stock Markets: Some New Evidence from DCC-GARCH and Wavelet Approaches," Working Papers 2014-143, Department of Research, Ipag Business School.
    11. Gok, Ibrahim Yasar & Demirdogen, Yavuz & Topuz, Sefa, 2020. "The impacts of terrorism on Turkish equity market: An investigation using intraday data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 540(C).
    12. Abu Bakar, Norhidayah & Masih, Abul Mansur M., 2014. "The Dynamic Linkages between Islamic Index and the Major Stock Markets: New Evidence from Wavelet time-scale decomposition Analysis," MPRA Paper 56977, University Library of Munich, Germany.
    13. Shahzad, Syed Jawad Hussain & Zakaria, Muhammad & Rehman, Mobeen ur & Ahmed, Tanveer & Khalid, Saniya, 2014. "Co-Movement of Pakistan Stock Exchange with India, S&P 500 and Nikkei 225: A Time-frequency (Wavelets) Analysis," MPRA Paper 60579, University Library of Munich, Germany.
    14. Mohamed Ali Houfi & Ghassen El Montasser, 2010. "Effets des points aberrants sur les tests de normalité et de linéarité. Applications à la bourse de Tokyo," Romanian Economic Journal, Department of International Business and Economics from the Academy of Economic Studies Bucharest, vol. 13(36), pages 15-51, June.
    15. Iwanicz-Drozdowska, Małgorzata & Rogowicz, Karol & Kurowski, Łukasz & Smaga, Paweł, 2021. "Two decades of contagion effect on stock markets: Which events are more contagious?," Journal of Financial Stability, Elsevier, vol. 55(C).
    16. Thai-Ha Le & Donghyun Park & Cong-Phu-Khanh Tran & Binh Tran-Nam, 2018. "The Impact of the Hai Yang Shi You 981 Event on Vietnam’s Stock Markets," Journal of Emerging Market Finance, Institute for Financial Management and Research, vol. 17(3_suppl), pages 344-375, December.
    17. Konstantinos Drakos, 2009. "Big Questions, Little Answers: Terrorism Activity, Investor Sentiment and Stock Returns," Economics of Security Working Paper Series 8, DIW Berlin, German Institute for Economic Research.
    18. Ben Rejeb, Aymen & Arfaoui, Mongi, 2016. "Financial market interdependencies: A quantile regression analysis of volatility spillover," Research in International Business and Finance, Elsevier, vol. 36(C), pages 140-157.
    19. Ahmad, Tanveer & Shahzad, Syed Jawad Hussain & Rehman, Mobeen ur, 2014. "Industry Premiums and Systematic Risk under Terror: Empirical Evidence from Pakistan," MPRA Paper 60082, University Library of Munich, Germany.
    20. Corbet, Shaen & McMullan, Caroline, 2018. "Stock market reaction to irregular supermarket chain behaviour: An investigation in the retail sectors of Ireland and the United Kingdom," Journal of Retailing and Consumer Services, Elsevier, vol. 43(C), pages 20-29.
    21. Drakos, Konstantinos, 2010. "Terrorism activity, investor sentiment, and stock returns," Review of Financial Economics, Elsevier, vol. 19(3), pages 128-135, August.
    22. Hudson, Robert & Urquhart, Andrew, 2015. "War and stock markets: The effect of World War Two on the British stock market," International Review of Financial Analysis, Elsevier, vol. 40(C), pages 166-177.
    23. M. Angeles Carnero & Daniel Peña & Esther Ruiz, 2008. "Estimating and Forecasting GARCH Volatility in the Presence of Outiers," Working Papers. Serie AD 2008-13, Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie).
    24. Cizek, P. & Haerdle, W. & Spokoiny, V., 2007. "Adaptive Pointwise Estimation in Time-Inhomogeneous Time-Series Models," Discussion Paper 2007-35, Tilburg University, Center for Economic Research.
    25. Zopiatis, A. & Savva, C.S. & Lambertides, N. & McAleer, M.J., 2017. "Tourism Stocks in Times of Crises: An Econometric Investigation of Unexpected Non-macroeconomic Factors," Econometric Institute Research Papers EI2017-15, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    26. Ben Rejeb, Aymen, 2017. "On the volatility spillover between lslamic and conventional stock markets: A quantile regression analysis," Research in International Business and Finance, Elsevier, vol. 42(C), pages 794-815.
