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Jae Hoon Kim

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, 2017. "International Stock Return Predictability: Evidence from New Statistical Tests," Post-Print hal-01626101, HAL.

    Cited by:

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

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

    Cited by:

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

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

    Cited by:

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

  4. Kim, Jae, 2016. "Stock Returns and Investors’ Mood: Good Day Sunshine or Spurious Correlation?," MPRA Paper 70692, University Library of Munich, Germany.

    Cited by:

    1. Margaret Samahita & Håkan J Holm, 2020. "Mining for Mood Effect in the Field," Working Papers 202002, School of Economics, University College Dublin.
    2. Jae H. Kim & Kamran Ahmed & Philip Inyeob Ji, 2018. "Significance Testing in Accounting Research: A Critical Evaluation Based on Evidence," Abacus, Accounting Foundation, University of Sydney, vol. 54(4), pages 524-546, December.
    3. Jae H. Kim & Andrew P. Robinson, 2019. "Interval-Based Hypothesis Testing and Its Applications to Economics and Finance," Econometrics, MDPI, vol. 7(2), pages 1-22, May.
    4. Polyzos, Stathis & Samitas, Aristeidis & Katsaiti, Marina-Selini, 2020. "Who is unhappy for Brexit? A machine-learning, agent-based study on financial instability," International Review of Financial Analysis, Elsevier, vol. 72(C).
    5. Filiz, Ibrahim & Nahmer, Thomas & Spiwoks, Markus, 2019. "Herd behavior and mood: An experimental study on the forecasting of share prices," Journal of Behavioral and Experimental Finance, Elsevier, vol. 24(C).
    6. Wang, Hanjie & Feil, Jan-Henning & Yu, Xiaohua, 2021. "Disagreement on sunspots and soybeans futures price," Economic Modelling, Elsevier, vol. 95(C), pages 385-393.
    7. Liu, Huajin & Zhang, Wei & Zhang, Xiaotao & Liu, Jia, 2021. "Temperature and trading behaviours," International Review of Financial Analysis, Elsevier, vol. 78(C).
    8. Lucian Liviu ALBU & Radu LUPU & Adrian Cantemir CĂLIN & Iulia LUPU, 2019. "Nonlinear Modeling of Financial Stability Using Default Probabilities from the Capital Market," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(1), pages 19-37, March.
    9. Ngoc Bao Vuong & Yoshihisa Suzuki, 2022. "The Moderating Effect of Market-Specific Factors on the Return Predictability of Investor Sentiment," SAGE Open, , vol. 12(3), pages 21582440221, July.
    10. Zhou Tianbao & Li Xinghao & Zhao Junguang, 2022. "Solar Term Anomaly in China Stock Market: Evidence from Shanghai Index," Papers 2203.12603, arXiv.org, revised Feb 2023.

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

    Cited by:

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

  6. Kim, Jae, 2015. "How to Choose the Level of Significance: A Pedagogical Note," MPRA Paper 66373, University Library of Munich, Germany.

    Cited by:

    1. Sara Rellstab & Pieter Bakx & Pilar (P.) Garcia-Gomez & Eddy (E.K.A.) van Doorslaer, 2018. "The kids are alright - labour market effects of unexpected parental hospitalisations in the Netherlands," Tinbergen Institute Discussion Papers 18-049/V, Tinbergen Institute.
    2. Nicoleta Dospinescu & Octavian Dospinescu & Maria Tatarusanu, 2020. "Analysis of the Influence Factors on the Reputation of Food-Delivery Companies: Evidence from Romania," Sustainability, MDPI, vol. 12(10), pages 1-13, May.
    3. Samuel Kwame Atta & Tinashe Tholana, 2022. "Cost competitive analysis of large-scale gold mines in Ghana from 2007 to 2016," Mineral Economics, Springer;Raw Materials Group (RMG);Luleå University of Technology, vol. 35(1), pages 53-65, March.
    4. Zhuquan Wang & Memon Rafait Mahmood & Hafeez Ullah & Imran Hanif & Qaiser Abbas & Muhammad Mohsin, 2020. "Multidimensional Perspective of Firms’ IT Capability Between Digital Business Strategy and Firms’ Efficiency: A Case of Chinese SMEs," SAGE Open, , vol. 10(4), pages 21582440209, December.

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

    Cited by:

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

  8. 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.

  9. Kim, Jae & Doucouliagos, Hristos & Stanley, T. D., 2014. "Market efficiency in Asian and Australasian stock markets: a fresh look at the evidence," Working Papers eco_2014_9, Deakin University, Department of Economics.

    Cited by:

    1. OlaOluwa S. Yaya & Oluwasegun B. Adekoya & Xuan Vinh Vo & Mamdouh Abdulaziz Saleh Al‐Faryan, 2024. "Stock Market Efficiency in Asia: Evidence from the Narayan–Liu–Westerlund's GARCH‐based unit root test," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 29(1), pages 91-101, January.
    2. Białkowski, Jędrzej & Bohl, Martin T. & Perera, Devmali, 2023. "Commodity futures hedge ratios: A meta-analysis," Journal of Commodity Markets, Elsevier, vol. 30(C).
    3. Yaya, OlaOluwa S. & Vo, Xuan Vinh & Adekoya, Oluwasegun B., 2021. "Market Efficiency of Asian Stocks: Evidence based on Narayan-Liu-Westerlund GARCH-based Unit root test," MPRA Paper 109828, University Library of Munich, Germany.
    4. Geyer-Klingeberg, Jerome & Hang, Markus & Rathgeber, Andreas W., 2019. "What drives financial hedging? A meta-regression analysis of corporate hedging determinants," International Review of Financial Analysis, Elsevier, vol. 61(C), pages 203-221.
    5. Stefan Hirsch, 2018. "Successful In The Long Run: A Meta†Regression Analysis Of Persistent Firm Profits," Journal of Economic Surveys, Wiley Blackwell, vol. 32(1), pages 23-49, February.
    6. John P. A. Ioannidis & T. D. Stanley & Hristos Doucouliagos, 2017. "The Power of Bias in Economics Research," Economic Journal, Royal Economic Society, vol. 127(605), pages 236-265, October.
    7. Jędrzej Białkowski & Martin T. Bohl & Devmali Perera, 2022. "Commodity Futures Hedge Ratios: A Meta-Analysis," Working Papers in Economics 22/12, University of Canterbury, Department of Economics and Finance.

  10. 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.

  11. 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.

  12. Jae H Kim & Iain Fraser & Rob J. Hyndman, 2010. "Improved Interval Estimation of Long Run Response from a Dynamic Linear Model: A Highest Density Region Approach," Working Papers 2010.06, School of Economics, La Trobe University.

    Cited by:

    1. Ben O’Neill, 2022. "Smallest covering regions and highest density regions for discrete distributions," Computational Statistics, Springer, vol. 37(3), pages 1229-1254, July.
    2. A. Talha Yalta, 2013. "The Dynamics of Road Energy Demand and Illegal Fuel Activity in Turkey: A Rolling Window Analysis," Working Papers 1304, TOBB University of Economics and Technology, Department of Economics, revised Jul 2013.
    3. Yalta, A. Talha & Yalta, A. Yasemin, 2016. "The dynamics of fuel demand and illegal fuel activity in Turkey," Energy Economics, Elsevier, vol. 54(C), pages 144-158.
    4. Galip Altinay & A. Talha Yalta, 2016. "Estimating the evolution of elasticities of natural gas demand: the case of Istanbul, Turkey," Empirical Economics, Springer, vol. 51(1), pages 201-220, August.
    5. Mario Arturo Ruiz Estrada & Evangelos Koutronas & Ross Knippenberg, 2016. "The Mega Distributed Lag Model," Contemporary Economics, University of Economics and Human Sciences in Warsaw., vol. 10(2), June.

  13. Abul Shamsuddin & Jae H Kim, 2009. "Short-Horizon Return Predictability in International Equity Markets," Working Papers 2009.01, 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. Amélie Charles & Olivier Darné & Jae H. Kim & Etienne Redor, 2016. "Stock Exchange Mergers and Market," Post-Print hal-01238707, HAL.
    3. Rahman, Md. Lutfur & Lee, Doowon & Shamsuddin, Abul, 2017. "Time-varying return predictability in South Asian equity markets," International Review of Economics & Finance, Elsevier, vol. 48(C), pages 179-200.
    4. Khurshid M. Kiani, 2016. "On Modelling and Forecasting Predictable Components in European Stock Markets," Computational Economics, Springer;Society for Computational Economics, vol. 48(3), pages 487-502, October.
    5. Yaya, OlaOluwa S. & Vo, Xuan Vinh & Adekoya, Oluwasegun B., 2021. "Market Efficiency of Asian Stocks: Evidence based on Narayan-Liu-Westerlund GARCH-based Unit root test," MPRA Paper 109828, University Library of Munich, Germany.
    6. Quynh Trang Phan & Poomthan Rangkakulnuwat, 2022. "How price informativeness affects the sensitivity of investment-to-stock price in Vietnamese listed firms," Afro-Asian Journal of Finance and Accounting, Inderscience Enterprises Ltd, vol. 12(1), pages 28-61.
    7. Park, Jin Suk & Newaz, Mohammad Khaleq, 2021. "Liquidity and short-run predictability: Evidence from international stock markets," Global Finance Journal, Elsevier, vol. 50(C).
    8. Amélie Charles & Olivier Darné & Jae H. Kim & Etienne Redor, 2014. "Stock Exchange Mergers and Market Efficiency," Working Papers hal-00940105, HAL.
    9. 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.
    10. Stéphane Goutte & David Guerreiro & Bilel Sanhaji & Sophie Saglio & Julien Chevallier, 2019. "International Financial Markets," Post-Print halshs-02183053, HAL.

  14. Jae H. Kim & Haiyang Song & Kevin Wong & George Athanasopoulos & Shen Liu, 2008. "Beyond point forecasting: evaluation of alternative prediction intervals for tourist arrivals," Monash Econometrics and Business Statistics Working Papers 11/08, Monash University, Department of Econometrics and Business Statistics, revised Oct 2009.

    Cited by:

    1. Cem Işık & Ercan Sirakaya-Turk & Serdar Ongan, 2020. "Testing the efficacy of the economic policy uncertainty index on tourism demand in USMCA: Theory and evidence," Tourism Economics, , vol. 26(8), pages 1344-1357, December.
    2. Peng, Bo & Song, Haiyan & Crouch, Geoffrey I., 2014. "A meta-analysis of international tourism demand forecasting and implications for practice," Tourism Management, Elsevier, vol. 45(C), pages 181-193.
    3. Hassani, Hossein & Silva, Emmanuel Sirimal & Antonakakis, Nikolaos & Filis, George & Gupta, Rangan, 2017. "Forecasting accuracy evaluation of tourist arrivals," Annals of Tourism Research, Elsevier, vol. 63(C), pages 112-127.
    4. George Athanasopoulos & Rob J Hyndman & Haiyan Song & Doris C Wu, 2008. "The tourism forecasting competition," Monash Econometrics and Business Statistics Working Papers 10/08, Monash University, Department of Econometrics and Business Statistics, revised Oct 2009.
    5. Liu, Shen & Maharaj, Elizabeth Ann & Inder, Brett, 2014. "Polarization of forecast densities: A new approach to time series classification," Computational Statistics & Data Analysis, Elsevier, vol. 70(C), pages 345-361.
    6. Song, Haiyan & Wen, Long & Liu, Chang, 2019. "Density tourism demand forecasting revisited," Annals of Tourism Research, Elsevier, vol. 75(C), pages 379-392.
    7. Xiaofeng Lv & Deyun Zhou & Yongchuan Tang & Ling Ma, 2018. "An Improved Test Selection Optimization Model Based on Fault Ambiguity Group Isolation and Chaotic Discrete PSO," Complexity, Hindawi, vol. 2018, pages 1-10, January.
    8. Andrea Saayman & Ilsé Botha, 2017. "Non-linear models for tourism demand forecasting," Tourism Economics, , vol. 23(3), pages 594-613, May.
    9. Eden Xiaoying Jiao & Jason Li Chen, 2019. "Tourism forecasting: A review of methodological developments over the last decade," Tourism Economics, , vol. 25(3), pages 469-492, May.
    10. Wai Kit Tsang & Dries F. Benoit, 2020. "Gaussian processes for daily demand prediction in tourism planning," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(3), pages 551-568, April.
    11. Yang, Dongchuan & Guo, Ju-e & Sun, Shaolong & Han, Jing & Wang, Shouyang, 2022. "An interval decomposition-ensemble approach with data-characteristic-driven reconstruction for short-term load forecasting," Applied Energy, Elsevier, vol. 306(PA).
    12. Ulrich Gunter, 2021. "Improving Hotel Room Demand Forecasts for Vienna across Hotel Classes and Forecast Horizons: Single Models and Combination Techniques Based on Encompassing Tests," Forecasting, MDPI, vol. 3(4), pages 1-36, November.
    13. Jakob Heins & Jan Schoenfelder & Steffen Heider & Axel R. Heller & Jens O. Brunner, 2022. "A Scalable Forecasting Framework to Predict COVID-19 Hospital Bed Occupancy," Interfaces, INFORMS, vol. 52(6), pages 508-523, November.
    14. Liu, Shen & Maharaj, Elizabeth Ann, 2013. "A hypothesis test using bias-adjusted AR estimators for classifying time series in small samples," Computational Statistics & Data Analysis, Elsevier, vol. 60(C), pages 32-49.
    15. Jun, Wang & Yuyan, Luo & Lingyu, Tang & Peng, Ge, 2018. "Modeling a combined forecast algorithm based on sequence patterns and near characteristics: An application for tourism demand forecasting," Chaos, Solitons & Fractals, Elsevier, vol. 108(C), pages 136-147.
    16. Hassani, Hossein & Webster, Allan & Silva, Emmanuel Sirimal & Heravi, Saeed, 2015. "Forecasting U.S. Tourist arrivals using optimal Singular Spectrum Analysis," Tourism Management, Elsevier, vol. 46(C), pages 322-335.
    17. Li, Gang & Wu, Doris Chenguang & Zhou, Menglin & Liu, Anyu, 2019. "The combination of interval forecasts in tourism," Annals of Tourism Research, Elsevier, vol. 75(C), pages 363-378.

  15. Jayasuriya, Sisira & Kim, Jae H. & Kumar, Parmod, 2007. "International and Internal Market Integration in Indian agriculture: A study of the Indian Rice Market," 106th Seminar, October 25-27, 2007, Montpellier, France 7935, European Association of Agricultural Economists.

    Cited by:

    1. Baylis, Kathy & Mallory, Mindy & Songsermsawas, Tisorn, 2015. "Effects of credit and market access on farm gate prices in India," 2015 AAEA & WAEA Joint Annual Meeting, July 26-28, San Francisco, California 205434, Agricultural and Applied Economics Association.
    2. Bathla, Seema & Srinivasulu, R., 2011. "Price Transmission and Asymmetry: An Empirical Analysis of Indian Groundnut Seed and Oil Markets," Indian Journal of Agricultural Economics, Indian Society of Agricultural Economics, vol. 66(4), pages 1-16.
    3. Hwa-Taek Lee & Gawon Yoon, 2013. "Does purchasing power parity hold sometimes? Regime switching in real exchange rates," Applied Economics, Taylor & Francis Journals, vol. 45(16), pages 2279-2294, June.
    4. Beag, F.A. & Singla, N., 2014. "Cointegration, Causality and Impulse Response Analysis in Major Apple Markets of India," Agricultural Economics Research Review, Agricultural Economics Research Association (India), vol. 27(2).

  16. Jae Kim & Param Silvapulle & Rob J. Hyndman, 2006. "Half-Life Estimation based on the Bias-Corrected Bootstrap: A Highest Density Region Approach," Monash Econometrics and Business Statistics Working Papers 11/06, Monash University, Department of Econometrics and Business Statistics.

    Cited by:

    1. Philip Inyeob Ji, 2013. "Do country-specific shocks matter? Evidence from Australia and high income countries," Applied Economics, Taylor & Francis Journals, vol. 45(6), pages 729-739, February.
    2. Kim, Jae H. & Fraser, Iain & Hyndman, Rob J., 2011. "Improved interval estimation of long run response from a dynamic linear model: A highest density region approach," Computational Statistics & Data Analysis, Elsevier, vol. 55(8), pages 2477-2489, August.
    3. Park, Yung Chul & Park, Hail, 2014. "Stock Market Co-Movement and Exchange Rate Flexibility: Experience of the Republic of Korea," ADBI Working Papers 479, Asian Development Bank Institute.
    4. Georgios Loukopoulos & Dimitrios Antonopoulos, 2015. "Purchasing Power Parity: A Unit Root, Cointegration and VAR Analysis in Emerging and Advanced Countries," Business and Economic Research, Macrothink Institute, vol. 5(1), pages 262-279, June.
    5. Qian Chen & David E. Giles, 2007. "A Saddlepoint Approximation to the Distribution of the Half-Life Estimator in an Autoregressive Model: New Insights Into the PPP Puzzle," Econometrics Working Papers 0703, Department of Economics, University of Victoria.
    6. Thabo M. Mokoena & Gupta, R. & Van Eyden, R., 2009. "Half-Life Deviations from PPP in the South African Development Community (SADC)," Applied Econometrics and International Development, Euro-American Association of Economic Development, vol. 9(1).
    7. Soon, Siew-Voon & Baharumshah, Ahmad Zubaidi & Mohamad Shariff, Nurul Sima, 2017. "The persistence in real interest rates: Does it solve the intertemporal consumption behavior puzzle?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 50(C), pages 36-51.
    8. Jayasuriya, Sisira & Kim, Jae H. & Kumar, Parmod, 2007. "International and Internal Market Integration in Indian agriculture: A study of the Indian Rice Market," 106th Seminar, October 25-27, 2007, Montpellier, France 7935, European Association of Agricultural Economists.
    9. Kim, Jae H. & Ji, Philip Inyeob, 2011. "Mean-reversion in international real interest rates," Economic Modelling, Elsevier, vol. 28(4), pages 1959-1966, July.
    10. L. Spierdijk & J.A. Bikker, 2012. "Mean Reversion in Stock Prices: Implications for Long-Term Investors," Working Papers 12-07, Utrecht School of Economics.

