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Amelie CHARLES

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.

Working papers

  1. 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.

  2. Amélie Charles & Olivier Darné, 2014. "Volatility persistence in crude oil markets," Post-Print hal-00940312, 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.

  3. Amélie Charles & Olivier Darné & Laurent Ferrara, 2014. "Does the Great Recession imply the end of the Great Moderation? International evidence," EconomiX Working Papers 2014-21, University of Paris Nanterre, EconomiX.

    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.

  4. Amélie Charles & Etienne Redor, 2014. "Women are from Venus, Men are from Mars: But Do the Financial Markets Know It?," Post-Print hal-00977037, HAL.

    Cited by:

    1. Jidong Zhang & Jing Han & Meiqun Yin, 2018. "A female style in corporate social responsibility? Evidence from charitable donations," International Journal of Disclosure and Governance, Palgrave Macmillan, vol. 15(3), pages 185-196, August.

  5. 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).

    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).

  6. 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.

  7. 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).

  8. 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.

  9. 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.

  10. Amélie Charles, 2010. "The day-of-the week effects on the volatility: The role of the asymmetry," Post-Print hal-00771136, HAL.

    Cited by:

    1. Mohamed El Hedi Arouri & Christophe Rault & Robert Sova & Anamaria Sova, 2013. "Market Structure and the Cost of Capital," CESifo Working Paper Series 4097, CESifo.
    2. Barunik, Jozef & Krehlik, Tomas & Vacha, Lukas, 2016. "Modeling and forecasting exchange rate volatility in time-frequency domain," European Journal of Operational Research, Elsevier, vol. 251(1), pages 329-340.
    3. Abdelhakim Aknouche & Bader Almohaimeed & Stefanos Dimitrakopoulos, 2022. "Periodic autoregressive conditional duration," Journal of Time Series Analysis, Wiley Blackwell, vol. 43(1), pages 5-29, January.
    4. Degiannakis, Stavros & Filis, George & Hassani, Hossein, 2015. "Forecasting implied volatility indices worldwide: A new approach," MPRA Paper 72084, University Library of Munich, Germany.
    5. Floros, Christos & Salvador, Enrique, 2014. "Calendar anomalies in cash and stock index futures: International evidence," Economic Modelling, Elsevier, vol. 37(C), pages 216-223.
    6. Bentes, Sonia R., 2018. "Is stock market volatility asymmetric? A multi-period analysis for five countries," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 499(C), pages 258-265.
    7. Urquhart, Andrew & Hudson, Robert, 2016. "Investor sentiment and local bias in extreme circumstances: The case of the Blitz," Research in International Business and Finance, Elsevier, vol. 36(C), pages 340-350.
    8. Mohamed El Hedi Arouri & Christophe Rault & Ana Maria Sova & Robert Sova & Frédéric Teulon, 2013. "Market Structure and the Cost of Capital," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-00798048, HAL.
    9. Guillen, Jordi & Maynou, Francesc, 2014. "Importance of temporal and spatial factors in the ex-vessel price formation for red shrimp and management implications," Marine Policy, Elsevier, vol. 47(C), pages 66-70.
    10. Juan Benjamín Duarte Duarte & Juan Manuel Mascare?nas Pérez-Iñigo, 2014. "Comprobación de la eficiencia débil en los principales mercados financieros latinoamericanos," Estudios Gerenciales, Universidad Icesi, November.
    11. 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.
    12. Chowdhury, Anup & Uddin, Moshfique & Anderson, Keith, 2022. "Trading behaviour and market sentiment: Firm-level evidence from an emerging Islamic market," Global Finance Journal, Elsevier, vol. 53(C).
    13. Wang, Xinya & Liu, Huifang & Huang, Shupei, 2019. "Identification of the daily seasonality in gold returns and volatilities: Evidence from Shanghai and London," Resources Policy, Elsevier, vol. 61(C), pages 522-531.
    14. Liu, Zhicao & Ye, Yong & Ma, Feng & Liu, Jing, 2017. "Can economic policy uncertainty help to forecast the volatility: A multifractal perspective," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 482(C), pages 181-188.
    15. Ma, Donglian & Tanizaki, Hisashi, 2019. "The day-of-the-week effect on Bitcoin return and volatility," Research in International Business and Finance, Elsevier, vol. 49(C), pages 127-136.
    16. Qadan, Mahmoud & Aharon, David Y. & Cohen, Gil, 2020. "Everybody likes shopping, including the US capital market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 551(C).
    17. Aknouche, Abdelhakim & Al-Eid, Eid & Demouche, Nacer, 2016. "Generalized quasi-maximum likelihood inference for periodic conditionally heteroskedastic models," MPRA Paper 75770, University Library of Munich, Germany, revised 19 Dec 2016.
    18. Qadan, Mahmoud & Kliger, Doron, 2016. "The short trading day anomaly," Journal of Empirical Finance, Elsevier, vol. 38(PA), pages 62-80.
    19. Farag, Hisham, 2013. "Price limit bands, asymmetric volatility and stock market anomalies: Evidence from emerging markets," Global Finance Journal, Elsevier, vol. 24(1), pages 85-97.
    20. Leandro Maciel & Fernando Gomide & Rosangela Ballini, 2014. "An Evolving Fuzzy-Garch Approach Forfinancial Volatility Modeling And Forecasting," Anais do XL Encontro Nacional de Economia [Proceedings of the 40th Brazilian Economics Meeting] 138, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics].
    21. Shekar Bose & Hafizur Rahman, 2022. "Are News Effects Necessarily Asymmetric? Evidence from Bangladesh Stock Market," SAGE Open, , vol. 12(4), pages 21582440221, October.
    22. Juan Benjamín Duarte Duarte & Juan Manuel Mascareñas Pérez-Iñigo, 2014. "¿Han sido los mercados bursátiles eficientes informacionalmente?," Apuntes del Cenes, Universidad Pedagógica y Tecnológica de Colombia, June.
    23. Degiannakis, Stavros & Filis, George & Hassani, Hossein, 2018. "Forecasting global stock market implied volatility indices," Journal of Empirical Finance, Elsevier, vol. 46(C), pages 111-129.
    24. Aknouche, Abdelhakim & Almohaimeed, Bader & Dimitrakopoulos, Stefanos, 2020. "Periodic autoregressive conditional duration," MPRA Paper 101696, University Library of Munich, Germany, revised 08 Jul 2020.
    25. Ndako, Umar Bida, 2013. "The Day of the Week effect on stock market returns and volatility: Evidence from Nigeria and South Africa," MPRA Paper 48076, University Library of Munich, Germany.
    26. Ali CELÝK, 2021. "Volatility of BIST 100 Returns After 2020, Calendar Anomalies and COVID-19 Effect," Journal of BRSA Banking and Financial Markets, Banking Regulation and Supervision Agency, vol. 15(1), pages 61-81.
    27. Bentes, Sonia R., 2016. "Long memory volatility of gold price returns: How strong is the evidence from distinct economic cycles?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 443(C), pages 149-160.
    28. Zhang, Bing & Zhou, Yun, 2015. "Asymmetries in stock marketsAuthor-Name: Wang, Peijie," European Journal of Operational Research, Elsevier, vol. 241(3), pages 749-762.
    29. Hudson, Robert & Urquhart, Andrew, 2022. "Naval disasters, world war two and the British stock market," Research in International Business and Finance, Elsevier, vol. 59(C).
    30. Krzysztof DRACHAL, 2017. "Volatility Clustering, Leverage Effects and Risk-Return Tradeoff in the Selected Stock Markets in the CEE Countries," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(3), pages 37-53, September.
    31. Osabuohien-Irabor Osarumwense, 2015. "Day-of-the-week effect in the Nigerian Stock Market Returns and Volatility: Does the Distributional Assumptions Influence Disappearance?," European Financial and Accounting Journal, Prague University of Economics and Business, vol. 2015(4), pages 33-44.
    32. Abdelhakim Aknouche & Eid Al-Eid & Nacer Demouche, 2018. "Generalized quasi-maximum likelihood inference for periodic conditionally heteroskedastic models," Statistical Inference for Stochastic Processes, Springer, vol. 21(3), pages 485-511, October.