    27. Les Coleman, 2012. "Testing equity market efficiency around terrorist attacks," Applied Economics, Taylor & Francis Journals, vol. 44(31), pages 4087-4099, November.
    28. Aymen Ben Rejeb, 2013. "Volatility spillovers and contagion: an empirical analysis of structural changes in emerging market volatility," Economics Bulletin, AccessEcon, vol. 33(1), pages 56-71.
    29. Corbet, Shaen & Gurdgiev, Constantin & Meegan, Andrew, 2018. "Long-term stock market volatility and the influence of terrorist attacks in Europe," The Quarterly Review of Economics and Finance, Elsevier, vol. 68(C), pages 118-131.
    30. Idier, J., 2006. "Stock exchanges industry consolidation and shock transmission," Working papers 159, Banque de France.
    31. Sermpinis, Georgios & Stasinakis, Charalampos & Dunis, Christian, 2014. "Stochastic and genetic neural network combinations in trading and hybrid time-varying leverage effects," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 30(C), pages 21-54.
    32. George Halkos & Argyro Zisiadou, 2020. "Is Investors’ Psychology Affected Due to a Potential Unexpected Environmental Disaster?," JRFM, MDPI, vol. 13(7), pages 1-24, July.
    33. Viorica CHIRILA & Ciprian CHIRILA, 2018. "Effects of US Monetary Policy on Eastern European Financial Markets," CES Working Papers, Centre for European Studies, Alexandru Ioan Cuza University, vol. 10(2), pages 149-166, August.
    34. Emrah Koçak & Umit Bulut & Angeliki N. Menegaki, 2022. "The resilience of green firms in the twirl of COVID‐19: Evidence from S&P500 Carbon Efficiency Index with a Fourier approach," Business Strategy and the Environment, Wiley Blackwell, vol. 31(1), pages 32-45, January.
    35. Mobeen Ur Rehman & Wafa Ghardallou & Nasir Ahmad & Xuan Vinh Vo & Sang Hoon Kang, 2024. "Does effect of risk and uncertainties on US sectoral returns differ across different investment horizons and market conditions," Risk Management, Palgrave Macmillan, vol. 26(1), pages 1-49, February.
    36. Massimiliano Mazzanti & Antonio Musolesi, 2011. "Income and time related effects in EKC," Working Papers 201105, University of Ferrara, Department of Economics.
    37. Aslam Faheem & Awan Tahir Mumtaz & Mohmand Yasir Tariq & Kang Hyoung-Goo & Mughal Khurrum Shahzad, 2021. "Stock Market Volatility and Terrorism: New Evidence from the Markov Switching Model," Peace Economics, Peace Science, and Public Policy, De Gruyter, vol. 27(2), pages 263-284, May.
    38. Jin, Xiaoye & An, Ximeng, 2016. "Global financial crisis and emerging stock market contagion: A volatility impulse response function approach," Research in International Business and Finance, Elsevier, vol. 36(C), pages 179-195.
    39. Halkos, George & Managi, Shunsuke & Zisiadou, Argyro, 2017. "Analyzing the determinants of terrorist attacks and their market reactions," Economic Analysis and Policy, Elsevier, vol. 54(C), pages 57-73.
    40. Pattnaik, Debidutta & Kumar, Satish & Burton, Bruce & Lim, Weng Marc, 2022. "Economic Modelling at thirty-five: A retrospective bibliometric survey," Economic Modelling, Elsevier, vol. 107(C).
    41. Ben Rejeb, Aymen & Arfaoui, Mongi, 2016. "Conventional and Islamic stock markets: what about financial performance?," MPRA Paper 73495, University Library of Munich, Germany.
    42. Zhou, Mei-Jing & Huang, Jian-Bai & Chen, Jin-Yu, 2020. "The effects of geopolitical risks on the stock dynamics of China's rare metals: A TVP-VAR analysis," Resources Policy, Elsevier, vol. 68(C).
    43. Narayan, S. & Le, T.-H. & Sriananthakumar, S., 2018. "The influence of terrorism risk on stock market integration: Evidence from eight OECD countries," International Review of Financial Analysis, Elsevier, vol. 58(C), pages 247-259.
    44. Massimiliano Mazzanti & Antonio Musolesi, 2010. "Carbon Abatement Leaders and Laggards Non Parametric Analyses of Policy Oriented Kuznets Curves," Working Papers 2010.149, Fondazione Eni Enrico Mattei.