  17. Clements, Michael P. & Galvão, Ana Beatriz & Kim, Jae H., 2006. "Quantile Forecasts of Daily Exchange Rate Returns from Forecasts of Realized Volatility," The Warwick Economics Research Paper Series (TWERPS) 777, University of Warwick, Department of Economics.

    Cited by:

    1. Christophe Chorro & Florian Ielpo & Benoît Sévi, 2017. "The contribution of jumps to forecasting the density of returns," Post-Print halshs-01442618, HAL.
    2. Christophe Chorro & Florian Ielpo & Benoît Sévi, 2020. "The contribution of intraday jumps to forecasting the density of returns," Post-Print halshs-02505861, HAL.
    3. Makoto Takahashi & Toshiaki Watanabe & Yasuhiro Omori, 2014. "Volatility and Quantile Forecasts by Realized Stochastic Volatility Models with Generalized Hyperbolic Distribution," CIRJE F-Series CIRJE-F-949, CIRJE, Faculty of Economics, University of Tokyo.
    4. Filip Žikeš & Jozef Baruník, 2016. "Semi-parametric Conditional Quantile Models for Financial Returns and Realized Volatility," Journal of Financial Econometrics, Oxford University Press, vol. 14(1), pages 185-226.
    5. Fuertes, Ana-Maria & Olmo, Jose, 2013. "Optimally harnessing inter-day and intra-day information for daily value-at-risk prediction," International Journal of Forecasting, Elsevier, vol. 29(1), pages 28-42.
    6. Lazar, Emese & Xue, Xiaohan, 2020. "Forecasting risk measures using intraday data in a generalized autoregressive score framework," International Journal of Forecasting, Elsevier, vol. 36(3), pages 1057-1072.
    7. Wen-Yuan Lin & I-Chun Tsai, 2016. "Asymmetric Fluctuating Behavior of China's Housing Prices," China & World Economy, Institute of World Economics and Politics, Chinese Academy of Social Sciences, vol. 24(2), pages 107-126, March.
    8. Phan, Dinh Hoang Bach & Sharma, Susan Sunila & Narayan, Paresh Kumar, 2016. "Intraday volatility interaction between the crude oil and equity markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 40(C), pages 1-13.
    9. Sévi, Benoît, 2014. "Forecasting the volatility of crude oil futures using intraday data," European Journal of Operational Research, Elsevier, vol. 235(3), pages 643-659.
    10. Marie Bessec & Othman Bouabdallah, 2015. "Forecasting GDP over the Business Cycle in a Multi-Frequency and Data-Rich Environment," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 77(3), pages 360-384, June.
    11. Barbara Będowska-Sójka, 2018. "Is intraday data useful for forecasting VaR? The evidence from EUR/PLN exchange rate," Risk Management, Palgrave Macmillan, vol. 20(4), pages 326-346, November.
    12. Douglas G. Santos & Flavio A. Ziegelmann, 2014. "Volatility Forecasting via MIDAS, HAR and their Combination: An Empirical Comparative Study for IBOVESPA," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 33(4), pages 284-299, July.
    13. Tim Bollerslev & Benjamin Hood & John Huss & Lasse Heje Pedersen, 2018. "Risk Everywhere: Modeling and Managing Volatility," The Review of Financial Studies, Society for Financial Studies, vol. 31(7), pages 2729-2773.
    14. Michael P. Clements & Ana Beatriz Galvão, 2009. "Forecasting US output growth using leading indicators: an appraisal using MIDAS models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 24(7), pages 1187-1206, November.
    15. Erik Kole & Thijs Markwat & Anne Opschoor & Dick van Dijk, 2017. "Forecasting Value-at-Risk under Temporal and Portfolio Aggregation," Journal of Financial Econometrics, Oxford University Press, vol. 15(4), pages 649-677.
    16. Jozef Barunik & Lubos Hanus, 2023. "Learning Probability Distributions of Day-Ahead Electricity Prices," Papers 2310.02867, arXiv.org, revised Oct 2023.
    17. Tae-Hwy Lee & Huiyu Huang, 2014. "Forecasting Value-at-Risk Using High Frequency Information," Working Papers 201409, University of California at Riverside, Department of Economics.
    18. Hwang, Eunju & Shin, Dong Wan, 2014. "Infinite-order, long-memory heterogeneous autoregressive models," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 339-358.
    19. Bjoern Schulte-Tillmann & Mawuli Segnon & Timo Wiedemann, 2023. "A comparison of high-frequency realized variance measures: Duration- vs. return-based approaches," CQE Working Papers 10523, Center for Quantitative Economics (CQE), University of Muenster.
    20. Frantisek Cech & Jozef Barunik, 2017. "Measurement of Common Risk Factors: A Panel Quantile Regression Model for Returns," Working Papers IES 2017/20, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Sep 2017.
    21. Ghysels, Eric & Ball, Ryan & Zhou, Huan, 2014. "Can we Automate Earnings Forecasts and Beat Analysts?," CEPR Discussion Papers 10186, C.E.P.R. Discussion Papers.
    22. Chorro, Christophe & Ielpo, Florian & Sévi, Benoît, 2020. "The contribution of intraday jumps to forecasting the density of returns," Journal of Economic Dynamics and Control, Elsevier, vol. 113(C).
    23. F. Lilla, 2017. "High Frequency vs. Daily Resolution: the Economic Value of Forecasting Volatility Models - 2nd ed," Working Papers wp1099, Dipartimento Scienze Economiche, Universita' di Bologna.
    24. Ubukata, Masato & Watanabe, Toshiaki, 2015. "Evaluating the performance of futures hedging using multivariate realized volatility," Journal of the Japanese and International Economies, Elsevier, vol. 38(C), pages 148-171.
    25. Masato Ubukata & Toshiaki Watanabe, 2014. "Pricing Nikkei 225 Options Using Realized Volatility," The Japanese Economic Review, Japanese Economic Association, vol. 65(4), pages 431-467, December.
    26. Gerlach, Richard & Wang, Chao, 2020. "Semi-parametric dynamic asymmetric Laplace models for tail risk forecasting, incorporating realized measures," International Journal of Forecasting, Elsevier, vol. 36(2), pages 489-506.
    27. Frantiv{s}ek v{C}ech & Jozef Barun'ik, 2018. "Panel quantile regressions for estimating and predicting the Value--at--Risk of commodities," Papers 1807.11823, arXiv.org.
    28. Seo, Sung Won & Kim, Jun Sik, 2015. "The information content of option-implied information for volatility forecasting with investor sentiment," Journal of Banking & Finance, Elsevier, vol. 50(C), pages 106-120.
    29. Alexander, Carol & Kaeck, Andreas & Sumawong, Anannit, 2019. "A parsimonious parametric model for generating margin requirements for futures," European Journal of Operational Research, Elsevier, vol. 273(1), pages 31-43.
    30. Fulvio Corsi & Davide Pirino & Roberto Renò, 2008. "Volatility forecasting: the jumps do matter," Department of Economics University of Siena 534, Department of Economics, University of Siena.
    31. Hallam, Mark & Olmo, Jose, 2014. "Forecasting daily return densities from intraday data: A multifractal approach," International Journal of Forecasting, Elsevier, vol. 30(4), pages 863-881.
    32. Hwang, Eunju & Shin, Dong Wan, 2015. "A CUSUMSQ test for structural breaks in error variance for a long memory heterogeneous autoregressive model," Statistics & Probability Letters, Elsevier, vol. 99(C), pages 167-176.
    33. Ghysels, Eric & Ball, Ryan, 2017. "Automated Earnings Forecasts:- Beat Analysts or Combine and Conquer?," CEPR Discussion Papers 12179, C.E.P.R. Discussion Papers.
    34. Christophe Chorro & Florian Ielpo & Benoît Sévi, 2017. "The contribution of jumps to forecasting the density of returns," Documents de travail du Centre d'Economie de la Sorbonne 17006, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    35. Li, Z. & Hurn, A.S. & Clements, A.E., 2017. "Forecasting quantiles of day-ahead electricity load," Energy Economics, Elsevier, vol. 67(C), pages 60-71.
    36. Aslanidis, Nektarios & Christiansen, Charlotte, 2014. "Quantiles of the realized stock–bond correlation and links to the macroeconomy," Journal of Empirical Finance, Elsevier, vol. 28(C), pages 321-331.
    37. Nieto, Maria Rosa & Ruiz, Esther, 2016. "Frontiers in VaR forecasting and backtesting," International Journal of Forecasting, Elsevier, vol. 32(2), pages 475-501.
    38. Ana-Maria Fuertes & Jose Olmo, 2016. "On Setting Day-Ahead Equity Trading Risk Limits: VaR Prediction at Market Close or Open?," JRFM, MDPI, vol. 9(3), pages 1-20, September.
    39. Christian T. Brownlees & Giampiero M. Gallo, 2010. "Comparison of Volatility Measures: a Risk Management Perspective," Journal of Financial Econometrics, Oxford University Press, vol. 8(1), pages 29-56, Winter.
    40. Christophe Chorro & Florian Ielpo & Benoît Sévi, 2020. "The contribution of intraday jumps to forecasting the density of returns," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-02505861, HAL.
    41. Louzis, Dimitrios P. & Xanthopoulos-Sisinis, Spyros & Refenes, Apostolos P., 2011. "Are realized volatility models good candidates for alternative Value at Risk prediction strategies?," MPRA Paper 30364, University Library of Munich, Germany.
    42. Mehmet Pinar & Thanasis Stengos & M. Ege Yazgan, 2018. "Quantile forecast combination using stochastic dominance," Empirical Economics, Springer, vol. 55(4), pages 1717-1755, December.
    43. Chortareas, Georgios & Jiang, Ying & Nankervis, John. C., 2011. "Forecasting exchange rate volatility using high-frequency data: Is the euro different?," International Journal of Forecasting, Elsevier, vol. 27(4), pages 1089-1107, October.
    44. Corsi, Fulvio & Fusari, Nicola & La Vecchia, Davide, 2013. "Realizing smiles: Options pricing with realized volatility," Journal of Financial Economics, Elsevier, vol. 107(2), pages 284-304.
    45. Bonato, Matteo & Caporin, Massimiliano & Ranaldo, Angelo, 2012. "Forecasting Realized (Co)Variances with a Bloc Structure Wishart Autoregressive Model," Working Papers on Finance 1211, University of St. Gallen, School of Finance.
    46. Louzis, Dimitrios P. & Xanthopoulos-Sisinis, Spyros & Refenes, Apostolos P., 2014. "Realized volatility models and alternative Value-at-Risk prediction strategies," Economic Modelling, Elsevier, vol. 40(C), pages 101-116.
    47. Anjum, Hassan & Malik, Farooq, 2020. "Forecasting risk in the US Dollar exchange rate under volatility shifts," The North American Journal of Economics and Finance, Elsevier, vol. 54(C).
    48. Santos, Douglas G. & Candido, Osvaldo & Tófoli, Paula V., 2022. "Forecasting risk measures using intraday and overnight information," The North American Journal of Economics and Finance, Elsevier, vol. 60(C).
    49. Bee, Marco & Dupuis, Debbie J. & Trapin, Luca, 2016. "Realizing the extremes: Estimation of tail-risk measures from a high-frequency perspective," Journal of Empirical Finance, Elsevier, vol. 36(C), pages 86-99.
    50. F. Lilla, 2016. "High Frequency vs. Daily Resolution: the Economic Value of Forecasting Volatility Models," Working Papers wp1084, Dipartimento Scienze Economiche, Universita' di Bologna.
    51. Andrada-Félix, Julián & Fernández-Rodríguez, Fernando & Fuertes, Ana-Maria, 2016. "Combining nearest neighbor predictions and model-based predictions of realized variance: Does it pay?," International Journal of Forecasting, Elsevier, vol. 32(3), pages 695-715.
    52. Lee, Chien-Chiang & Lee, Cheng-Feng & Lee, Chi-Chuan, 2014. "Asymmetric dynamics in REIT prices: Further evidence based on quantile regression analysis," Economic Modelling, Elsevier, vol. 42(C), pages 29-37.
    53. Yang, Cai & Gong, Xu & Zhang, Hongwei, 2019. "Volatility forecasting of crude oil futures: The role of investor sentiment and leverage effect," Resources Policy, Elsevier, vol. 61(C), pages 548-563.
    54. Jozef Barunik & Lubos Hanus, 2022. "Learning Probability Distributions in Macroeconomics and Finance," Papers 2204.06848, arXiv.org.
    55. Masato Ubukata & Toshiaki Watanabe, 2013. "Pricing Nikkei 225 Options Using Realized Volatility," Global COE Hi-Stat Discussion Paper Series gd12-273, Institute of Economic Research, Hitotsubashi University.
    56. Ma, Feng & Wahab, M.I.M. & Zhang, Yaojie, 2019. "Forecasting the U.S. stock volatility: An aligned jump index from G7 stock markets," Pacific-Basin Finance Journal, Elsevier, vol. 54(C), pages 132-146.
    57. Zargar, Faisal Nazir & Kumar, Dilip, 2020. "Heterogeneous market hypothesis approach for modeling unbiased extreme value volatility estimator in presence of leverage effect: An individual stock level study with economic significance analysis," The Quarterly Review of Economics and Finance, Elsevier, vol. 77(C), pages 271-285.
    58. Ryan T. Ball & Eric Ghysels, 2018. "Automated Earnings Forecasts: Beat Analysts or Combine and Conquer?," Management Science, INFORMS, vol. 64(10), pages 4936-4952, October.
    59. Hua, Jian & Manzan, Sebastiano, 2013. "Forecasting the return distribution using high-frequency volatility measures," Journal of Banking & Finance, Elsevier, vol. 37(11), pages 4381-4403.
    60. Kawakami, Tabito, 2023. "Quantile prediction for Bitcoin returns using financial assets’ realized measures," Finance Research Letters, Elsevier, vol. 55(PA).
    61. Guo, Yangli & He, Feng & Liang, Chao & Ma, Feng, 2022. "Oil price volatility predictability: New evidence from a scaled PCA approach," Energy Economics, Elsevier, vol. 105(C).
    62. Degiannakis, Stavros, 2018. "Multiple Days Ahead Realized Volatility Forecasting: Single, Combined and Average Forecasts," MPRA Paper 96272, University Library of Munich, Germany.
    63. Vortelinos, Dimitrios I. & Lakshmi, Geeta, 2015. "Market risk of BRIC Eurobonds in the financial crisis period," International Review of Economics & Finance, Elsevier, vol. 39(C), pages 295-310.
    64. Hwang, Eunju & Shin, Dong Wan, 2013. "A CUSUM test for a long memory heterogeneous autoregressive model," Economics Letters, Elsevier, vol. 121(3), pages 379-383.
    65. Xu, Qifa & Zhuo, Xingxuan & Jiang, Cuixia & Liu, Xi & Liu, Yezheng, 2018. "Group penalized unrestricted mixed data sampling model with application to forecasting US GDP growth," Economic Modelling, Elsevier, vol. 75(C), pages 221-236.
    66. Chao Wang & Richard Gerlach, 2019. "Semi-parametric Realized Nonlinear Conditional Autoregressive Expectile and Expected Shortfall," Papers 1906.09961, arXiv.org.
    67. Lin, Wen-Yuan & Tsai, I-Chun, 2019. "Black swan events in China's stock markets: Intraday price behaviors on days of volatility," International Review of Economics & Finance, Elsevier, vol. 59(C), pages 395-411.
    68. Dimitrios P. Louzis & Spyros Xanthopoulos - Sissinis & Apostolos P. Refenes, 2012. "Stock index Value-at-Risk forecasting: A realized volatility extreme value theory approach," Economics Bulletin, AccessEcon, vol. 32(1), pages 981-991.
    69. Dimitrios Louzis & Spyros Xanthopoulos-Sisinis & Apostolos Refenes, 2011. "Stock index realized volatility forecasting in the presence of heterogeneous leverage effects and long range dependence in the volatility of realized volatility," Post-Print hal-00709559, HAL.
    70. Baruník, Jozef & Čech, František, 2021. "Measurement of common risks in tails: A panel quantile regression model for financial returns," Journal of Financial Markets, Elsevier, vol. 52(C).

  18. Philip Inyeob Ji & Jae H. Kim, 2005. "Real Interest Rate Linkages in the Pacific Basin Region," Monash Econometrics and Business Statistics Working Papers 23/05, Monash University, Department of Econometrics and Business Statistics.

    Cited by:

    1. Baharumshah, Ahmad Zubaidi & Soon, Siew-Voon & Hamzah, Nor Aishah, 2013. "Parity reversion in real interest rate in the Asian countries: Further evidence based on local-persistent model," Economic Modelling, Elsevier, vol. 35(C), pages 634-642.
    2. Chang, Ming-Jen & Su, Che-Yi, 2014. "The dynamic relationship between exchange rates and macroeconomic fundamentals: Evidence from Pacific Rim countries," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 30(C), pages 220-246.
    3. Abdullah Gulcu & Dilem Yildirim, 2018. "Smooth Breaks And Nonlinear Mean Reversion In Real Interest Parity: Evidence From East Asian Countries," ERC Working Papers 1804, ERC - Economic Research Center, Middle East Technical University, revised Feb 2018.
    4. Zixiong Xie & Shyh-Wei Chen & An-Chi Wu, 2023. "Real interest rate parity in the Pacific Rim countries: new empirical evidence," Empirical Economics, Springer, vol. 64(3), pages 1471-1515, March.
    5. Khalid Kisswani & Salah Nusair, 2014. "Nonlinear convergence in Asian interest and inflation rates: evidence from Asian countries," Economic Change and Restructuring, Springer, vol. 47(3), pages 155-186, August.
    6. Kisswani, Khalid/ M. & Nusair, Salah/ A., 2011. "Non-linear convergence in Asian interest rates and inflation rates," MPRA Paper 34179, University Library of Munich, Germany.