  11. 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).

  12. 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.

  13. 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).
    45. Ben Ammar, Imen & Hellara, Slaheddine, 2021. "Intraday interactions between high-frequency trading and price efficiency," Finance Research Letters, Elsevier, vol. 41(C).
    46. Jean-Marie Dufour & Lynda Khalaf & Marcel Voia, 2013. "Finite-sample resampling-based combined hypothesis tests, with applications to serial correlation and predictability," CIRANO Working Papers 2013s-40, CIRANO.
    47. 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.
    48. Ammy-Driss, Ayoub & Garcin, Matthieu, 2023. "Efficiency of the financial markets during the COVID-19 crisis: Time-varying parameters of fractional stable dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 609(C).
    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.
    50. Amelie Charles & Olivier Darne, 2009. "Testing for Random Walk Behavior in Euro Exchange Rates," Economie Internationale, CEPII research center, issue 119, pages 25-45.
    51. Neil Kellard & Denise Osborn & Jerry Coakley & John C. Nankervis & Periklis Kougoulis & Jerry Coakley, 2015. "Generalized Variance-Ratio Tests in the Presence of Statistical Dependence," Journal of Time Series Analysis, Wiley Blackwell, vol. 36(5), pages 687-705, September.
    52. Joao Sousa Andrade & Irina Syssoyeva-Masson, 2016. "Investigating the presence of long memory in debt series and its relation with growth," EcoMod2016 9627, EcoMod.
    53. 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.
    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.
    55. Constandina Koki & Stefanos Leonardos & Georgios Piliouras, 2019. "A Peek into the Unobservable: Hidden States and Bayesian Inference for the Bitcoin and Ether Price Series," Papers 1909.10957, arXiv.org, revised Jul 2021.
    56. Stéphane Goutte & David Guerreiro & Bilel Sanhaji & Sophie Saglio & Julien Chevallier, 2019. "International Financial Markets," Post-Print halshs-02183053, HAL.

  14. 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.