    45. Gan Jin & Md Rafiul Karim & Günther G. Schulze, 2024. "The Stock Market Effects of Islamist versus Non-Islamist Terror," CESifo Working Paper Series 10960, CESifo.
    46. Aymen Ben Rejeb & Adel Boughrara, 2015. "Financial integration in emerging market economies: Effects on volatility transmission and contagion," Borsa Istanbul Review, Research and Business Development Department, Borsa Istanbul, vol. 15(3), pages 161-179, September.
    47. Halkos, George & Zisiadou, Argyro, 2016. "Exploring the effect of terrorist attacks on markets," MPRA Paper 71877, University Library of Munich, Germany.
    48. Christos Kollias & Stephanos Papadamou & Costas Siriopoulos, 2013. "European Markets’ Reactions to Exogenous Shocks: A High Frequency Data Analysis of the 2005 London Bombings," IJFS, MDPI, vol. 1(4), pages 1-14, November.
    49. Umar, Zaghum & Polat, Onur & Choi, Sun-Yong & Teplova, Tamara, 2022. "The impact of the Russia-Ukraine conflict on the connectedness of financial markets," Finance Research Letters, Elsevier, vol. 48(C).
    50. Ben Rejeb, Aymen, 2016. "Volatility Spillover between Islamic and conventional stock markets: evidence from Quantile Regression analysis," MPRA Paper 73302, University Library of Munich, Germany.
    51. Chang, Bisharat & Iqbal, Javed, 2014. "Financial Analysis of Industrial Portfolios in Pakistan: A Comparative Analysis of Pre 9/11 and Post 9/11Period," MPRA Paper 55433, University Library of Munich, Germany.
    52. Lee, Chien-Chiang & Chen, Mei-Ping, 2020. "Do natural disasters and geopolitical risks matter for cross-border country exchange-traded fund returns?," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
    53. Jorge Andraz & Paulo Rodrigues, 2010. "Events that marked tourism in Portugal," Applied Economics Letters, Taylor & Francis Journals, vol. 17(8), pages 761-766.
    54. Aloui, Chaker & Hkiri, Besma, 2014. "Co-movements of GCC emerging stock markets: New evidence from wavelet coherence analysis," Economic Modelling, Elsevier, vol. 36(C), pages 421-431.
    55. Carnero, M. Angeles & Peña, Daniel & Ruiz, Esther, 2012. "Estimating GARCH volatility in the presence of outliers," Economics Letters, Elsevier, vol. 114(1), pages 86-90.
    56. Muhammad Niaz Khan & Suzanne G. M. Fifield & Nongnuch Tantisantiwong & David M. Power, 2022. "Changes in co-movement and risk transmission between South Asian stock markets amidst the development of regional co-operation," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 36(1), pages 87-117, March.
    57. Hussain, Shahzad & Akbar, Muhammad & Malik, Qaisar & Ahmad, Tanveer & Abbas, Nasir, 2021. "Downside Systematic Risk in Pakistani Stock Market: Role of Corporate Governance, Financial Liberalization and Investor Sentiment," CAFE Working Papers 14, Centre for Accountancy, Finance and Economics (CAFE), Birmingham City Business School, Birmingham City University.
    58. Yu, Lean & Zha, Rui & Stafylas, Dimitrios & He, Kaijian & Liu, Jia, 2020. "Dependences and volatility spillovers between the oil and stock markets: New evidence from the copula and VAR-BEKK-GARCH models," International Review of Financial Analysis, Elsevier, vol. 68(C).
    59. Ahmed, Walid M.A., 2008. "Cointegration and dynamic linkages of international stock markets: an emerging market perspective," MPRA Paper 26986, University Library of Munich, Germany.
    60. Christos Kollias & Stephanos Papadamou & Vangelis Arvanitis, 2013. "Does Terrorism Affect the Stock‐Bond Covariance? Evidence from European Countries," Southern Economic Journal, John Wiley & Sons, vol. 79(4), pages 832-848, April.
    61. Evrim Mandaci, Pınar & Azimli, Asil & Mandaci, Nazif, 2023. "The impact of geopolitical risks on connectedness among natural resource commodities: A quantile vector autoregressive approach," Resources Policy, Elsevier, vol. 85(PA).
    62. Min-Hsien Chiang & Ray Yeutien Chou & Li-Min Wang, 2016. "Outlier Detection in the Lognormal Logarithmic Conditional Autoregressive Range Model," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 78(1), pages 126-144, February.