  19. Jae H. Kim & Hristos Doucouliagos, 2005. "Realized Volatility and Correlation in Grain Futures Markets: Testing for Spill-Over Effects," Monash Econometrics and Business Statistics Working Papers 22/05, Monash University, Department of Econometrics and Business Statistics.

    Cited by:

    1. Chang, Chia-Lin & Khamkaew, Thanchanok & McAleer, Michael & Tansuchat, Roengchai, 2011. "Modelling conditional correlations in the volatility of Asian rubber spot and futures returns," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 81(7), pages 1482-1490.
    2. Younes Boujelbène & Majdi Ksantini, 2009. "La transmission entre les marchés boursiers :Une analyse en composante principale," Brussels Economic Review, ULB -- Universite Libre de Bruxelles, vol. 52(2), pages 161-194.
    3. Kim Hiang Liow, 2015. "Risk-return convergence in international public property markets," Journal of Property Research, Taylor & Francis Journals, vol. 32(1), pages 1-32, March.
    4. Pozo, Veronica F. & Schroeder, Ted C., 2012. "Price and Volatility Spillover between Livestock and Related Commodity Markets," 2012 Annual Meeting, August 12-14, 2012, Seattle, Washington 124798, Agricultural and Applied Economics Association.

  20. Param Silvapulle & Titi Kanti Lestari & Jae Kim, 2004. "Nonlinear Modelling of Purchasing Power Parity in Indonesia," Econometric Society 2004 Australasian Meetings 316, Econometric Society.

    Cited by:

    1. Hwa-Taek Lee & Gawon Yoon, 2013. "Does purchasing power parity hold sometimes? Regime switching in real exchange rates," Applied Economics, Taylor & Francis Journals, vol. 45(16), pages 2279-2294, June.

  21. Jae H. Kim, 2004. "Testing for the martingale hypothesis in Asian stock prices: evidence from a new joint variance ratio test," Econometric Society 2004 Australasian Meetings 98, Econometric Society.

    Cited by:

    1. 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.
    2. Annina Kaltenbrunner & Machiko Nissanke, 2009. "The Case for an Intermediate Exchange Rate Regime with Endogenizing Market Structures and Capital Mobility: The Empirical Study of Brazil," WIDER Working Paper Series RP2009-29, World Institute for Development Economic Research (UNU-WIDER).
    3. Mohsen Mehrara & Nafiseh Behradmehr & Mitra Saboonchi, 2013. "Investigating the Long time Memory in the Future Market of Gold," International Journal of Financial Economics, Research Academy of Social Sciences, vol. 1(1), pages 28-32.

Articles

  1. Jae H. Kim & In Choi, 2021. "Choosing the Level of Significance: A Decision‐theoretic Approach," Abacus, Accounting Foundation, University of Sydney, vol. 57(1), pages 27-71, March.

    Cited by:

    1. Jae H. Kim, 2022. "Moving to a world beyond p-value," Review of Managerial Science, Springer, vol. 16(8), pages 2467-2493, November.
    2. Run-Ping Che & Mei-Chun Cheung, 2022. "Community-Dwelling Older Adults’ Intended Use of Different Types of Long-Term Care in China and Its Associated Factors Based on the Andersen Behavioral Model," IJERPH, MDPI, vol. 19(18), pages 1-16, September.
    3. Mahiah Said & Ammar Azfar Azli & Shahnaz Shafiza Sabri, 2023. "Investigating the Factors Influencing Students’ Acceptance of Esports as a Career Choice," Information Management and Business Review, AMH International, vol. 15(2), pages 109-115.

  2. Kim, Jae H. & Shamsuddin, Abul, 2020. "A bootstrap test for predictability of asset returns," Finance Research Letters, Elsevier, vol. 35(C).

    Cited by:

    1. Khyati Kathuria & Nand Kumar, 2022. "Pandemic‐induced fear and government policy response as a measure of uncertainty in the foreign exchange market: Evidence from (a)symmetric wild bootstrap likelihood ratio test," Pacific Economic Review, Wiley Blackwell, vol. 27(4), pages 361-379, October.
    2. Erik Hjalmarsson & Tamas Kiss, 2022. "Long‐run predictability tests are even worse than you thought," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(7), pages 1334-1355, November.
    3. Godwin Olasehinde-Williams & Oktay Özkan, 2022. "Is interest rate uncertainty a predictor of investment volatility? evidence from the wild bootstrap likelihood ratio approach," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 46(3), pages 507-521, July.
    4. 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.

  3. Jae H. Kim, 2020. "Decision-Theoretic Hypothesis Testing: A Primer With R Package OptSig," The American Statistician, Taylor & Francis Journals, vol. 74(4), pages 370-379, October.

    Cited by:

    1. Maike Tormahlen & Galiya Klinkova & Michael Grabinski, 2021. "Statistical significance revisited," Papers 2104.00262, arXiv.org, revised Apr 2021.
    2. Jae H. Kim, 2022. "Moving to a world beyond p-value," Review of Managerial Science, Springer, vol. 16(8), pages 2467-2493, November.
    3. Jeremy Arkes, 2020. "Teaching Graduate (and Undergraduate) Econometrics: Some Sensible Shifts to Improve Efficiency, Effectiveness, and Usefulness," Econometrics, MDPI, vol. 8(3), pages 1-23, September.
    4. Maike Tormählen & Galiya Klinkova & Michael Grabinski, 2021. "Statistical Significance Revisited," Mathematics, MDPI, vol. 9(9), pages 1-16, April.

  4. Jae H. Kim & Andrew P. Robinson, 2019. "Interval-Based Hypothesis Testing and Its Applications to Economics and Finance," Econometrics, MDPI, vol. 7(2), pages 1-22, May.

    Cited by:

    1. Jae H. Kim, 2022. "Moving to a world beyond p-value," Review of Managerial Science, Springer, vol. 16(8), pages 2467-2493, November.
    2. Jan S. Krause & Gerrit Nanninga & Patrick Ring & Ulrich Schmidt & Daniel Schunk, 2020. "The Influence of Ambient Temperature on Social Perception and Social Behavior," Working Papers 2013, Gutenberg School of Management and Economics, Johannes Gutenberg-Universität Mainz.
    3. Pankaj Agrrawal, 2023. "The Gibbons, Ross, and Shanken Test for Portfolio Efficiency: A Note Based on Its Trigonometric Properties," Mathematics, MDPI, vol. 11(9), pages 1-19, May.

  5. Jae H. Kim, 2019. "Tackling False Positives In Business Research: A Statistical Toolbox With Applications," Journal of Economic Surveys, Wiley Blackwell, vol. 33(3), pages 862-895, July.

    Cited by:

    1. Kellner, Ralf & Rösch, Daniel, 2021. "A Bayesian Re-Interpretation of “significant” empirical financial research," Finance Research Letters, Elsevier, vol. 38(C).
    2. Jae H. Kim, 2022. "Moving to a world beyond p-value," Review of Managerial Science, Springer, vol. 16(8), pages 2467-2493, November.
    3. Jae H. Kim & Andrew P. Robinson, 2019. "Interval-Based Hypothesis Testing and Its Applications to Economics and Finance," Econometrics, MDPI, vol. 7(2), pages 1-22, May.
    4. Engsted, Tom & Schneider, Jesper W., 2023. "Non-Experimental Data, Hypothesis Testing, and the Likelihood Principle: A Social Science Perspective," SocArXiv nztk8, Center for Open Science.
    5. Paritosh Chandra Sinha, 2021. "Attention to the Election-Economics-Politics (EEP) Nexus in the Indian 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. 13(1), pages 7-32, June.

  6. Kim, Jae H. & Rahman, Md Lutfur & Shamsuddin, Abul, 2019. "Can energy prices predict stock returns? An extreme bounds analysis," Energy Economics, Elsevier, vol. 81(C), pages 822-834.

    Cited by:

    1. Naeem, Muhammad Abubakr & Balli, Faruk & Shahzad, Syed Jawad Hussain & de Bruin, Anne, 2020. "Energy commodity uncertainties and the systematic risk of US industries," Energy Economics, Elsevier, vol. 85(C).
    2. Guo, Li-Yang & Feng, Chao & Yang, Jun, 2022. "Can energy predict the regional prices of carbon emission allowances in China?," International Review of Financial Analysis, Elsevier, vol. 82(C).
    3. Kamal, Javed Bin & Wohar, Mark, 2023. "Heterogenous responses of stock markets to covid related news and sentiments: Evidence from the 1st year of pandemic," International Economics, Elsevier, vol. 173(C), pages 68-85.
    4. Fijorek, Kamil & Jurkowska, Aleksandra & Jonek-Kowalska, Izabela, 2021. "Financial contagion between the financial and the mining industries – Empirical evidence based on the symmetric and asymmetric CoVaR approach," Resources Policy, Elsevier, vol. 70(C).
    5. Zhang, Hua & Chen, Jinyu & Shao, Liuguo, 2021. "Dynamic spillovers between energy and stock markets and their implications in the context of COVID-19," International Review of Financial Analysis, Elsevier, vol. 77(C).
    6. Rahman, Md Lutfur & Hedström, Axel & Uddin, Gazi Salah & Kang, Sang Hoon, 2021. "Quantile relationship between Islamic and non-Islamic equity markets," Pacific-Basin Finance Journal, Elsevier, vol. 68(C).
    7. César Castro & Rebeca Jiménez-Rodríguez & Renatas Kizys, 2023. "Time-Varying Relation between Oil Shocks and European Stock Market Returns," JRFM, MDPI, vol. 16(3), pages 1-28, March.
    8. Godwin Olasehinde-Williams & Oktay Özkan, 2022. "Is interest rate uncertainty a predictor of investment volatility? evidence from the wild bootstrap likelihood ratio approach," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 46(3), pages 507-521, July.
    9. Xiao, Jihong & Wang, Yudong, 2022. "Good oil volatility, bad oil volatility, and stock return predictability," International Review of Economics & Finance, Elsevier, vol. 80(C), pages 953-966.
    10. Avik Sinha & Arshian Sharif & Arnab Adhikari & Ankit Sharma, 2022. "Dependence structure between Indian financial market and energy commodities: a cross-quantilogram based evidence," Annals of Operations Research, Springer, vol. 313(1), pages 257-287, June.
    11. Tri Wahyu Adi, 2022. "The International Gas and Crude Oil Price Variability Effect on Indonesian Coal Mining Companies Listed at IDX," International Journal of Energy Economics and Policy, Econjournals, vol. 12(5), pages 1-10, September.
    12. Ahmed, Walid M.A., 2022. "Robust drivers of Bitcoin price movements: An extreme bounds analysis," The North American Journal of Economics and Finance, Elsevier, vol. 62(C).
    13. Adekoya, Oluwasegun B. & Ogunbowale, Gideon O. & Akinseye, Ademola B. & Oduyemi, Gabriel O., 2021. "Improving the predictability of stock returns with global financial cycle and oil price in oil-exporting African countries," International Economics, Elsevier, vol. 168(C), pages 166-181.

  7. Jae H. Kim & Kamran Ahmed & Philip Inyeob Ji, 2018. "Significance Testing in Accounting Research: A Critical Evaluation Based on Evidence," Abacus, Accounting Foundation, University of Sydney, vol. 54(4), pages 524-546, December.

    Cited by:

    1. Kellner, Ralf & Rösch, Daniel, 2021. "A Bayesian Re-Interpretation of “significant” empirical financial research," Finance Research Letters, Elsevier, vol. 38(C).
    2. Dan Hu & Eunju Lee & Bingxin Li, 2023. "Trade secrets protection and stock price crash risk," The Financial Review, Eastern Finance Association, vol. 58(2), pages 395-421, May.
    3. Chen, Xiaomeng Charlene & Jones, Stewart & Hasan, Mostafa Monzur & Zhao, Ruoyun & Alam, Nurul, 2023. "Does strategic deviation influence firms’ use of supplier finance?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 85(C).
    4. Jae H. Kim & Andrew P. Robinson, 2019. "Interval-Based Hypothesis Testing and Its Applications to Economics and Finance," Econometrics, MDPI, vol. 7(2), pages 1-22, May.
    5. Jones, Stewart & Wang, Tim, 2019. "Predicting private company failure: A multi-class analysis," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 61(C), pages 161-188.
    6. Thomas R. Dyckman & Stephen A. Zeff, 2019. "Important Issues in Statistical Testing and Recommended Improvements in Accounting Research," Econometrics, MDPI, vol. 7(2), pages 1-11, May.
    7. Stewart Jones & Nurul Alam, 2019. "A machine learning analysis of citation impact among selected Pacific Basin journals," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 59(4), pages 2509-2552, December.
    8. Xi Fu & Xiaoxi Wu & Zhifang Zhang, 2021. "The Information Role of Earnings Conference Call Tone: Evidence from Stock Price Crash Risk," Journal of Business Ethics, Springer, vol. 173(3), pages 643-660, October.
    9. Jae H. Kim & In Choi, 2021. "Choosing the Level of Significance: A Decision‐theoretic Approach," Abacus, Accounting Foundation, University of Sydney, vol. 57(1), pages 27-71, March.
    10. James A. Ohlson, 2022. "Researchers’ data analysis choices: an excess of false positives?," Review of Accounting Studies, Springer, vol. 27(2), pages 649-667, June.
    11. Muhammad Ishaq Bhatti & Jae H. Kim, 2020. "Towards a New Paradigm for Statistical Evidence in the Use of p -Value," Econometrics, MDPI, vol. 9(1), pages 1-3, December.
    12. Johnstone, David, 2022. "Accounting research and the significance test crisis," CRITICAL PERSPECTIVES ON ACCOUNTING, Elsevier, vol. 89(C).

  8. Kim, Jae H., 2017. "Stock returns and investors' mood: Good day sunshine or spurious correlation?," International Review of Financial Analysis, Elsevier, vol. 52(C), pages 94-103.
    See citations under working paper version above.
  9. Charles, Amélie & Darné, Olivier & Kim, Jae H., 2017. "Adaptive markets hypothesis for Islamic stock indices: Evidence from Dow Jones size and sector-indices," International Economics, Elsevier, vol. 151(C), pages 100-112.
    See citations under working paper version above.
  10. Charles, Amélie & Darné, Olivier & Kim, Jae H., 2017. "International stock return predictability: Evidence from new statistical tests," International Review of Financial Analysis, Elsevier, vol. 54(C), pages 97-113.
    See citations under working paper version above.
  11. Jae H. Kim & In Choi, 2017. "Unit Roots in Economic and Financial Time Series: A Re-Evaluation at the Decision-Based Significance Levels," Econometrics, MDPI, vol. 5(3), pages 1-23, September.

    Cited by:

    1. Jae H. Kim, 2022. "Moving to a world beyond p-value," Review of Managerial Science, Springer, vol. 16(8), pages 2467-2493, November.
    2. Jae H. Kim & Kamran Ahmed & Philip Inyeob Ji, 2018. "Significance Testing in Accounting Research: A Critical Evaluation Based on Evidence," Abacus, Accounting Foundation, University of Sydney, vol. 54(4), pages 524-546, December.
    3. Jae H. Kim & Andrew P. Robinson, 2019. "Interval-Based Hypothesis Testing and Its Applications to Economics and Finance," Econometrics, MDPI, vol. 7(2), pages 1-22, May.
    4. Harkat, Tahar, 2020. "Causality between Energy Consumption and Economic Development: Empirical Evidence from Morocco," MPRA Paper 98313, University Library of Munich, Germany.
    5. Harkat, Tahar, 2020. "Nexus between Energy Consumption, Economic Development, and CO2 Emissions: Empirical Evidence from Morocco," MPRA Paper 98476, University Library of Munich, Germany.
    6. In Choi & Hanbat Jeong, 2020. "Differencing versus nondifferencing in factor‐based forecasting," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(6), pages 728-750, September.
    7. Muhammad Ishaq Bhatti & Jae H. Kim, 2020. "Towards a New Paradigm for Statistical Evidence in the Use of p -Value," Econometrics, MDPI, vol. 9(1), pages 1-3, December.
    8. Michael P. Clements, 2020. "Are Some Forecasters’ Probability Assessments of Macro Variables Better Than Those of Others?," Econometrics, MDPI, vol. 8(2), pages 1-16, May.

  12. Am鬩e Charles & Olivier Darn頍 & Jae H. Kim & Etienne Redor, 2016. "Stock exchange mergers and market efficiency," Applied Economics, Taylor & Francis Journals, vol. 48(7), pages 576-589, February.
    See citations under working paper version above.
  13. Kim, Jae H. & Ji, Philip Inyeob, 2015. "Significance testing in empirical finance: A critical review and assessment," Journal of Empirical Finance, Elsevier, vol. 34(C), pages 1-14.