  15. 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.

  16. 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.

  17. 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.

  18. 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.

Articles

  1. 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.
  2. Amelie Charles & Etienne Redor, 2014. "Women are from Venus, Men are from Mars: But Do the Financial Markets Know It?," Economics Bulletin, AccessEcon, vol. 34(1), pages 589-604.
    See citations under working paper version above.
  3. 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.
  4. 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.

    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).

  5. Charles, Amélie & Darné, Olivier & Fouilloux, Jessica, 2013. "Market efficiency in the European carbon markets," Energy Policy, Elsevier, vol. 60(C), pages 785-792.

    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.

  6. 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.

    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.

  7. 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.

    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.

  8. 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.
  9. 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.
  10. 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.
  11. 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.
  12. 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.

    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.

  13. Am�lie Charles, 2010. "Does the day-of-the-week effect on volatility improve the volatility forecasts?," Applied Economics Letters, Taylor & Francis Journals, vol. 17(3), pages 257-262, February.

    Cited by:

    1. Gonzalez-Perez, Maria T. & Guerrero, David E., 2013. "Day-of-the-week effect on the VIX. A parsimonious representation," The North American Journal of Economics and Finance, Elsevier, vol. 25(C), pages 243-260.
    2. Bentes, Sonia R., 2018. "Is stock market volatility asymmetric? A multi-period analysis for five countries," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 499(C), pages 258-265.
    3. Carlos Francisco Alves & Duarte André de Castro Reis, 2018. "Evidence of Idiosyncratic Seasonality in ETFs Performance," FEP Working Papers 603, Universidade do Porto, Faculdade de Economia do Porto.
    4. Kristjanpoller Rodríguez Werner, 2013. "Anomalías en la autocorrelación de rendimientos y la importancia de los periodos de no transacción en mercados latinoamericanos," Contaduría y Administración, Accounting and Management, vol. 58(1), pages 37-62, enero-mar.
    5. Osabuohien-Irabor Osarumwense, 2015. "Day-of-the-week effect in the Nigerian Stock Market Returns and Volatility: Does the Distributional Assumptions Influence Disappearance?," European Financial and Accounting Journal, Prague University of Economics and Business, vol. 2015(4), pages 33-44.
    6. Wamg, Jianxin, 2011. "Forecasting Volatility in Asian Stock Markets: Contributions of Local, Regional, and Global Factors," Asian Development Review, Asian Development Bank, vol. 28(2), pages 32-57.

  14. Charles, Amélie, 2010. "The day-of-the-week effects on the volatility: The role of the asymmetry," European Journal of Operational Research, Elsevier, vol. 202(1), pages 143-152, April.
    See citations under working paper version above.
  15. 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.
  16. Amelie Charles & Olivier Darne, 2009. "Testing for Random Walk Behavior in Euro Exchange Rates," Economie Internationale, CEPII research center, issue 119, pages 25-45.

    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.

  17. 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.
  18. 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.
  19. Amélie Charles, 2008. "Forecasting volatility with outliers in GARCH models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(7), pages 551-565.

    Cited by:

    1. Amélie Charles & Olivier Darné, 2012. "Volatility Persistence in Crude Oil Markets," Working Papers hal-00719387, HAL.
    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. 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.
    4. 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.
    5. 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.
    6. 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.
    7. González-Sánchez, Mariano, 2021. "Is there a relationship between the time scaling property of asset returns and the outliers? Evidence from international financial markets," Finance Research Letters, Elsevier, vol. 38(C).
    8. 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).
    9. Grané, Aurea & Veiga, Helena, 2010. "Wavelet-based detection of outliers in financial time series," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2580-2593, November.
    10. Alanya-Beltran, Willy, 2022. "Unit roots in lower-bounded series with outliers," Economic Modelling, Elsevier, vol. 115(C).
    11. Charles, Amélie & Darné, Olivier, 2017. "Forecasting crude-oil market volatility: Further evidence with jumps," Energy Economics, Elsevier, vol. 67(C), pages 508-519.
    12. Lisa Crosato & Luigi Grossi, 2019. "Correcting outliers in GARCH models: a weighted forward approach," Statistical Papers, Springer, vol. 60(6), pages 1939-1970, December.
    13. 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.
    14. Vasiliki Chatzikonstanti & Michail Karoglou, 2022. "Can black swans be tamed with a flexible mean‐variance specification?," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(3), pages 3202-3227, July.
    15. Manh Ha Nguyen & Olivier Darné, 2018. "Forecasting and risk management in the Vietnam Stock Exchange," Working Papers halshs-01679456, HAL.
    16. 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.
    17. You‐How Go & Jia‐Jun Teo & Kam Fong Chan, 2023. "The effectiveness of crude oil futures hedging during infectious disease outbreaks in the 21st century," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 43(11), pages 1559-1575, November.
    18. Alex Huang, 2011. "Volatility Modeling by Asymmetrical Quadratic Effect with Diminishing Marginal Impact," Computational Economics, Springer;Society for Computational Economics, vol. 37(3), pages 301-330, March.
    19. 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.

  20. 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.
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    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.

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