  58. Charles, Amelie & Darne, Olivier, 2005. "Outliers and GARCH models in financial data," Economics Letters, Elsevier, vol. 86(3), pages 347-352, March.

    Cited by:

    1. Amélie Charles & Olivier Darné, 2012. "Volatility Persistence in Crude Oil Markets," Working Papers hal-00719387, HAL.
    2. Fang, WenShwo & Miller, Stephen M., 2009. "Modeling the volatility of real GDP growth: The case of Japan revisited," Japan and the World Economy, Elsevier, vol. 21(3), pages 312-324, August.
    3. Charles, Amélie & Darné, Olivier, 2014. "Large shocks in the volatility of the Dow Jones Industrial Average index: 1928–2013," Journal of Banking & Finance, Elsevier, vol. 43(C), pages 188-199.
    4. WenShwo Fang & Stephen M. Miller, 2012. "Output Growth and Its Volatility: The Gold Standard through the Great Moderation," Working papers 2012-11, University of Connecticut, Department of Economics.
    5. Hotta, Luiz & Trucíos, Carlos & Ruiz Ortega, Esther, 2015. "Robust bootstrap forecast densities for GARCH models: returns, volatilities and value-at-risk," DES - Working Papers. Statistics and Econometrics. WS ws1523, Universidad Carlos III de Madrid. Departamento de Estadística.
    6. Laurent Ferrara & Clément Marsilli & Juan-Pablo Ortega, 2013. "Forecasting US growth during the Great Recession: Is the financial volatility the missing ingredient?," Working Papers hal-04141198, HAL.
    7. Charles, Amelie & Darne, Olivier, 2006. "Large shocks and the September 11th terrorist attacks on international stock markets," Economic Modelling, Elsevier, vol. 23(4), pages 683-698, July.
    8. Cristina Chinazzo & Vahidin Jeleskovic, 2024. "Forecasting Bitcoin Volatility: A Comparative Analysis of Volatility Approaches," Papers 2401.02049, arXiv.org.
    9. Piotr Fiszeder & Marta Ma³ecka, 2022. "Forecasting volatility during the outbreak of Russian invasion of Ukraine: application to commodities, stock indices, currencies, and cryptocurrencies," Equilibrium. Quarterly Journal of Economics and Economic Policy, Institute of Economic Research, vol. 17(4), pages 939-967, December.
    10. Grané, Aurea & Veiga, Helena, 2010. "Outliers in Garch models and the estimation of risk measures," DES - Working Papers. Statistics and Econometrics. WS ws100502, Universidad Carlos III de Madrid. Departamento de Estadística.
    11. Dewachter, Hans & Erdemlioglu, Deniz & Gnabo, Jean-Yves & Lecourt, Christelle, 2014. "The intra-day impact of communication on euro-dollar volatility and jumps," Journal of International Money and Finance, Elsevier, vol. 43(C), pages 131-154.
    12. YAMAMOTO, Yohei & 山本, 庸平, 2015. "Asymptotic Inference for Common Factor Models in the Presence of Jumps," Discussion Papers 2015-05, Graduate School of Economics, Hitotsubashi University.
    13. Laurent, Sébastien & Lecourt, Christelle & Palm, Franz C., 2016. "Testing for jumps in conditionally Gaussian ARMA–GARCH models, a robust approach," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 383-400.
    14. Wagner Piazza Gaglianone & Luiz Renato Lima & Oliver Linton & Daniel R. Smith, 2011. "Evaluating Value-at-Risk Models via Quantile Regression," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 29(1), pages 150-160, January.
    15. Behmiri, Niaz Bashiri & Manera, Matteo, 2015. "The Role of Outliers and Oil Price Shocks on Volatility of Metal Prices," Energy: Resources and Markets 208768, Fondazione Eni Enrico Mattei (FEEM).
    16. Liu, Feng & Xu, Jie & Ai, Chunrong, 2023. "Heterogeneous impacts of oil prices on China's stock market: Based on a new decomposition method," Energy, Elsevier, vol. 268(C).
    17. Chikashi Tsuji, 2016. "Does the fear gauge predict downside risk more accurately than econometric models? Evidence from the US stock market," Cogent Economics & Finance, Taylor & Francis Journals, vol. 4(1), pages 1220711-122, December.
    18. Charles, Amélie & Darné, Olivier, 2017. "Forecasting crude-oil market volatility: Further evidence with jumps," Energy Economics, Elsevier, vol. 67(C), pages 508-519.