    Cited by:

    1. Amélie Charles & Olivier Darné & Jae H. Kim, 2022. "Stock return predictability: Evaluation based on interval forecasts," Bulletin of Economic Research, Wiley Blackwell, vol. 74(2), pages 363-385, April.
    2. Kim, Jae H., 2017. "Stock returns and investors' mood: Good day sunshine or spurious correlation?," International Review of Financial Analysis, Elsevier, vol. 52(C), pages 94-103.
    3. Kellner, Ralf & Rösch, Daniel, 2021. "A Bayesian Re-Interpretation of “significant” empirical financial research," Finance Research Letters, Elsevier, vol. 38(C).
    4. Baker, Andrew C. & Larcker, David F. & Wang, Charles C.Y., 2022. "How much should we trust staggered difference-in-differences estimates?," Journal of Financial Economics, Elsevier, vol. 144(2), pages 370-395.
    5. Stephan B. Bruns & David I. Stern, 2019. "Lag length selection and p-hacking in Granger causality testing: prevalence and performance of meta-regression models," Empirical Economics, Springer, vol. 56(3), pages 797-830, March.
    6. Anghel, Dan Gabriel, 2021. "Data Snooping Bias in Tests of the Relative Performance of Multiple Forecasting Models," Journal of Banking & Finance, Elsevier, vol. 126(C).
    7. Jae H. Kim, 2022. "Moving to a world beyond p-value," Review of Managerial Science, Springer, vol. 16(8), pages 2467-2493, November.
    8. Jeremy Arkes, 2020. "Teaching Graduate (and Undergraduate) Econometrics: Some Sensible Shifts to Improve Efficiency, Effectiveness, and Usefulness," Econometrics, MDPI, vol. 8(3), pages 1-23, September.
    9. Jae H. Kim & Kamran Ahmed & Philip Inyeob Ji, 2018. "Significance Testing in Accounting Research: A Critical Evaluation Based on Evidence," Abacus, Accounting Foundation, University of Sydney, vol. 54(4), pages 524-546, December.
    10. Yergeau, Gabriel, 2016. "Profitability and Market Quality of High Frequency Market-makers: An Empirical Investigation," Working Papers 16-3, HEC Montreal, Canada Research Chair in Risk Management.
    11. Jae H. Kim & Andrew P. Robinson, 2019. "Interval-Based Hypothesis Testing and Its Applications to Economics and Finance," Econometrics, MDPI, vol. 7(2), pages 1-22, May.
    12. Kim, Jae, 2015. "How to Choose the Level of Significance: A Pedagogical Note," MPRA Paper 66373, University Library of Munich, Germany.
    13. Kim, Jae & Choi, In, 2015. "Unit Roots in Economic and Financial Time Series: A Re-Evaluation based on Enlightened Judgement," MPRA Paper 68411, University Library of Munich, Germany.
    14. Richard Startz, 2019. "Not p -Values, Said a Little Bit Differently," Econometrics, MDPI, vol. 7(1), pages 1-5, March.
    15. Geyer-Klingeberg, Jerome & Hang, Markus & Rathgeber, Andreas, 2020. "Meta-analysis in finance research: Opportunities, challenges, and contemporary applications," International Review of Financial Analysis, Elsevier, vol. 71(C).
    16. Jerome Geyer-Klingeberg & Markus Hang & Andreas Rathgeber, 2021. "Corporate financial hedging and firm value: a meta-analysis," The European Journal of Finance, Taylor & Francis Journals, vol. 27(6), pages 461-485, April.
    17. John Quiggin, 2019. "The Replication Crisis as Market Failure," Econometrics, MDPI, vol. 7(4), pages 1-8, November.
    18. Jan S. Krause & Gerrit Nanninga & Patrick Ring & Ulrich Schmidt & Daniel Schunk, 2020. "The Influence of Ambient Temperature on Social Perception and Social Behavior," Working Papers 2013, Gutenberg School of Management and Economics, Johannes Gutenberg-Universität Mainz.
    19. Liu, Huajin & Zhang, Wei & Zhang, Xiaotao & Liu, Jia, 2021. "Temperature and trading behaviours," International Review of Financial Analysis, Elsevier, vol. 78(C).
    20. Amir Karami & Morgan Lundy & Frank Webb & Gabrielle Turner-McGrievy & Brooke W. McKeever & Robert McKeever, 2021. "Identifying and Analyzing Health-Related Themes in Disinformation Shared by Conservative and Liberal Russian Trolls on Twitter," IJERPH, MDPI, vol. 18(4), pages 1-16, February.
    21. Michaelides, Michael, 2021. "Large sample size bias in empirical finance," Finance Research Letters, Elsevier, vol. 41(C).
    22. Jae H. Kim & In Choi, 2021. "Choosing the Level of Significance: A Decision‐theoretic Approach," Abacus, Accounting Foundation, University of Sydney, vol. 57(1), pages 27-71, March.
    23. Fjesme, Sturla Lyngnes, 2020. "Retail investor experience, asset learning, and portfolio risk-adjusted returns," Finance Research Letters, Elsevier, vol. 36(C).
    24. Zack Jourdan & J. Ken. Corley & Randall Valentine & Arthur M. Tran, 2023. "Fintech: A content analysis of the finance and information systems literature," Electronic Markets, Springer;IIM University of St. Gallen, vol. 33(1), pages 1-21, December.
    25. Grace Lepone & Joakim Westerholm & Danika Wright, 2023. "Speculative trading preferences of retail investor birth cohorts," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 63(1), pages 555-574, March.
    26. David Trafimow, 2019. "A Frequentist Alternative to Significance Testing, p -Values, and Confidence Intervals," Econometrics, MDPI, vol. 7(2), pages 1-14, June.
    27. Jae H. Kim & In Choi, 2017. "Unit Roots in Economic and Financial Time Series: A Re-Evaluation at the Decision-Based Significance Levels," Econometrics, MDPI, vol. 5(3), pages 1-23, September.
    28. Johnstone, David, 2022. "Accounting research and the significance test crisis," CRITICAL PERSPECTIVES ON ACCOUNTING, Elsevier, vol. 89(C).
    29. Todd Mitton, 2022. "Methodological Variation in Empirical Corporate Finance," The Review of Financial Studies, Society for Financial Studies, vol. 35(2), pages 527-575.

  14. Shamsuddin, Abul & Kim, Jae H., 2015. "Market sentiment and the Fama–French factor premia," Economics Letters, Elsevier, vol. 136(C), pages 129-132.

    Cited by:

    1. Pati, Pratap Chandra & Rajib, Prabina & Barai, Parama, 2019. "The role of the volatility index in asset pricing: The case of the Indian stock market," The Quarterly Review of Economics and Finance, Elsevier, vol. 74(C), pages 336-346.
    2. Bekiros, Stelios & Jlassi, Mouna & Naoui, Kamel & Uddin, Gazi Salah, 2017. "The asymmetric relationship between returns and implied volatility: Evidence from global stock markets," Journal of Financial Stability, Elsevier, vol. 30(C), pages 156-174.

  15. Jae H. Kim & Abul Shamsuddin, 2015. "A closer look at return predictability of the US stock market: evidence from new panel variance ratio tests," Quantitative Finance, Taylor & Francis Journals, vol. 15(9), pages 1501-1514, September.

    Cited by:

    1. Rahman, Md. Lutfur & Lee, Doowon & Shamsuddin, Abul, 2017. "Time-varying return predictability in South Asian equity markets," International Review of Economics & Finance, Elsevier, vol. 48(C), pages 179-200.
    2. Md Lutfur Rahman & Mahbub Khan & Samuel A. Vigne & Gazi Salah Uddin, 2021. "Equity return predictability, its determinants, and profitable trading strategies," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(1), pages 162-186, January.
    3. Awijen, Haithem & Ben Zaied, Younes & Ben Lahouel, Béchir & Khlifi, Foued, 2023. "Machine learning for US cross-industry return predictability under information uncertainty," Research in International Business and Finance, Elsevier, vol. 64(C).
    4. Charalampos Stasinakis & Georgios Sermpinis & Ioannis Psaradellis & Thanos Verousis, 2016. "Krill-Herd Support Vector Regression and heterogeneous autoregressive leverage: evidence from forecasting and trading commodities," Quantitative Finance, Taylor & Francis Journals, vol. 16(12), pages 1901-1915, December.
    5. Eva Regnier, 2018. "Probability Forecasts Made at Multiple Lead Times," Management Science, INFORMS, vol. 64(5), pages 2407-2426, May.

  16. Charles, Amélie & Darné, Olivier & Kim, Jae H., 2015. "Will precious metals shine? A market efficiency perspective," International Review of Financial Analysis, Elsevier, vol. 41(C), pages 284-291.
    See citations under working paper version above.
  17. Kim, Jae H., 2014. "Testing for parameter restrictions in a stationary VAR model: A bootstrap alternative," Economic Modelling, Elsevier, vol. 41(C), pages 267-273.

    Cited by:

    1. Ghassan, Hassan & Alhajhoj, Hassan R. & Balli, Faruk, 2018. "Bi-Demographic Changes and Current Account using SVAR Modeling: Evidence from Saudi Arabia," MPRA Paper 93013, University Library of Munich, Germany, revised 01 Feb 2019.
    2. Amélie Charles & Olivier Darné & Jae H Kim, 2017. "International Stock Return Predictability: Evidence from New Statistical Tests," Post-Print hal-01626101, HAL.
    3. Liew, Ping-Xin & Lim, Kian-Ping & Goh, Kim-Leng, 2018. "Foreign equity flows: Boon or bane to the liquidity of Malaysian stock market?," The North American Journal of Economics and Finance, Elsevier, vol. 45(C), pages 161-181.

  18. 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.

    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. 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.
    4. 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.
    5. Rahman, Md. Lutfur & Lee, Doowon & Shamsuddin, Abul, 2017. "Time-varying return predictability in South Asian equity markets," International Review of Economics & Finance, Elsevier, vol. 48(C), pages 179-200.
    6. Khurshid M. Kiani, 2016. "On Modelling and Forecasting Predictable Components in European Stock Markets," Computational Economics, Springer;Society for Computational Economics, vol. 48(3), pages 487-502, October.
    7. Noda, Akihiko, 2016. "A test of the adaptive market hypothesis using a time-varying AR model in Japan," Finance Research Letters, Elsevier, vol. 17(C), pages 66-71.
    8. Fabio S. Dias & Gareth W. Peters, 2020. "A Non-parametric Test and Predictive Model for Signed Path Dependence," Computational Economics, Springer;Society for Computational Economics, vol. 56(2), pages 461-498, August.
    9. Mikio Ito & Akihiko Noda & Tatsuma Wada, 2012. "The Evolution of Stock Market Efficiency in the US: A Non-Bayesian Time-Varying Model Approach," Papers 1202.0100, arXiv.org, revised Aug 2015.
    10. 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.
    11. 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.
    12. 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.
    13. 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.
    14. Urquhart, Andrew & McGroarty, Frank, 2014. "Calendar effects, market conditions and the Adaptive Market Hypothesis: Evidence from long-run U.S. data," International Review of Financial Analysis, Elsevier, vol. 35(C), pages 154-166.
    15. Md Lutfur Rahman & Mahbub Khan & Samuel A. Vigne & Gazi Salah Uddin, 2021. "Equity return predictability, its determinants, and profitable trading strategies," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(1), pages 162-186, January.
    16. 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.
    17. Siddique, Maryam, 2023. "Does the Adaptive Market Hypothesis Exist in Equity Market? Evidence from Pakistan Stock Exchange," OSF Preprints 9b5dx, Center for Open Science.
    18. Urquhart, Andrew & Hudson, Robert, 2013. "Efficient or adaptive markets? Evidence from major stock markets using very long run historic data," International Review of Financial Analysis, Elsevier, vol. 28(C), pages 130-142.
    19. Dzung Phan Tran Trung & Hung Pham Quang, 2019. "Adaptive Market Hypothesis: Evidence from the Vietnamese Stock Market," JRFM, MDPI, vol. 12(2), pages 1-16, May.
    20. 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.
    21. Hill, Jonathan B. & Motegi, Kaiji, 2019. "Testing the white noise hypothesis of stock returns," Economic Modelling, Elsevier, vol. 76(C), pages 231-242.
    22. Kenichi Hirayama & Akihiko Noda, 2019. "Measuring the Time-Varying Market Efficiency in the Prewar Japanese Stock Market, 1924-1943," Papers 1911.04059, arXiv.org, revised Dec 2022.
    23. Shahzad, Syed Jawad Hussain & Bouri, Elie & Kayani, Ghulam Mujtaba & Nasir, Rana Muhammad & Kristoufek, Ladislav, 2020. "Are clean energy stocks efficient? Asymmetric multifractal scaling behaviour," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 550(C).
    24. Al-Khazali, Osamah & Mirzaei, Ali, 2017. "Stock market anomalies, market efficiency and the adaptive market hypothesis: Evidence from Islamic stock indices," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 51(C), pages 190-208.
    25. 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.
    26. Urquhart, Andrew & Gebka, Bartosz & Hudson, Robert, 2015. "How exactly do markets adapt? Evidence from the moving average rule in three developed markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 38(C), pages 127-147.
    27. 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.
    28. 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.
    29. 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.
    30. Maderitsch, R., 2015. "Information transmission between stock markets in Hong Kong, Europe and the US: New evidence on time- and state-dependence," Pacific-Basin Finance Journal, Elsevier, vol. 35(PA), pages 13-36.
    31. Mushinada, Venkata Narasimha Chary, 2020. "Are individual investors irrational or adaptive to market dynamics?," Journal of Behavioral and Experimental Finance, Elsevier, vol. 25(C).
    32. 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.
    33. Ke Meng & Shouhao Li, 2021. "The adaptive market hypothesis and high frequency trading," PLOS ONE, Public Library of Science, vol. 16(12), pages 1-19, December.
    34. Jan Jakub Szczygielski & Chimwemwe Chipeta, 2023. "Properties of returns and variance and the implications for time series modelling: Evidence from South Africa," Modern Finance, Modern Finance Institute, vol. 1(1), pages 35-55.
    35. 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.

  19. Rushdi, Mustabshira & Kim, Jae H. & Silvapulle, Param, 2012. "ARDL bounds tests and robust inference for the long run relationship between real stock returns and inflation in Australia," Economic Modelling, Elsevier, vol. 29(3), pages 535-543.

    Cited by:

    1. Aviral Kumar Tiwari & Adeolu O. Adewuyi & Olabanji B. Awodumi & David Roubaud, 2022. "Relationship between stock returns and inflation: New evidence from the US using wavelet and causality methods," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(4), pages 4515-4540, October.
    2. Anyiwe, Mercy Ada & Sunday Osahon Igbinedion, 2015. "Stock Returns, Inflation and the “Reverse Causality†Hypothesis: Evidence from Nigeria," International Journal of Research in Business and Social Science (2147-4478), Center for the Strategic Studies in Business and Finance, vol. 4(1), pages 32-50, January.
    3. Avishek Bhandari & Kamaiah Bandi, 2018. "On the Dynamics of Inflation-Stock Returns in India," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 16(1), pages 89-99, March.
    4. Salisu, Afees A. & Raheem, Ibrahim D. & Ndako, Umar B., 2020. "The inflation hedging properties of gold, stocks and real estate: A comparative analysis," Resources Policy, Elsevier, vol. 66(C).
    5. Hatab, Assem Abu & Nsabimana, Aimable, 2016. "A Dynamic Analysis of Egyptian Orange Exports to Russia: A Co-integration Analysis," Agricultural Economics Review, Greek Association of Agricultural Economists, vol. 17(2), June.
    6. Konrad Farrugia & Janice Duca & Peter J. Baldacchino & Simon Grima, 2021. "The Relationship between Inflation and Stock Returns in a Small Island State: An Analysis," International Journal of Finance, Insurance and Risk Management, International Journal of Finance, Insurance and Risk Management, vol. 11(2), pages 51-78.
    7. Ye Fan & Zhicheng Zhang & Xiaoli Zhao & Haitao Yin, 2018. "Interaction between Industrial Policy and Stock Price Volatility: Evidence from China’s Power Market Reform," Sustainability, MDPI, vol. 10(6), pages 1-19, May.
    8. Tiwari, Aviral Kumar & Dar, Arif Billah & Bhanja, Niyati & Arouri, Mohamed & Teulon, Frédéric, 2015. "Stock returns and inflation in Pakistan," Economic Modelling, Elsevier, vol. 47(C), pages 23-31.
    9. Basse, Tobias & Wegener, Christoph, 2022. "Inflation expectations: Australian consumer survey data versus the bond market," Journal of Economic Behavior & Organization, Elsevier, vol. 203(C), pages 416-430.
    10. Donald A. Otieno & Rose W. Ngugi & Peter W. Muriu, 2019. "The impact of inflation rate on stock market returns: evidence from Kenya," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 43(1), pages 73-90, January.
    11. Nassar S. Al-Nassar & Razzaque H. Bhatti, 2019. "Are common stocks a hedge against inflation in emerging markets?," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 43(3), pages 421-455, July.
    12. Ghozali Maski & An'im Kafabih & Arif Hoetoro, 2018. "Testing Profit and Loss Sharing to Stabilise Level of Inflation: Evidence From Indonesia," Research in World Economy, Research in World Economy, Sciedu Press, vol. 9(2), pages 12-23, June.
    13. Chen, Mei-Ping & Lee, Chien-Chiang & Hsu, Yi-Chung, 2017. "Investor sentiment and country exchange traded funds: Does economic freedom matter?," The North American Journal of Economics and Finance, Elsevier, vol. 42(C), pages 285-299.
    14. Somayeh Madadpour & Mohsen Asgari, 2019. "The puzzling relationship between stocks return and inflation: a review article," International Review of Economics, Springer;Happiness Economics and Interpersonal Relations (HEIRS), vol. 66(2), pages 115-145, June.
    15. Hassan Heidari & Arash Refah Kahriz & Yousef Mohammadzadeh, 2019. "Stock market behavior of pharmaceutical industry in Iran and macroeconomic factors," Economic Change and Restructuring, Springer, vol. 52(3), pages 255-277, August.
    16. Dragos Stefan Oprea, 2014. "The Fisher effect: Evidence from the Romanian Stock Market," International Journal of Academic Research in Business and Social Sciences, Human Resource Management Academic Research Society, International Journal of Academic Research in Business and Social Sciences, vol. 4(5), pages 637-644, May.
    17. Jasman Tuyon & Zamri Ahmad & Hylmee Matahir, 2016. "The Roles of Investor Sentiment in Malaysian Stock Market," Asian Academy of Management Journal of Accounting and Finance (AAMJAF), Penerbit Universiti Sains Malaysia, vol. 12(Suppl. 1), pages 43-75.
    18. NEIFAR, MALIKA & HACHICHA, Fatma, 2022. "GFH validity for Canada, UK, and Suisse stock markets: Evidence ‎from univariate and panel ARDL models," MPRA Paper 114613, University Library of Munich, Germany.
    19. Ge, Xiaodong & Li, Yaoguang & Luloff, Albert E. & Dong, Kaikai & Xiao, Jun, 2015. "Effect of agricultural economic growth on sandy desertification in Horqin Sandy Land," Ecological Economics, Elsevier, vol. 119(C), pages 53-63.
    20. Niyati Bhanja & Arif Billah Dar, 2019. "Stock returns and inflation: a tale of two periods in India," Economic Change and Restructuring, Springer, vol. 52(4), pages 413-438, November.
    21. Rene Coppe Pimentel & Taufiq Choudhry, 2014. "Stock Returns Under High Inflation and Interest Rates: Evidence from the Brazilian Market," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 50(1), pages 71-92, January.