    19. Lisa Crosato & Luigi Grossi, 2019. "Correcting outliers in GARCH models: a weighted forward approach," Statistical Papers, Springer, vol. 60(6), pages 1939-1970, December.
    20. Cunado, Juncal & Gomez Biscarri, Javier & Perez de Gracia, Fernando, 2006. "Changes in the dynamic behavior of emerging market volatility: Revisiting the effects of financial liberalization," Emerging Markets Review, Elsevier, vol. 7(3), pages 261-278, September.
    21. Alfred Wong & Jiayue Zhang, 2018. "Breakdown of covered interest parity: mystery or myth?," BIS Papers chapters, in: Bank for International Settlements (ed.), The price, real and financial effects of exchange rates, volume 96, pages 57-78, Bank for International Settlements.
    22. Lei Shi & Md. Mostafizur Rahman & Wen Gan & Jianhua Zhao, 2015. "Stepwise local influence in generalized autoregressive conditional heteroskedasticity models," Journal of Applied Statistics, Taylor & Francis Journals, vol. 42(2), pages 428-444, February.
    23. Fokianos, Konstantions & Fried, Roland, 2009. "Interventions in ingarch processes," Technical Reports 2009,11, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    24. L. Grossi & G. Morelli, 2006. "Robust volatility forecasts and model selection in financial time series," Economics Department Working Papers 2006-SE02, Department of Economics, Parma University (Italy).
    25. Charles, Amélie & Darné, Olivier & Pop, Adrian, 2015. "Risk and ethical investment: Empirical evidence from Dow Jones Islamic indexes," Research in International Business and Finance, Elsevier, vol. 35(C), pages 33-56.
    26. Amélie Charles, 2008. "Forecasting volatility with outliers in GARCH models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(7), pages 551-565.
    27. Alfred Wong & Jiayue Zhang, 2018. "Breakdown of covered interest parity: mystery or myth?," FIW Working Paper series 182, FIW.
    28. Jonathan Dark & Xibin Zhang & Nan Qu, 2010. "Influence diagnostics for multivariate GARCH processes," Journal of Time Series Analysis, Wiley Blackwell, vol. 31(4), pages 278-291, July.
    29. Juraj Valachy & Ev??en Ko?enda, 2003. "Exchange Rate Regimes and Volatility: Comparison of the Snake and Visegrad," William Davidson Institute Working Papers Series 2003-622, William Davidson Institute at the University of Michigan.
    30. Xiaowen Dai & Libin Jin & Anqi Shi & Lei Shi, 2016. "Outlier detection and accommodation in general spatial models," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 25(3), pages 453-475, August.
    31. Guanghui Cai & Zhimin Wu & Lei Peng, 2021. "Forecasting volatility with outliers in Realized GARCH models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(4), pages 667-685, July.
    32. Çevik, Emre & Çevik, Emrah İsmail & Dibooglu, Sel & Cergibozan, Raif & Bugan, Mehmet Fatih & Destek, Mehmet Akif, 2022. "Connectedness and risk spillovers between crude oil and clean energy stock markets," MPRA Paper 117558, University Library of Munich, Germany.
    33. Juncal Cuñado & Javier Gómez Biscarri & Fernando Perez de Gracia, 2006. "Changes in the Dynamic Behavior of Emerging Market Volatility: Revisiting the Effects of Financial L," Faculty Working Papers 01/06, School of Economics and Business Administration, University of Navarra.
    34. Konstantinos Fokianos & Roland Fried, 2010. "Interventions in INGARCH processes," Journal of Time Series Analysis, Wiley Blackwell, vol. 31(3), pages 210-225, May.
    35. Chalabi, Yohan / Y. & Wuertz, Diethelm, 2010. "Weighted trimmed likelihood estimator for GARCH models," MPRA Paper 26536, University Library of Munich, Germany.
    36. Min-Hsien Chiang & Ray Yeutien Chou & Li-Min Wang, 2016. "Outlier Detection in the Lognormal Logarithmic Conditional Autoregressive Range Model," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 78(1), pages 126-144, February.