  20. 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.
  21. Jasim Al-Ajmi & J. H. Kim, 2012. "Are Gulf stock markets efficient? Evidence from new multiple variance ratio tests," Applied Economics, Taylor & Francis Journals, vol. 44(14), pages 1737-1747, May.

    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. Hatemi-J, Abdulnasser, 2012. "Is the UAE stock market integrated with the USA stock market? New evidence from asymmetric causality testing," Research in International Business and Finance, Elsevier, vol. 26(2), pages 273-280.
    3. Turki Rashed Alshammari & Jean-Noël Ory, 2023. "The Impact of Religious Announcements on Stock Prices and Investment Decisions on the Saudi Stock Exchange," Post-Print hal-04105704, HAL.
    4. Ghada Abbas, 2014. "Testing Random Walk Behavior in the Damascus Securities Exchange," International Journal of Academic Research in Accounting, Finance and Management Sciences, Human Resource Management Academic Research Society, International Journal of Academic Research in Accounting, Finance and Management Sciences, vol. 4(4), pages 317-325, October.
    5. Fathia Elleuch Lahyani, 2014. "Are MENA and Pacific Basin Stock Equity Markets Predictable?," SAGE Open, , vol. 4(4), pages 21582440145, December.
    6. Al-Hadi, Ahmed & Taylor, Grantley & Hossain, Mahmud, 2015. "Disaggregation, auditor conservatism and implied cost of equity capital: An international evidence from the GCC," Journal of Multinational Financial Management, Elsevier, vol. 29(C), pages 66-98.
    7. Hatemi-J, Abdulnasser & Mustafa, Alan, 2016. "Testing for Financial Market Integration of the Chinese Market with the US Market," MPRA Paper 72733, University Library of Munich, Germany.
    8. Khoja, Layla & Chipulu, Maxwell & Jayasekera, Ranadeva, 2019. "Analysis of financial distress cross countries: Using macroeconomic, industrial indicators and accounting data," International Review of Financial Analysis, Elsevier, vol. 66(C).
    9. Alhashel, Bader S. & Albader, Sulaiman H., 2020. "How do sovereign wealth funds pay their portfolio companies’ executives? Evidence from Kuwait," International Review of Economics & Finance, Elsevier, vol. 67(C), pages 303-322.
    10. Al-Faryan, Mamdouh Abdulaziz Saleh & Dockery, Everton, 2020. "Testing for efficiency in the Saudi stock market: does corporate governance change matter?," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, issue Latest Ar, pages 1-30.
    11. Achal Awasthi & Oleg Malafeyev, 2015. "Is the Indian Stock Market efficient - A comprehensive study of Bombay Stock Exchange Indices," Papers 1510.03704, arXiv.org.
    12. 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).
    13. 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).
    14. Jamaani, Fouad & Roca, Eduardo, 2015. "Are the regional Gulf stock markets weak-form efficient as single stock markets and as a regional stock market?," Research in International Business and Finance, Elsevier, vol. 33(C), pages 221-246.
    15. Layla Khoja & Maxwell Chipulu & Ranadeva Jayasekera, 2016. "Analysing corporate insolvency in the Gulf Cooperation Council using logistic regression and multidimensional scaling," Review of Quantitative Finance and Accounting, Springer, vol. 46(3), pages 483-518, April.
    16. 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.
    17. Abdulsamad Alazzani & Wan Nordin Wan-Hussin & Michael Jones & Ahmed Al-hadi, 2021. "ESG Reporting and Analysts’ Recommendations in GCC: The Moderation Role of Royal Family Directors," JRFM, MDPI, vol. 14(2), pages 1-21, February.

  22. 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.
  23. Kim, Jae H. & Ryoo, Heajin H., 2011. "Common stocks as a hedge against inflation: Evidence from century-long US data," Economics Letters, Elsevier, vol. 113(2), pages 168-171.

    Cited by:

    1. Mustapha Ibn Boamah, 2017. "Common Stocks and Inflation: An Empirical Analysis of G7 and BRICS," Atlantic Economic Journal, Springer;International Atlantic Economic Society, vol. 45(2), pages 213-224, June.
    2. Salisu, Afees A. & Adediran, Idris A., 2019. "Assessing the inflation hedging potential of coal and iron ore in Australia," Resources Policy, Elsevier, vol. 63(C), pages 1-1.
    3. Aviral Kumar Tiwari & Adeolu O. Adewuyi & Olabanji B. Awodumi & David Roubaud, 2022. "Relationship between stock returns and inflation: New evidence from the US using wavelet and causality methods," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(4), pages 4515-4540, October.
    4. Anyiwe, Mercy Ada & Sunday Osahon Igbinedion, 2015. "Stock Returns, Inflation and the “Reverse Causality†Hypothesis: Evidence from Nigeria," International Journal of Research in Business and Social Science (2147-4478), Center for the Strategic Studies in Business and Finance, vol. 4(1), pages 32-50, January.
    5. Avishek Bhandari & Kamaiah Bandi, 2018. "On the Dynamics of Inflation-Stock Returns in India," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 16(1), pages 89-99, March.
    6. Salisu, Afees A. & Raheem, Ibrahim D. & Ndako, Umar B., 2020. "The inflation hedging properties of gold, stocks and real estate: A comparative analysis," Resources Policy, Elsevier, vol. 66(C).
    7. Konrad Farrugia & Janice Duca & Peter J. Baldacchino & Simon Grima, 2021. "The Relationship between Inflation and Stock Returns in a Small Island State: An Analysis," International Journal of Finance, Insurance and Risk Management, International Journal of Finance, Insurance and Risk Management, vol. 11(2), pages 51-78.
    8. Adekoya, Oluwasegun B. & Oliyide, Johnson A. & Tahir, Hammad, 2021. "What do we know about the inflation-hedging property of precious metals in Africa? The case of leading producers of the commodities," Resources Policy, Elsevier, vol. 72(C).
    9. Tiwari, Aviral Kumar & Dar, Arif Billah & Bhanja, Niyati & Arouri, Mohamed & Teulon, Frédéric, 2015. "Stock returns and inflation in Pakistan," Economic Modelling, Elsevier, vol. 47(C), pages 23-31.
    10. Zaremba, Adam & Umar, Zaghum & Mikutowski, Mateusz, 2019. "Inflation hedging with commodities: A wavelet analysis of seven centuries worth of data," Economics Letters, Elsevier, vol. 181(C), pages 90-94.
    11. Donald A. Otieno & Rose W. Ngugi & Peter W. Muriu, 2019. "The impact of inflation rate on stock market returns: evidence from Kenya," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 43(1), pages 73-90, January.
    12. Nassar S. Al-Nassar & Razzaque H. Bhatti, 2019. "Are common stocks a hedge against inflation in emerging markets?," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 43(3), pages 421-455, July.
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    115. 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.
    116. Navaz Naghavi & Wee-Yeap Lau, 2014. "Exploring the nexus between financial openness and informational efficiency -- does the quality of institution matter?," Applied Economics, Taylor & Francis Journals, vol. 46(7), pages 674-685, March.
    117. Bhatia, Madhur, 2023. "On the efficiency of the gold returns: An econometric exploration for India, USA and Brazil," Resources Policy, Elsevier, vol. 82(C).
    118. Kinnunen, Jyri, 2013. "Dynamic return predictability in the Russian stock market," Emerging Markets Review, Elsevier, vol. 15(C), pages 107-121.
    119. Ali Fayyaz Munir & Mohd Edil Abd. Sukor & Shahrin Saaid Shaharuddin, 2022. "Adaptive Market Hypothesis and Time-varying Contrarian Effect: Evidence From Emerging Stock Markets of South Asia," SAGE Open, , vol. 12(1), pages 21582440211, January.
    120. Meraz, M. & Alvarez-Ramirez, J. & Rodriguez, E., 2022. "Multivariate rescaled range analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 589(C).
    121. 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.
    122. 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).
    123. Jasman Tuyon & Zamri Ahmad, 2018. "Behavioural Asset Pricing Determinants in a Factor and Style Investing Framework," Capital Markets Review, Malaysian Finance Association, vol. 26(2), pages 32-52.
    124. Aurelio F. Bariviera & Luciano Zunino & Osvaldo A. Rosso, 2018. "An analysis of high-frequency cryptocurrencies prices dynamics using permutation-information-theory quantifiers," Papers 1808.01926, arXiv.org.
    125. Chen, Chien-Hua & Su, Xuan-Qi & Lin, Jun-Biao, 2016. "The role of information uncertainty in moving-average technical analysis: A study of individual stock-option issuance in Taiwan," Finance Research Letters, Elsevier, vol. 18(C), pages 263-272.
    126. 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.
    127. Koichiro Moriya & Akihiko Noda, 2023. "On the Time-Varying Structure of the Arbitrage Pricing Theory using the Japanese Sector Indices," Papers 2305.05998, arXiv.org, revised Mar 2024.
    128. Godfrey, Keith R.L., 2017. "Toward a model-free measure of market efficiency," Pacific-Basin Finance Journal, Elsevier, vol. 44(C), pages 97-112.
    129. Stéphane Goutte & David Guerreiro & Bilel Sanhaji & Sophie Saglio & Julien Chevallier, 2019. "International Financial Markets," Post-Print halshs-02183053, HAL.

  25. Kim, Jae H. & Ji, Philip Inyeob, 2011. "Mean-reversion in international real interest rates," Economic Modelling, Elsevier, vol. 28(4), pages 1959-1966, July.

    Cited by:

    1. Philip Inyeob Ji & Sangbae Kim, 2013. "Mean-reversion in closed-end fund discount: evidence from half-life," Applied Economics, Taylor & Francis Journals, vol. 45(32), pages 4503-4515, November.
    2. Soon, Siew-Voon & Baharumshah, Ahmad Zubaidi & Mohamad Shariff, Nurul Sima, 2017. "The persistence in real interest rates: Does it solve the intertemporal consumption behavior puzzle?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 50(C), pages 36-51.
    3. Khalid Kisswani & Salah Nusair, 2014. "Nonlinear convergence in Asian interest and inflation rates: evidence from Asian countries," Economic Change and Restructuring, Springer, vol. 47(3), pages 155-186, August.
    4. Chih-Kai Chang & Tsangyao Chang, 2012. "Statistical evidence on the mean reversion of real interest rates: SPSM using the Panel KSS test with a Fourier function," Applied Economics Letters, Taylor & Francis Journals, vol. 19(13), pages 1299-1304, September.

  26. 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.

    Cited by:

    1. Ma, Rui & Anderson, Hamish D. & Marshall, Ben R., 2019. "Risk perceptions and international stock market liquidity," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 62(C), pages 94-116.
    2. 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.
    3. Hooy, Chee-Wooi & Lim, Kian-Ping, 2013. "Is market integration associated with informational efficiency of stock markets?," Journal of Policy Modeling, Elsevier, vol. 35(1), pages 29-44.
    4. Noda, Akihiko, 2016. "A test of the adaptive market hypothesis using a time-varying AR model in Japan," Finance Research Letters, Elsevier, vol. 17(C), pages 66-71.
    5. Akihiko Noda, 2019. "On the Evolution of Cryptocurrency Market Efficiency," Papers 1904.09403, arXiv.org, revised Jul 2020.
    6. Zhang, Wei & Huang, Ke & Feng, Xu & Zhang, Yongjie, 2017. "Market maker competition and price efficiency: Evidence from China," Economic Modelling, Elsevier, vol. 66(C), pages 121-131.
    7. Md Lutfur Rahman & Mahbub Khan & Samuel A. Vigne & Gazi Salah Uddin, 2021. "Equity return predictability, its determinants, and profitable trading strategies," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(1), pages 162-186, January.
    8. Andrieş, Alin Marius & Plopeanu, Aurelian-Petruş & Sprincean, Nicu, 2023. "Institutional determinants of households’ financial investment behaviour across European countries," Economic Analysis and Policy, Elsevier, vol. 77(C), pages 300-325.
    9. Giuseppe Galloppo & Mauro Aliano, 2018. "Fund Manager Performance in Emerging Market: Factor Specialisation and Financial Crisis Impact," Journal of Emerging Market Finance, Institute for Financial Management and Research, vol. 17(1), pages 130-158, April.
    10. Navaz Naghavi & Muhammad Shujaat Mubarik & Devinder Kaur, 2018. "Financial Liberalization And Stock Market Efficiency: Measuring The Threshold Effects Of Governance," Annals of Financial Economics (AFE), World Scientific Publishing Co. Pte. Ltd., vol. 13(04), pages 1-24, December.
    11. Caihong Xu & Dong Zhang, 2019. "Market openness and market quality in gold markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 39(3), pages 384-401, March.
    12. Fabrice Barthélémy & Charles-Olivier Amédée-Manesme & Jean-Luc Prigent, 2015. "Real Estate Investment: Market Volatility and Optimal Holding Period under Risk Aversion," THEMA Working Papers 2015-21, THEMA (THéorie Economique, Modélisation et Applications), Université de Cergy-Pontoise.
    13. Sensoy, Ahmet & Aras, Guler & Hacihasanoglu, Erk, 2015. "Predictability dynamics of Islamic and conventional equity markets," The North American Journal of Economics and Finance, Elsevier, vol. 31(C), pages 222-248.
    14. Jasman Tuyon & Zamri Ahmada, 2016. "Behavioural finance perspectives on Malaysian stock market efficiency," Borsa Istanbul Review, Research and Business Development Department, Borsa Istanbul, vol. 16(1), pages 43-61, March.
    15. Gianluca Marcato & Stanimira Milcheva & Chen Zheng, 2018. "Urban Economic Openness and IPO Underpricing," The Journal of Real Estate Finance and Economics, Springer, vol. 56(3), pages 325-351, April.
    16. Sensoy, Ahmet & Tabak, Benjamin M., 2015. "Time-varying long term memory in the European Union stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 436(C), pages 147-158.
    17. Badar Nadeem Ashraf & Sidra Arshad & Liang Yan, 2017. "Trade Openness and Bank Risk-Taking Behavior: Evidence from Emerging Economies," JRFM, MDPI, vol. 10(3), pages 1-18, July.
    18. Camelia Oprean, 2012. "Testing the financial market informational efficiency in emerging states," Review of Applied Socio-Economic Research, Pro Global Science Association, vol. 4(2), pages 181-190, Decembre.
    19. Tshikalange, Mulanga & Bonga-Bonga, Lumengo, 2023. "The determinants of the dynamic correlation between foreign exchange and equity markets: Cross-Country comparisons," MPRA Paper 118401, University Library of Munich, Germany.
    20. Ebenezer Boateng & Emmanuel Asafo-Adjei & John Gartchie Gatsi & ªtefan Cristian Gherghina & Liliana Nicoleta Simionescu, 2022. "Multifrequency-based non-linear approach to analyzing implied volatility transmission across global financial markets," Oeconomia Copernicana, Institute of Economic Research, vol. 13(3), pages 699-743, September.
    21. Mohammed Mizanur Rahman & Munni Begum & Badar Nadeem Ashraf & Md. Abdul Kaium Masud, 2020. "Does Trade Openness Affect Bank Risk-Taking Behavior? Evidence from BRICS Countries," Economies, MDPI, vol. 8(3), pages 1-30, September.
    22. 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.
    23. Navaz Naghavi & Wee-Yeap Lau, 2014. "Exploring the nexus between financial openness and informational efficiency -- does the quality of institution matter?," Applied Economics, Taylor & Francis Journals, vol. 46(7), pages 674-685, March.
    24. Narayan, Paresh Kumar & Phan, Dinh Hoang Bach & Bannigidadmath, Deepa, 2017. "Is the profitability of Indian stocks compensation for risks?," Emerging Markets Review, Elsevier, vol. 31(C), pages 47-64.
    25. Ashraf, Badar Nadeem, 2018. "Do trade and financial openness matter for financial development? Bank-level evidence from emerging market economies," Research in International Business and Finance, Elsevier, vol. 44(C), pages 434-458.
    26. Tongurai, Jittima & Vithessonthi, Chaiporn, 2023. "Financial openness and financial market development," Journal of Multinational Financial Management, Elsevier, vol. 67(C).
    27. Tran, Thi Bich Ngoc, 2017. "Speculative bubbles in emerging stock markets and macroeconomic factors: A new empirical evidence for Asia and Latin America," Research in International Business and Finance, Elsevier, vol. 42(C), pages 454-467.
    28. A. Sensoy & Benjamin M. Tabak, 2013. "How much random does European Union walk? A time-varying long memory analysis," Working Papers Series 342, Central Bank of Brazil, Research Department.

  27. Kim, Jae H. & Wong, Kevin & Athanasopoulos, George & Liu, Shen, 2011. "Beyond point forecasting: Evaluation of alternative prediction intervals for tourist arrivals," International Journal of Forecasting, Elsevier, vol. 27(3), pages 887-901, July.
    See citations under working paper version above.
  28. Kim, Jae H. & Fraser, Iain & Hyndman, Rob J., 2011. "Improved interval estimation of long run response from a dynamic linear model: A highest density region approach," Computational Statistics & Data Analysis, Elsevier, vol. 55(8), pages 2477-2489, August.
    See citations under working paper version above.
  29. Abul Shamsuddin & Jae H. Kim, 2010. "Short‐Horizon Return Predictability in International Equity Markets," The Financial Review, Eastern Finance Association, vol. 45(2), pages 469-484, May.
    See citations under working paper version above.
  30. Ji, Philip Inyeob & Kim, Jae H., 2009. "Real interest rate linkages in the Pacific-Basin region," International Review of Economics & Finance, Elsevier, vol. 18(3), pages 440-448, June.
    See citations under working paper version above.
  31. Kim, Jae H., 2009. "Automatic variance ratio test under conditional heteroskedasticity," Finance Research Letters, Elsevier, vol. 6(3), pages 179-185, September.