  59. Vivien Guiraud & Michel Terraza & Olivier Darné, 2004. "Forecasts of the seasonal fractional integrated series," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 23(1), pages 1-17.

    Cited by:

    1. Laurent Ferrara & Dominique Guegan & Zhiping Lu, 2010. "Testing Fractional Order of Long Memory Processes: A Monte Carlo Study," PSE-Ecole d'économie de Paris (Postprint) hal-00486655, HAL.
    2. Laurent Ferrara & Dominique Guegan & Zhiping Lu, 2008. "Testing fractional order of long memory processes : a Monte Carlo study," Post-Print halshs-00259193, HAL.
    3. John Galbraith & Greg Tkacz, 2007. "How Far Can Forecasting Models Forecast? Forecast Content Horizons for Some Important Macroeconomic Variables," Staff Working Papers 07-1, Bank of Canada.
    4. Laurent Ferrara & Dominique Guegan, 2006. "Fractional seasonality: Models and Application to Economic Activity in the Euro Area," Post-Print halshs-00185370, HAL.

  60. Olivier Darné, 2004. "The effects of additive outliers on stationarity tests: a monte carlo study," Economics Bulletin, AccessEcon, vol. 3(16), pages 1-8.

    Cited by:

    1. P. S. Sephton, 2010. "Unit roots and purchasing power parity: another kick at the can," Applied Economics, Taylor & Francis Journals, vol. 42(27), pages 3439-3453.
    2. Katarzyna Rosiak-Lada, 2008. "Stylized Facts of Macroeconomics: the Polish Experience," Ekonomia journal, Faculty of Economic Sciences, University of Warsaw, vol. 20.
    3. Fiuza, Eduardo P.S. & Tito, Fabiana F.M., 2010. "Post-merger time series analysis: Iron ore mining," Resources Policy, Elsevier, vol. 35(3), pages 141-155, September.

  61. Darne, Olivier & Diebolt, Claude, 2004. "Unit roots and infrequent large shocks: new international evidence on output," Journal of Monetary Economics, Elsevier, vol. 51(7), pages 1449-1465, October.
    See citations under working paper version above.
  62. Darne, Olivier, 2004. "Seasonal cointegration for monthly data," Economics Letters, Elsevier, vol. 82(3), pages 349-356, March.

    Cited by:

    1. Akdi, Yilmaz & Berument, Hakan & Mümin Cilasun, Seyit, 2006. "The relationship between different price indices: Evidence from Turkey," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 360(2), pages 483-492.
    2. González-Rivera, Gloria & Rodríguez Caballero, Carlos Vladimir & Ruiz Ortega, Esther, 2023. "Modelling intervals of minimum/maximum temperatures in the Iberian Peninsula," DES - Working Papers. Statistics and Econometrics. WS 37968, Universidad Carlos III de Madrid. Departamento de Estadística.
    3. Méndez Parra, Maximiliano, 2015. "Futures prices, trade and domestic supply of agricultural commodities," Economics PhD Theses 0115, Department of Economics, University of Sussex Business School.
    4. Sheng-Hung Chen & Song-Zan Chiou-Wei & Zhen Zhu, 2022. "Stochastic seasonality in commodity prices: the case of US natural gas," Empirical Economics, Springer, vol. 62(5), pages 2263-2284, May.

  63. Olivier Darné & Claude Diebolt, 2002. "A Note on Seasonal Unit Root Tests," Quality & Quantity: International Journal of Methodology, Springer, vol. 36(3), pages 305-310, August.

    Cited by:

    1. Massimiliano Giacalone & Raffaele Mattera & Eugenia Nissi, 2020. "Economic indicators forecasting in presence of seasonal patterns: time series revision and prediction accuracy," Quality & Quantity: International Journal of Methodology, Springer, vol. 54(1), pages 67-84, February.

Chapters

  1. Olivier Darné & Claude Diebolt, 2005. "Non-stationarity Tests in Macroeconomic Time Series," Springer Books, in: Claude Diebolt & Catherine Kyrtsou (ed.), New Trends in Macroeconomics, pages 173-194, Springer.
    See citations under working paper version above.Sorry, no citations of chapters recorded.
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