    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. 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.
    4. 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).
    5. 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.
    6. Kim, Jae H. & Shamsuddin, Abul & Lim, Kian-Ping, 2011. "Stock return predictability and the adaptive markets hypothesis: Evidence from century-long U.S. data," Journal of Empirical Finance, Elsevier, vol. 18(5), pages 868-879.
    7. Amélie Charles & Olivier Darné & Jae H. Kim & Etienne Redor, 2016. "Stock Exchange Mergers and Market," Post-Print hal-01238707, HAL.
    8. 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.
    9. Omid Sabbaghi & Navid Sabbaghi, 2017. "The Chicago Climate Exchange and market efficiency: an empirical analysis," Environmental Economics and Policy Studies, Springer;Society for Environmental Economics and Policy Studies - SEEPS, vol. 19(4), pages 711-734, October.
    10. Nadarajah, Saralees & Chu, Jeffrey, 2017. "On the inefficiency of Bitcoin," Economics Letters, Elsevier, vol. 150(C), pages 6-9.
    11. 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.
    12. Andrew Phiri, 2022. "Changing efficiency of BRICS currency markets during the COVID-19 pandemic," Economic Change and Restructuring, Springer, vol. 55(3), pages 1673-1699, August.
    13. 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.
    14. 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.
    15. 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.
    16. 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.
    17. Rahman, Md. Lutfur & Lee, Doowon & Shamsuddin, Abul, 2017. "Time-varying return predictability in South Asian equity markets," International Review of Economics & Finance, Elsevier, vol. 48(C), pages 179-200.
    18. 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.
    19. Regis Augusto Ely, 2011. "Returns Predictability and Stock Market Efficiency in Brazil," Brazilian Review of Finance, Brazilian Society of Finance, vol. 9(4), pages 571-584.
    20. 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.
    21. 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.
    22. Stefano Martinazzi & Daniele Regoli & Andrea Flori, 2020. "A Tale of Two Layers: The Mutual Relationship between Bitcoin and Lightning Network," Risks, MDPI, vol. 8(4), pages 1-18, December.
    23. 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.
    24. 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.
    25. Kräussl, Roman & Tugnetti, Alessandro, 2023. "Non-fungible tokens (NFTs): A review of pricing determinants, applications and opportunities," CFS Working Paper Series 693, Center for Financial Studies (CFS).
    26. Montagnoli, Alberto & de Vries, Frans P., 2010. "Carbon trading thickness and market efficiency," Energy Economics, Elsevier, vol. 32(6), pages 1331-1336, November.
    27. 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.
    28. Amélie Charles & Olivier Darné & Jae H. Kim & Etienne Redor, 2014. "Stock Exchange Mergers and Market Efficiency," Working Papers hal-00940105, HAL.
    29. Md Lutfur Rahman & Mahbub Khan & Samuel A. Vigne & Gazi Salah Uddin, 2021. "Equity return predictability, its determinants, and profitable trading strategies," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(1), pages 162-186, January.
    30. 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.
    31. Dowling, Michael, 2022. "Fertile LAND: Pricing non-fungible tokens," Finance Research Letters, Elsevier, vol. 44(C).
    32. 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.
    33. Karasiński Jacek, 2023. "The adaptive market hypothesis and the return predictability in the cryptocurrency markets," Economics and Business Review, Sciendo, vol. 9(1), pages 94-118, April.
    34. 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.
    35. Yuanyuan Zhang & Stephen Chan & Jeffrey Chu & Hana Sulieman, 2020. "On the Market Efficiency and Liquidity of High-Frequency Cryptocurrencies in a Bull and Bear Market," JRFM, MDPI, vol. 13(1), pages 1-14, January.
    36. Vidal-Tomás, David, 2022. "Which cryptocurrency data sources should scholars use?," International Review of Financial Analysis, Elsevier, vol. 81(C).
    37. Linton, Oliver & Smetanina, Ekaterina, 2016. "Testing the martingale hypothesis for gross returns," Journal of Empirical Finance, Elsevier, vol. 38(PB), pages 664-689.
    38. 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.
    39. Amélie Charles & Olivier Darné & Jae H. Kim, 2015. "Will precious metals shine ? A market efficiency perspective," Post-Print hal-01238706, HAL.
    40. Juan Benjamín Duarte Duarte & Katherine Julieth Sierra Suárez & Víctor Alfonso Rueda Ortiz, 2015. "Análisis comparativo de eficiencia entre Brasil, México y Estados Unidos," Revista Finanzas y Politica Economica, Universidad Católica de Colombia, vol. 7(2), pages 341-357, July.
    41. Amélie Charles & Olivier Darné & Jae H. Kim, 2014. "Precious metals shine? A market efficiency perspective," Working Papers hal-01010516, HAL.
    42. Brauneis, Alexander & Mestel, Roland, 2018. "Price discovery of cryptocurrencies: Bitcoin and beyond," Economics Letters, Elsevier, vol. 165(C), pages 58-61.
    43. Huai-Long Shi & Zhi-Qiang Jiang & Wei-Xing Zhou, 2016. "Time-varying return predictability in the Chinese stock market," Papers 1611.04090, arXiv.org.
    44. 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.
    45. Anselmi, Giulio & Petrella, Giovanni, 2023. "Non-fungible token artworks: More crypto than art?," Finance Research Letters, Elsevier, vol. 51(C).
    46. Wei, Wang Chun, 2018. "Liquidity and market efficiency in cryptocurrencies," Economics Letters, Elsevier, vol. 168(C), pages 21-24.
    47. 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.
    48. Maderitsch, R., 2015. "Information transmission between stock markets in Hong Kong, Europe and the US: New evidence on time- and state-dependence," Pacific-Basin Finance Journal, Elsevier, vol. 35(PA), pages 13-36.
    49. Amairi, Haifa & Zantour, Ahlem & Saadi, Samir, 2021. "Information dissemination and price discovery," Finance Research Letters, Elsevier, vol. 38(C).
    50. Ben Ammar, Imen & Hellara, Slaheddine, 2021. "Intraday interactions between high-frequency trading and price efficiency," Finance Research Letters, Elsevier, vol. 41(C).
    51. Graham Smith, 2012. "The changing and relative efficiency of European emerging stock markets," The European Journal of Finance, Taylor & Francis Journals, vol. 18(8), pages 689-708, September.
    52. 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.
    53. Flori, Andrea, 2019. "News and subjective beliefs: A Bayesian approach to Bitcoin investments," Research in International Business and Finance, Elsevier, vol. 50(C), pages 336-356.
    54. Bohl, Martin T. & Pütz, Alexander & Sulewski, Christoph, 2021. "Speculation and the informational efficiency of commodity futures markets," Journal of Commodity Markets, Elsevier, vol. 23(C).
    55. Ashok Chanabasangouda Patil & Shailesh Rastogi, 2020. "Multifractal Analysis of Market Efficiency across Structural Breaks: Implications for the Adaptive Market Hypothesis," JRFM, MDPI, vol. 13(10), pages 1-18, October.
    56. 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.
    57. Navaz Naghavi & Wee-Yeap Lau, 2014. "Exploring the nexus between financial openness and informational efficiency -- does the quality of institution matter?," Applied Economics, Taylor & Francis Journals, vol. 46(7), pages 674-685, March.
    58. Al-Khazali, Osamah M. & Pyun, Chong Soo & Kim, Daewon, 2012. "Are exchange rate movements predictable in Asia-Pacific markets? Evidence of random walk and martingale difference processes," International Review of Economics & Finance, Elsevier, vol. 21(1), pages 221-231.
    59. Bhatia, Madhur, 2023. "On the efficiency of the gold returns: An econometric exploration for India, USA and Brazil," Resources Policy, Elsevier, vol. 82(C).
    60. Nikolaos A. Kyriazis, 2019. "A Survey on Efficiency and Profitable Trading Opportunities in Cryptocurrency Markets," JRFM, MDPI, vol. 12(2), pages 1-17, April.
    61. Herrera, Gabriel Paes & Constantino, Michel & Tabak, Benjamin Miranda & Pistori, Hemerson & Su, Jen-Je & Naranpanawa, Athula, 2019. "Long-term forecast of energy commodities price using machine learning," Energy, Elsevier, vol. 179(C), pages 214-221.
    62. Urquhart, Andrew, 2016. "The inefficiency of Bitcoin," Economics Letters, Elsevier, vol. 148(C), pages 80-82.
    63. 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.
    64. Zhang, Wei & Wang, Pengfei & Li, Xiao & Shen, Dehua, 2018. "The inefficiency of cryptocurrency and its cross-correlation with Dow Jones Industrial Average," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 510(C), pages 658-670.
    65. 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.
    66. Manahov, Viktor & Urquhart, Andrew, 2021. "The efficiency of Bitcoin: A strongly typed genetic programming approach to smart electronic Bitcoin markets," International Review of Financial Analysis, Elsevier, vol. 73(C).
    67. 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.
    68. Xiaokang Hou & Shah Fahad & Peipei Zhao & Beibei Yan & Tianjun Liu, 2022. "The Trilogy of the Chinese Apple Futures Market: Price Discovery, Risk-Hedging and Cointegration," Sustainability, MDPI, vol. 14(19), pages 1-16, October.
    69. Benjamin R. Auer, 2022. "On false discoveries of standard t-tests in investment management applications," Review of Managerial Science, Springer, vol. 16(3), pages 751-768, April.
    70. Muhammad Shehryar & Furrukh Bashir & Kashif Raza & Rashid Ahmad, 2022. "Random Walk Hypothesis: An Empirical Comparison of Shari’ah and Non-Shari’ah Capital Markets of Pakistan and China," iRASD Journal of Economics, International Research Alliance for Sustainable Development (iRASD), vol. 4(3), pages 439-447, September.
    71. Andrea Flori, 2019. "Cryptocurrencies In Finance: Review And Applications," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 22(05), pages 1-22, August.
    72. 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.
    73. 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.
    74. Stéphane Goutte & David Guerreiro & Bilel Sanhaji & Sophie Saglio & Julien Chevallier, 2019. "International Financial Markets," Post-Print halshs-02183053, HAL.

  32. Kim, Jae H. & Shamsuddin, Abul, 2008. "Are Asian stock markets efficient? Evidence from new multiple variance ratio tests," Journal of Empirical Finance, Elsevier, vol. 15(3), pages 518-532, June.

    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. 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.
    3. Hatemi-J, Abdulnasser, 2012. "Is the UAE stock market integrated with the USA stock market? New evidence from asymmetric causality testing," Research in International Business and Finance, Elsevier, vol. 26(2), pages 273-280.
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    4. Vieito, João Paulo & Wong, Wing-Keung & Zhu, Zhenzhen, 2015. "Could the global financial crisis improve the performance of the G7 stocks markets?," MPRA Paper 66521, University Library of Munich, Germany.
    5. Shah, Anand & Bahri, Anu, 2022. "Metanomics: Adaptive market and volatility behaviour in Metaverse," MPRA Paper 114442, University Library of Munich, Germany.
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    2. Abounoori, Esmaiel & Shahrazi, Mahdi & Rasekhi, Saeed, 2012. "An investigation of Forex market efficiency based on detrended fluctuation analysis: A case study for Iran," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(11), pages 3170-3179.

  36. Clements, Michael P. & Kim, Jae H., 2007. "Bootstrap prediction intervals for autoregressive time series," Computational Statistics & Data Analysis, Elsevier, vol. 51(7), pages 3580-3594, April.

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    2. Nowotarski, Jakub & Weron, Rafał, 2018. "Recent advances in electricity price forecasting: A review of probabilistic forecasting," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P1), pages 1548-1568.
    3. Mohitosh Kejriwal & Xuewen Yu, 2019. "Generalized Forecasr Averaging in Autoregressions with a Near Unit Root," Purdue University Economics Working Papers 1318, Purdue University, Department of Economics.
    4. Zi‐Yi Guo, 2021. "Out‐of‐sample performance of bias‐corrected estimators for diffusion processes," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(2), pages 243-268, March.
    5. Liu, Shen & Maharaj, Elizabeth Ann & Inder, Brett, 2014. "Polarization of forecast densities: A new approach to time series classification," Computational Statistics & Data Analysis, Elsevier, vol. 70(C), pages 345-361.
    6. Alonso, Andres M. & Sipols, Ana E., 2008. "A time series bootstrap procedure for interpolation intervals," Computational Statistics & Data Analysis, Elsevier, vol. 52(4), pages 1792-1805, January.
    7. Anna Staszewska-Bystrova & Peter Winker, 2016. "Improved bootstrap prediction intervals for SETAR models," Statistical Papers, Springer, vol. 57(1), pages 89-98, March.
    8. João Henrique Gonçalves Mazzeu & Esther Ruiz & Helena Veiga, 2018. "Uncertainty And Density Forecasts Of Arma Models: Comparison Of Asymptotic, Bayesian, And Bootstrap Procedures," Journal of Economic Surveys, Wiley Blackwell, vol. 32(2), pages 388-419, April.
    9. Bertail, Patrice & Clemencon, Stephan, 2008. "Approximate regenerative-block bootstrap for Markov chains," Computational Statistics & Data Analysis, Elsevier, vol. 52(5), pages 2739-2756, January.
    10. Takada, Teruko, 2009. "Simulated minimum Hellinger distance estimation of stochastic volatility models," Computational Statistics & Data Analysis, Elsevier, vol. 53(6), pages 2390-2403, April.
    11. Stephen Haben & Julien Caudron & Jake Verma, 2021. "Probabilistic Day-Ahead Wholesale Price Forecast: A Case Study in Great Britain," Forecasting, MDPI, vol. 3(3), pages 1-37, August.
    12. Giovanni Fonseca & Federica Giummolè & Paolo Vidoni, 2021. "A note on simultaneous calibrated prediction intervals for time series," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 30(1), pages 317-330, March.
    13. Anna Staszewska‐Bystrova, 2011. "Bootstrap prediction bands for forecast paths from vector autoregressive models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 30(8), pages 721-735, December.
    14. Diego Fresoli, 2022. "Bootstrap VAR forecasts: The effect of model uncertainties," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(2), pages 279-293, March.
    15. Alonso Fernández, Andrés Modesto & Bastos, Guadalupe & García-Martos, Carolina, 2017. "BIAS correction for dynamic factor models," DES - Working Papers. Statistics and Econometrics. WS 24029, Universidad Carlos III de Madrid. Departamento de Estadística.
    16. Anna Staszewska-Bystrova, 2009. "Bootstrap Confidence Bands for Forecast Paths," Working Papers 024, COMISEF.
    17. Gonçalves Mazzeu, Joao Henrique & Ruiz Ortega, Esther & Veiga, Helena, 2015. "Model uncertainty and the forecast accuracy of ARMA models: A survey," DES - Working Papers. Statistics and Econometrics. WS ws1508, Universidad Carlos III de Madrid. Departamento de Estadística.
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    2. Kuttu, Saint, 2017. "Time-varying conditional discrete jumps in emerging African equity markets," Global Finance Journal, Elsevier, vol. 32(C), pages 35-54.
    3. Shaista Arshad & Omair Haroon & Syed Aun R. Rizvi, 2019. "Understanding Asian Emerging Stock Markets," Bulletin of Monetary Economics and Banking, Bank Indonesia, vol. 0(12th BMEB), pages 1-16, January.
    4. Ghada Abbas, 2014. "Testing Random Walk Behavior in the Damascus Securities Exchange," International Journal of Academic Research in Accounting, Finance and Management Sciences, Human Resource Management Academic Research Society, International Journal of Academic Research in Accounting, Finance and Management Sciences, vol. 4(4), pages 317-325, October.
    5. 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.
    6. 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.
    7. 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.
    8. Omid Sabbaghi & Navid Sabbaghi, 2017. "The Chicago Climate Exchange and market efficiency: an empirical analysis," Environmental Economics and Policy Studies, Springer;Society for Environmental Economics and Policy Studies - SEEPS, vol. 19(4), pages 711-734, October.
    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. Abullah M. Noman & Minhaz U. Ahmed, 2008. "Efficiency of the foreign exchange markets in South Asian Countries," AIUB Bus Econ Working Paper Series AIUB-BUS-ECON-2008-18, American International University-Bangladesh (AIUB), Office of Research and Publications (ORP), revised Jun 2008.
    11. 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.
    12. OlaOluwa S. Yaya & Oluwasegun B. Adekoya & Xuan Vinh Vo & Mamdouh Abdulaziz Saleh Al‐Faryan, 2024. "Stock Market Efficiency in Asia: Evidence from the Narayan–Liu–Westerlund's GARCH‐based unit root test," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 29(1), pages 91-101, January.
    13. Benjamin Auer & Martin Schuster, 2011. "Does the financial crisis influence the random walk behaviour of international stock markets?," Applied Economics Letters, Taylor & Francis Journals, vol. 18(4), pages 319-323.
    14. 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.
    15. Hiremath, Gourishankar S & Bandi, Kamaiah, 2010. "Some Further Evidence on the Behaviour of Stock Returns in India," MPRA Paper 48518, University Library of Munich, Germany.
    16. 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.
    17. 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.
    18. Rahman, Md. Lutfur & Lee, Doowon & Shamsuddin, Abul, 2017. "Time-varying return predictability in South Asian equity markets," International Review of Economics & Finance, Elsevier, vol. 48(C), pages 179-200.
    19. Taipalus, Katja, 2012. "Detecting asset price bubbles with time-series methods," Bank of Finland Scientific Monographs, Bank of Finland, volume 0, number sm2012_047.
    20. 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.
    21. José A. Roldán-Casas & Mª B. García-Moreno García, 2022. "A procedure for testing the hypothesis of weak efficiency in financial markets: a Monte Carlo simulation," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 31(5), pages 1289-1327, December.
    22. Amélie Charles & Olivier Darné, 2009. "Variance‐Ratio Tests Of Random Walk: An Overview," Journal of Economic Surveys, Wiley Blackwell, vol. 23(3), pages 503-527, July.
    23. Muhammad A. Cheema & Gilbert V. Nartea, 2017. "Cross-Sectional and Time-Series Momentum Returns and Market Dynamics: Are Islamic Stocks Different?," Working Papers in Economics 17/14, University of Canterbury, Department of Economics and Finance.
    24. 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.
    25. Yaya, OlaOluwa S. & Vo, Xuan Vinh & Adekoya, Oluwasegun B., 2021. "Market Efficiency of Asian Stocks: Evidence based on Narayan-Liu-Westerlund GARCH-based Unit root test," MPRA Paper 109828, University Library of Munich, Germany.
    26. Ritesh Kumar Mishra & Sanjay Sehgal & N.R. Bhanumurthy, 2011. "A search for long‐range dependence and chaotic structure in Indian stock market," Review of Financial Economics, John Wiley & Sons, vol. 20(2), pages 96-104, May.
    27. Hellström, Jörgen & Liu, Yuna & Sjögren, Tomas, 2016. "Stock exchange mergers and weak-form information efficiency: Evidence from the OMX Nordic and Baltic consolidation," Umeå Economic Studies 923, Umeå University, Department of Economics.
    28. Fathia Elleuch Lahyani, 2014. "Are MENA and Pacific Basin Stock Equity Markets Predictable?," SAGE Open, , vol. 4(4), pages 21582440145, December.
    29. Montagnoli, Alberto & de Vries, Frans P., 2010. "Carbon trading thickness and market efficiency," Energy Economics, Elsevier, vol. 32(6), pages 1331-1336, November.
    30. 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.
    31. Nartea, Gilbert V. & Valera, Harold Glenn A. & Valera, Maria Luisa G., 2021. "Mean reversion in Asia-Pacific stock prices: New evidence from quantile unit root tests," International Review of Economics & Finance, Elsevier, vol. 73(C), pages 214-230.
    32. Kuttu, Saint, 2018. "Modelling long memory in volatility in sub-Saharan African equity markets," Research in International Business and Finance, Elsevier, vol. 44(C), pages 176-185.
    33. Alda, Mercedes, 2017. "The relationship between pension funds and the stock market: Does the aging population of Europe affect it?," International Review of Financial Analysis, Elsevier, vol. 49(C), pages 83-97.
    34. 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.
    35. Yen-Hsien Lee, 2010. "The Impact Of Deregulation On Stock Market Efficiency," The International Journal of Business and Finance Research, The Institute for Business and Finance Research, vol. 4(2), pages 165-176.
    36. Azubuike Samuel Agbam, 2015. "Tests of Random Walk and Efficient Market Hypothesis in Developing Economies: Evidence from Nigerian Capital Market," International Journal of Management Sciences, Research Academy of Social Sciences, vol. 5(1), pages 1-53.
    37. 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.
    38. Md Lutfur Rahman & Mahbub Khan & Samuel A. Vigne & Gazi Salah Uddin, 2021. "Equity return predictability, its determinants, and profitable trading strategies," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(1), pages 162-186, January.
    39. Siddique, Maryam, 2023. "Does the Adaptive Market Hypothesis Exist in Equity Market? Evidence from Pakistan Stock Exchange," OSF Preprints 9b5dx, Center for Open Science.
    40. 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.
    41. Urquhart, Andrew & Hudson, Robert, 2013. "Efficient or adaptive markets? Evidence from major stock markets using very long run historic data," International Review of Financial Analysis, Elsevier, vol. 28(C), pages 130-142.
    42. Dzung Phan Tran Trung & Hung Pham Quang, 2019. "Adaptive Market Hypothesis: Evidence from the Vietnamese Stock Market," JRFM, MDPI, vol. 12(2), pages 1-16, May.
    43. Arshad, Shaista & Rizvi, Syed Aun R., 2015. "The troika of business cycle, efficiency and volatility. An East Asian perspective," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 419(C), pages 158-170.
    44. Graham Smith, 2008. "Liquidity And The Informational Efficiency Of African Stock Markets," South African Journal of Economics, Economic Society of South Africa, vol. 76(2), pages 161-175, June.
    45. Ben Rejeb, Aymen & Boughrara, Adel, 2013. "Financial liberalization and stock markets efficiency: New evidence from emerging economies," Emerging Markets Review, Elsevier, vol. 17(C), pages 186-208.
    46. 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.
    47. Andrew Urquhart, 2017. "How predictable are precious metal returns?," The European Journal of Finance, Taylor & Francis Journals, vol. 23(14), pages 1390-1413, November.
    48. Al-Faryan, Mamdouh Abdulaziz Saleh & Dockery, Everton, 2020. "Testing for efficiency in the Saudi stock market: does corporate governance change matter?," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, issue Latest Ar, pages 1-30.
    49. 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.
    50. Abdelbari El Khamlichi & Kabir Sarkar Humayun & Mohamed Arouri & Frédéric Teulon, 2014. "Are Islamic equity indices more efficient than their conventional counterparts ? Evidence from major global index families," Working Papers 2014-91, Department of Research, Ipag Business School.
    51. Chang, Hao-Wen & Chiang, Yi-Chein & Ke, Mei-Chu & Wang, Ming-Hui & Nguyen, Tien-Trung, 2023. "Market efficiency of Asian stock markets during the financial crisis and non-financial crisis periods," International Review of Economics & Finance, Elsevier, vol. 83(C), pages 312-329.
    52. Sheereen Fauzel, 2016. "A Generalized Autoregressive Conditional Heteroscedastic Approach for the Assessment of Weak-form-efficiency and Seasonality Effect: Evidence from Mauritius," International Journal of Economics and Financial Issues, Econjournals, vol. 6(2), pages 745-755.
    53. Sulaiman T. Al-Abduljader, 2019. "Interdependence of Securitized Real Estate in Frontier Markets," International Real Estate Review, Global Social Science Institute, vol. 22(1), pages 83-108.
    54. 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.
    55. Wang, Zi-Mei & Chiao, Chaoshin & Chang, Ya-Ting, 2012. "Technical analyses and order submission behaviors: Evidence from an emerging market," International Review of Economics & Finance, Elsevier, vol. 24(C), pages 109-128.
    56. Taipalus, Katja, 2012. "Signaling asset price bubbles with time-series methods," Bank of Finland Research Discussion Papers 7/2012, Bank of Finland.
    57. Nidhi Choudhary & Girish K. Nair & Harsh Purohit, 2015. "Volatility In Copper Prices In India," Annals of Financial Economics (AFE), World Scientific Publishing Co. Pte. Ltd., vol. 10(02), pages 1-26, December.
    58. Onali, Enrico & Goddard, John, 2009. "Unifractality and multifractality in the Italian stock market," International Review of Financial Analysis, Elsevier, vol. 18(4), pages 154-163, September.
    59. Yiuman Tse & Jose A. Gutierrez, 2009. "Where does Volatility and Return Come From? The Case of Asian ETFs," Working Papers 0063, College of Business, University of Texas at San Antonio.
    60. Parthajit Kayal & S. Maheswaran, 2018. "Speed of Price Adjustment towards Market Efficiency: Evidence from Emerging Countries," Journal of Emerging Market Finance, Institute for Financial Management and Research, vol. 17(1_suppl), pages 112-135, April.
    61. A.S.M. Sohel Azad, 2009. "Efficiency, Cointegration and Contagion in Equity Markets: Evidence from China, Japan and South Korea," Asian Economic Journal, East Asian Economic Association, vol. 23(1), pages 93-118, March.
    62. 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.
    63. Jasman Tuyon & Zamri Ahmada, 2016. "Behavioural finance perspectives on Malaysian stock market efficiency," Borsa Istanbul Review, Research and Business Development Department, Borsa Istanbul, vol. 16(1), pages 43-61, March.
    64. 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.
    65. Anagnostidis, P. & Varsakelis, C. & Emmanouilides, C.J., 2016. "Has the 2008 financial crisis affected stock market efficiency? The case of Eurozone," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 447(C), pages 116-128.
    66. RIZWAN QAMAR Muhammad & SHEIKH Ali Nawaz, 2014. "Random Walk Behavior Of Emerging Stocks Markets: Evidence From Karachi Stock Exchange," Studies in Business and Economics, Lucian Blaga University of Sibiu, Faculty of Economic Sciences, vol. 9(3), pages 97-106, December.
    67. 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.
    68. Hiremath, Gourishankar S & Bandi, Kamaiah, 2009. "On the random walk characteristics of stock returns in India," MPRA Paper 46499, University Library of Munich, Germany.
    69. Alhashel, Bader S. & Almudhaf, Fahad W. & Hansz, J. Andrew, 2018. "Can technical analysis generate superior returns in securitized property markets? Evidence from East Asia markets," Pacific-Basin Finance Journal, Elsevier, vol. 47(C), pages 92-108.
    70. Siva Kiran & Prabhakar Rao.R, 2019. "Analysis of Stock Market Efficiency in Emerging Markets: Evidence from BRICS," Romanian Economic Journal, Department of International Business and Economics from the Academy of Economic Studies Bucharest, vol. 22(72), pages 60-77, June.
    71. Ying-Jiuan Wong & Chi-Feng Wang, 2018. "Is an overconfident CEO good for advertising investments?," Australian Journal of Management, Australian School of Business, vol. 43(3), pages 439-455, August.
    72. Chiang, Shu-Mei & Lee, Yen-Hsien & Su, Hsin-Mei & Tzou, Yi-Pin, 2010. "Efficiency tests of foreign exchange markets for four Asian Countries," Research in International Business and Finance, Elsevier, vol. 24(3), pages 284-294, September.
    73. Choi, Sun-Yong, 2021. "Analysis of stock market efficiency during crisis periods in the US stock market: Differences between the global financial crisis and COVID-19 pandemic," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 574(C).
    74. Muhammad Naeem Shahid, 2022. "COVID-19 and adaptive behavior of returns: evidence from commodity markets," Palgrave Communications, Palgrave Macmillan, vol. 9(1), pages 1-15, December.
    75. Ursu Iuliana Maria & Bilti Raluca Simina, 2016. "Trading Old for New: Econobiology and Econophysics as Explanatory Frameworks of Current Financial System," Journal of Heterodox Economics, Sciendo, vol. 3(2), pages 63-73, December.
    76. Gutierrez, Jose A. & Martinez, Valeria & Tse, Yiuman, 2009. "Where does return and volatility come from? The case of Asian ETFs," International Review of Economics & Finance, Elsevier, vol. 18(4), pages 671-679, October.
    77. Han-Ching Huang & Yong-Chern Su & Tze-Yi Lin, 2016. "Market Efficiency of Commercial Bank in Financial Crisis," International Journal of Economics and Financial Issues, Econjournals, vol. 6(2), pages 756-764.
    78. Aumeboonsuke, Vesarach & Dryver, Arthur L., 2014. "The importance of using a test of weak-form market efficiency that does not require investigating the data first," International Review of Economics & Finance, Elsevier, vol. 33(C), pages 350-357.
    79. Bley, Jorg, 2011. "Are GCC stock markets predictable?," Emerging Markets Review, Elsevier, vol. 12(3), pages 217-237, September.
    80. Kearney, Colm, 2012. "Emerging markets research: Trends, issues and future directions," Emerging Markets Review, Elsevier, vol. 13(2), pages 159-183.
    81. Panha Heng & Scott J. Niblock, 2014. "Trading with Tigers: A Technical Analysis of Southeast Asian Stock Index Futures," International Economic Journal, Taylor & Francis Journals, vol. 28(4), pages 679-692, December.
    82. Amelie Charles & Olivier Darne, 2009. "Testing for Random Walk Behavior in Euro Exchange Rates," Economie Internationale, CEPII research center, issue 119, pages 25-45.
    83. Yu, Hao & Nartea, Gilbert V. & Gan, Christopher & Yao, Lee J., 2013. "Predictive ability and profitability of simple technical trading rules: Recent evidence from Southeast Asian stock markets," International Review of Economics & Finance, Elsevier, vol. 25(C), pages 356-371.
    84. Khan, Walayet & Vieito, João Paulo, 2012. "Stock exchange mergers and weak form of market efficiency: The case of Euronext Lisbon," International Review of Economics & Finance, Elsevier, vol. 22(1), pages 173-189.
    85. Janet Jyothi Dsouza & T. Mallikarjunappa, 2015. "Does the Indian Stock Market Exhibit Random Walk?," Paradigm, , vol. 19(1), pages 1-20, June.
    86. Azad, A.S.M. Sohel, 2009. "Random walk and efficiency tests in the Asia-Pacific foreign exchange markets: Evidence from the post-Asian currency crisis data," Research in International Business and Finance, Elsevier, vol. 23(3), pages 322-338, September.
    87. Manahov, Viktor & Urquhart, Andrew, 2021. "The efficiency of Bitcoin: A strongly typed genetic programming approach to smart electronic Bitcoin markets," International Review of Financial Analysis, Elsevier, vol. 73(C).
    88. 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.
    89. Kemp-Benedict, Eric, 2014. "A Kaleckian Model with Intermediate Goods," MPRA Paper 57076, University Library of Munich, Germany.
    90. 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.
    91. Tabak, Benjamin M. & Lima, Eduardo J.A., 2009. "Market efficiency of Brazilian exchange rate: Evidence from variance ratio statistics and technical trading rules," European Journal of Operational Research, Elsevier, vol. 194(3), pages 814-820, May.

  39. Kelvin Balcombe & Iain Fraser & Jae Kim, 2006. "Estimating technical efficiency of Australian dairy farms using alternative frontier methodologies," Applied Economics, Taylor & Francis Journals, vol. 38(19), pages 2221-2236.

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    1. Vuciterna, Rina & Thomsen, Michael & Popp, Jennie & Musliu, Arben, 2017. "Efficiency and Competitiveness of Kosovo Raspberry Producers," 2017 Annual Meeting, February 4-7, 2017, Mobile, Alabama 252770, Southern Agricultural Economics Association.
    2. Balcombe, Kelvin George & Doucouliagos, Hristos & Fraser, Iain, 2007. "Input usage, output mix and industry deregulation: an analysis of the Australian dairy manufacturing industry," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 51(2), pages 1-20.
    3. Chumpitaz, Ruben & Kerstens, Kristiaan & Paparoidamis, Nicholas & Staat, Matthias, 2010. "Comparing efficiency across markets: An extension and critique of the methodology," European Journal of Operational Research, Elsevier, vol. 205(3), pages 719-728, September.
    4. Vu Hoang Linh, 2012. "Efficiency of rice farming households in Vietnam," International Journal of Development Issues, Emerald Group Publishing Limited, vol. 11(1), pages 60-73, April.
    5. Olga Murova & Benaissa Chidmi, 2013. "Technical efficiency of US dairy farms and federal government programs," Applied Economics, Taylor & Francis Journals, vol. 45(7), pages 839-847, March.
    6. Juan Cabas Monje & Bouali Guesmi & Amer Ait Sidhoum & José María Gil, 2023. "Measuring technical efficiency of Spanish pig farming: Quantile stochastic frontier approach," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 67(4), pages 688-703, October.
    7. Geys, Benny & Moesen, Wim, 2008. "Measuring local government technical (in)efficiency: An application and comparison of FDH, DEA and econometric approaches," Discussion Papers, Research Unit: Market Processes and Governance SP II 2008-21, WZB Berlin Social Science Center.
    8. Seongho Song & David Yi, 2011. "The fundraising efficiency in U.S. non-profit art organizations: an application of a Bayesian estimation approach using the stochastic frontier production model," Journal of Productivity Analysis, Springer, vol. 35(2), pages 171-180, April.
    9. Erol Taymaz & Ebru Voyvoda & Kamil Yilmaz, 2008. "Turkiye Imalat Sanayiinde Yapisal Dönüsüm ve Teknolojik Degisme Dinamikleri," ERC Working Papers 0804, ERC - Economic Research Center, Middle East Technical University, revised Jun 2008.
    10. Murova, Olga I. & Chidmi, Benaissa, 2008. "Impacts of Federal Government Programs and Specific Farm Variables on Technical Effiicency of Dairy Farms," 2009 Annual Meeting, January 31-February 3, 2009, Atlanta, Georgia 46822, Southern Agricultural Economics Association.
    11. Kelly, E & Shalloo, L & Geary, U & Kinsella, A. & Thorne, F & Wallace, M, 2013. "An analysis of the factors associated with technical and scale efficiency of Irish dairy farms," International Journal of Agricultural Management, Institute of Agricultural Management, vol. 2(3), pages 1-11, April.
    12. Hien Thu Pham & Nhan Buu Phan & Shino Takayama, 2020. "Productivity, Efficiency and Firm Size Distribution: Evidence from Vietnam," Discussion Papers Series 617, School of Economics, University of Queensland, Australia.
    13. Sauer, J. & Davidova, S. & Gorton, M., 2013. "Land Fragmentation and Market Integration- Heterogenous Technologies in Kosovo," Proceedings “Schriften der Gesellschaft für Wirtschafts- und Sozialwissenschaften des Landbaues e.V.”, German Association of Agricultural Economists (GEWISOLA), vol. 48, March.
    14. Artur Wilczynski & Ewa Koloszycz & Michal Switlyk, 2020. "Technical Efficiency of Dairy Farms: An Empirical Study of Producers in Poland," European Research Studies Journal, European Research Studies Journal, vol. 0(1), pages 117-127.
    15. Sauer, Johannes & Davidova, Sophia & Gorton, Matthew, 2012. "Land Fragmentation, Market Integration and Farm Efficiency: Empirical Evidence from Kosovo," 2012 Annual Meeting, August 12-14, 2012, Seattle, Washington 123236, Agricultural and Applied Economics Association.
    16. Johannes Sauer, 2011. "The Empirical Identification of Heterogenous Technologies and Technical Change," Post-Print hal-00768585, HAL.
    17. Świtłyk, Michał, 2021. "Using the Färe-Primont Index to Measure Changes in Total Factor Productivity of Dairy Farms," Problems of Agricultural Economics / Zagadnienia Ekonomiki Rolnej 319786, Institute of Agricultural and Food Economics - National Research Institute (IAFE-NRI).
    18. Michael S. Rimler & Seongho Song & David T. Yi, 2010. "Estimating Production Efficiency in Men’s NCAA College Basketball: A Bayesian Approach," Journal of Sports Economics, , vol. 11(3), pages 287-315, June.
    19. Sauer, Johannes & Davidova, Sophia & Gorton, Matthew, 2012. "Heterogeneous Technologies as an Answer to Market and Price Risk: The Case of Kosovo," 123rd Seminar, February 23-24, 2012, Dublin, Ireland 122509, European Association of Agricultural Economists.
    20. Johannes Sauer & Catherine J. Morrison Paul, 2013. "The empirical identification of heterogeneous technologies and technical change," Applied Economics, Taylor & Francis Journals, vol. 45(11), pages 1461-1479, April.
    21. Fabian Frick & Johannes Sauer, 2021. "Technological Change in Dairy Farming with Increased Price Volatility," Journal of Agricultural Economics, Wiley Blackwell, vol. 72(2), pages 564-588, June.
    22. Lucio Cecchini & Francesco Romagnoli & Massimo Chiorri & Biancamaria Torquati, 2023. "Eco-Efficiency and Its Determinants: The Case of the Italian Beef Cattle Sector," Agriculture, MDPI, vol. 13(5), pages 1-18, May.

  40. Ahmed, Kamran & Kim, Jae H. & Henry, Darren, 2006. "International cross-listings by Australian firms: A stochastic dominance analysis of equity returns," Journal of Multinational Financial Management, Elsevier, vol. 16(5), pages 494-508, December.

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    2. Banalieva, Elitsa R. & Robertson, Christopher J., 2010. "Performance, diversity, and multiplicity of foreign cross-listing portfolios," International Business Review, Elsevier, vol. 19(6), pages 531-547, December.
    3. Cécile Carpentier & Jean-François L'Her & Jean-Marc Suret, 2009. "Long-run Performance Following Cross-Listing: A Re-examination," CIRANO Working Papers 2007s-25, CIRANO.

  41. Kim, Jae H., 2006. "Wild bootstrapping variance ratio tests," Economics Letters, Elsevier, vol. 92(1), pages 38-43, July.

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    1. Cheteni, Priviledge, 2013. "Non-linearity behaviour of the ALBI Index: A case of Johannesburg Stock Exchange in South Africa," MPRA Paper 56369, University Library of Munich, Germany.
    2. 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.
    3. 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).
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    5. 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).
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    7. 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.
    8. Shah, Anand & Bahri, Anu, 2022. "Metanomics: Adaptive market and volatility behaviour in Metaverse," MPRA Paper 114442, University Library of Munich, Germany.
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    10. Omid Sabbaghi & Navid Sabbaghi, 2017. "The Chicago Climate Exchange and market efficiency: an empirical analysis," Environmental Economics and Policy Studies, Springer;Society for Environmental Economics and Policy Studies - SEEPS, vol. 19(4), pages 711-734, October.
    11. Amélie Charles & Olivier Darné, 2009. "The random walk hypothesis for Chinese stock markets: Evidence from variance ratio tests," Post-Print hal-00771080, HAL.
    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.
    13. Benjamin Auer & Martin Schuster, 2011. "Does the financial crisis influence the random walk behaviour of international stock markets?," Applied Economics Letters, Taylor & Francis Journals, vol. 18(4), pages 319-323.
    14. 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.
    15. Irina Syssoyeva-Masson & João de Sousa Andrade, 2017. "The Effect of Public Debt on Growth in Multiple Regimes in the Presence of Long-Memory and Non-Stationary Debt Series," CeBER Working Papers 2017-07, Centre for Business and Economics Research (CeBER), University of Coimbra.
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    22. 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.
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    24. Dumitru-Nicusor Carausu, 2016. "European Integration And Capital Market Efficiency In Cee Countries," Annals of Faculty of Economics, University of Oradea, Faculty of Economics, vol. 1(1), pages 661-670, July.
    25. Hellström, Jörgen & Liu, Yuna & Sjögren, Tomas, 2016. "Stock exchange mergers and weak-form information efficiency: Evidence from the OMX Nordic and Baltic consolidation," Umeå Economic Studies 923, Umeå University, Department of Economics.
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    28. Shynkevich, Andrei, 2012. "Short-term predictability of equity returns along two style dimensions," Journal of Empirical Finance, Elsevier, vol. 19(5), pages 675-685.
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    35. Md Lutfur Rahman & Mahbub Khan & Samuel A. Vigne & Gazi Salah Uddin, 2021. "Equity return predictability, its determinants, and profitable trading strategies," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(1), pages 162-186, January.
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    40. 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.
    41. 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.
    42. Andrew Urquhart, 2017. "How predictable are precious metal returns?," The European Journal of Finance, Taylor & Francis Journals, vol. 23(14), pages 1390-1413, November.
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    48. Amélie Charles & Olivier Darné & Jae H. Kim, 2015. "Will precious metals shine ? A market efficiency perspective," Post-Print hal-01238706, HAL.
    49. Penasse, J.N.G. & Renneboog, L.D.R., 2014. "Bubbles and Trading Frenzies : Evidence from the Art Market," Other publications TiSEM 386dd5e7-e672-4d9d-829c-6, Tilburg University, School of Economics and Management.
    50. Michael Jetter & Alex Nikolsko-Rzhevskyy & Olena Ogrokhina, 2019. "Can policy shifts explain the forward discount puzzle?," Empirical Economics, Springer, vol. 57(6), pages 1891-1909, December.
    51. Amélie Charles & Olivier Darné & Jae H. Kim, 2014. "Precious metals shine? A market efficiency perspective," Working Papers hal-01010516, HAL.
    52. Charles B. Moss & James F. Oehmke & Alexandre Lyambabaje & Andrew Schmitz, 2016. "Distribution of Budget Shares for Food: An Application of Quantile Regression to Food Security 1," Econometrics, MDPI, vol. 4(2), pages 1-12, April.
    53. Brauneis, Alexander & Mestel, Roland, 2018. "Price discovery of cryptocurrencies: Bitcoin and beyond," Economics Letters, Elsevier, vol. 165(C), pages 58-61.
    54. Huai-Long Shi & Zhi-Qiang Jiang & Wei-Xing Zhou, 2016. "Time-varying return predictability in the Chinese stock market," Papers 1611.04090, arXiv.org.
    55. Andrei Shynkevich, 2021. "Impact of bitcoin futures on the informational efficiency of bitcoin spot market," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(1), pages 115-134, January.
    56. 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.
    57. 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).
    58. Sohail Chand & Nuzhat Aftab, 2018. "Modified Variance Ratio Test for Autocorrelation in the Presence of Heteroskedasticity," Lahore Journal of Economics, Department of Economics, The Lahore School of Economics, vol. 23(1), pages 1-19, Jan-June.
    59. Xuexin WANG, 2021. "Generalized Spectral Tests for High Dimensional Multivariate Martingale Difference Hypotheses," Working Papers 2021-11-06, Wang Yanan Institute for Studies in Economics (WISE), Xiamen University.
    60. Christopher A. Hartwell, 2021. "Market Behavior in the Face of Political Violence: Evidence from Tsarist Russia," JRFM, MDPI, vol. 14(9), pages 1-13, September.
    61. Dilip Kumar & Srinivasan Maheswaran, 2014. "Are major global stock markets efficient? An application of the martingale difference hypothesis with wild bootstrap," American Journal of Finance and Accounting, Inderscience Enterprises Ltd, vol. 3(2/3/4), pages 217-233.
    62. Amairi, Haifa & Zantour, Ahlem & Saadi, Samir, 2021. "Information dissemination and price discovery," Finance Research Letters, Elsevier, vol. 38(C).
    63. Ben Ammar, Imen & Hellara, Slaheddine, 2021. "Intraday interactions between high-frequency trading and price efficiency," Finance Research Letters, Elsevier, vol. 41(C).
    64. 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.
    65. Ursu Iuliana Maria & Bilti Raluca Simina, 2016. "Trading Old for New: Econobiology and Econophysics as Explanatory Frameworks of Current Financial System," Journal of Heterodox Economics, Sciendo, vol. 3(2), pages 63-73, December.
    66. Graham Smith, 2012. "The changing and relative efficiency of European emerging stock markets," The European Journal of Finance, Taylor & Francis Journals, vol. 18(8), pages 689-708, September.
    67. Graham Smith, 2009. "Martingales in European emerging stock markets: Size, liquidity and market quality," The European Journal of Finance, Taylor & Francis Journals, vol. 15(3), pages 249-262.
    68. 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.
    69. Samih Antoine Azar, 2013. "Mean Aversion in and Persistence of Shocks to the US Dollar: Evidence from Nine Foreign Currencies," International Journal of Economics and Financial Issues, Econjournals, vol. 3(3), pages 723-733.
    70. Ufuk CAN & Zeynep Gizem CAN & Süleyman DEĞİRMEN, 2019. "Paranın Dolaşım Hızının ve Para Talebi Fonksiyonunun Ekonometrik Analizi: Türkiye Örneği," Istanbul Business Research, Istanbul University Business School, vol. 48(2), pages 218-247, November.
    71. Kim, Jae H. & Shamsuddin, Abul, 2008. "Are Asian stock markets efficient? Evidence from new multiple variance ratio tests," Journal of Empirical Finance, Elsevier, vol. 15(3), pages 518-532, June.
    72. 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.
    73. 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.
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    76. Filipovski, Vladimir & Tevdovski, Dragan, 2017. "Stock market efficiency in South Eastern Europe: testing return predictability and presence of calendar effects," MPRA Paper 76818, University Library of Munich, Germany.
    77. Graham, Michael & Peltomäki, Jarkko & Sturludóttir, Hildur, 2015. "Do capital controls affect stock market efficiency? Lessons from Iceland," International Review of Financial Analysis, Elsevier, vol. 41(C), pages 82-88.
    78. 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.
    79. Xiaokang Hou & Shah Fahad & Peipei Zhao & Beibei Yan & Tianjun Liu, 2022. "The Trilogy of the Chinese Apple Futures Market: Price Discovery, Risk-Hedging and Cointegration," Sustainability, MDPI, vol. 14(19), pages 1-16, October.
    80. Jasim Al-Ajmi & J. H. Kim, 2012. "Are Gulf stock markets efficient? Evidence from new multiple variance ratio tests," Applied Economics, Taylor & Francis Journals, vol. 44(14), pages 1737-1747, May.
    81. 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.
    82. 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.
    83. 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.
    84. Stéphane Goutte & David Guerreiro & Bilel Sanhaji & Sophie Saglio & Julien Chevallier, 2019. "International Financial Markets," Post-Print halshs-02183053, HAL.

  42. Jae Kim & Mahbuba Yeasmin, 2005. "The Size and Power of the Bias-Corrected Bootstrap Test for Regression Models with Autocorrelated Errors," Computational Economics, Springer;Society for Computational Economics, vol. 25(3), pages 255-267, June.

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    1. Chiara Consiglio & Nicoletta Massa & Valentina Sommovigo & Luigi Fusco, 2023. "Techno-Stress Creators, Burnout and Psychological Health among Remote Workers during the Pandemic: The Moderating Role of E-Work Self-Efficacy," IJERPH, MDPI, vol. 20(22), pages 1-23, November.

  43. Jae Kim, 2005. "Investigating the advertising-sales relationship in the Lydia Pinkham data: a bootstrap approach," Applied Economics, Taylor & Francis Journals, vol. 37(3), pages 347-354.

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    1. José Casals Carro & Miguel Jerez Méndez & Sonia Sotoca López, 2006. "Decomposition of state-space Model with inputs: The theory and an application to estimate the ROI of advertising," Documentos de Trabajo del ICAE 0602, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.

  44. Imad Moosa & Jae Kim, 2004. "Direct and indirect forecasting of the money multiplier and velocity of circulation in the United Kingdom," International Economic Journal, Taylor & Francis Journals, vol. 18(1), pages 103-118.

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    1. Ngomba Bodi, Francis Ghislain & Onomo, Julie, 2018. "Analyse du multiplicateur monétaire en zone CEMAC [Money multiplier analysis in CEMAC subregion]," MPRA Paper 116431, University Library of Munich, Germany.
    2. Hénock Katuala Muanza, 2020. "Stability and predictability of the monetary multiplier in the Democratic Republic of the Congo [Stabilité et prédictibilité du multiplicateur monétaire en République démocratique du Congo ]," Working Papers hal-02610767, HAL.
    3. Hénock Muanza Katuala, 2020. "Monetary Policy, Monetary Stability And Economic Growth In The Democratic Republic Of Congo [Politique Monetaire, Stabilite Monetaire Et Croissance Economique En Republique Democratique Du Congo]," Working Papers hal-02616124, HAL.

  45. Jae H. Kim, 2004. "Bias-corrected bootstrap prediction regions for vector autoregression," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 23(2), pages 141-154.

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    1. Pascual, Lorenzo & Ruiz Ortega, Esther & Fresoli, Diego Eduardo, 2011. "Bootstrap forecast of multivariate VAR models without using the backward representation," DES - Working Papers. Statistics and Econometrics. WS ws113426, Universidad Carlos III de Madrid. Departamento de Estadística.
    2. Grabowski, Daniel & Staszewska-Bystrova, Anna, 2018. "Skewness-Adjusted Bootstrap Confidence Intervals and Confidence Bands for Impulse Response Functions," VfS Annual Conference 2018 (Freiburg, Breisgau): Digital Economy 181590, Verein für Socialpolitik / German Economic Association.
    3. Bruns, Martin & Lütkepohl, Helmut, 2022. "Comparison of local projection estimators for proxy vector autoregressions," Journal of Economic Dynamics and Control, Elsevier, vol. 134(C).
    4. Liu, Shen & Maharaj, Elizabeth Ann & Inder, Brett, 2014. "Polarization of forecast densities: A new approach to time series classification," Computational Statistics & Data Analysis, Elsevier, vol. 70(C), pages 345-361.
    5. Tom Engsted & Thomas Q. Pedersen, 2014. "Bias-Correction in Vector Autoregressive Models: A Simulation Study," Econometrics, MDPI, vol. 2(1), pages 1-27, March.
    6. De Gooijer, Jan G. & Hyndman, Rob J., 2006. "25 years of time series forecasting," International Journal of Forecasting, Elsevier, vol. 22(3), pages 443-473.
    7. Helmut Lütkepohl & Anna Staszewska-Bystrova & Peter Winker, 2014. "Confidence Bands for Impulse Responses: Bonferroni versus Wald," CESifo Working Paper Series 4634, CESifo.
    8. Li, Jing, 2011. "Bootstrap prediction intervals for SETAR models," International Journal of Forecasting, Elsevier, vol. 27(2), pages 320-332.
    9. Helmut Lütkepohl & Anna Staszewska-Bystrova & Peter Winker, 2013. "Comparison of Methods for Constructing Joint Confidence Bands for Impulse Response Functions," SFB 649 Discussion Papers SFB649DP2013-031, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    10. Anna Staszewska‐Bystrova, 2011. "Bootstrap prediction bands for forecast paths from vector autoregressive models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 30(8), pages 721-735, December.
    11. Fresoli, Diego & Ruiz, Esther & Pascual, Lorenzo, 2015. "Bootstrap multi-step forecasts of non-Gaussian VAR models," International Journal of Forecasting, Elsevier, vol. 31(3), pages 834-848.
    12. Jing, Li, 2009. "Bootstrap prediction intervals for threshold autoregressive models," MPRA Paper 13086, University Library of Munich, Germany.
    13. Anna Staszewska-Bystrova, 2009. "Bootstrap Confidence Bands for Forecast Paths," Working Papers 024, COMISEF.
    14. Li, Jing, 2011. "Bootstrap prediction intervals for SETAR models," International Journal of Forecasting, Elsevier, vol. 27(2), pages 320-332, April.
    15. Mulubrhan G. Haile & Lingling Zhang & David J. Olive, 2024. "Predicting Random Walks and a Data-Splitting Prediction Region," Stats, MDPI, vol. 7(1), pages 1-11, January.
    16. Staszewska-Bystrova, Anna & Winker, Peter, 2013. "Constructing narrowest pathwise bootstrap prediction bands using threshold accepting," International Journal of Forecasting, Elsevier, vol. 29(2), pages 221-233.

  46. Kim, Jae H., 2004. "Bootstrap prediction intervals for autoregression using asymptotically mean-unbiased estimators," International Journal of Forecasting, Elsevier, vol. 20(1), pages 85-97.

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    1. Kim, Jae H. & Wong, Kevin & Athanasopoulos, George & Liu, Shen, 2011. "Beyond point forecasting: Evaluation of alternative prediction intervals for tourist arrivals," International Journal of Forecasting, Elsevier, vol. 27(3), pages 887-901, July.
    2. Liu, Shen & Maharaj, Elizabeth Ann & Inder, Brett, 2014. "Polarization of forecast densities: A new approach to time series classification," Computational Statistics & Data Analysis, Elsevier, vol. 70(C), pages 345-361.
    3. Song, Haiyan & Wen, Long & Liu, Chang, 2019. "Density tourism demand forecasting revisited," Annals of Tourism Research, Elsevier, vol. 75(C), pages 379-392.
    4. K. D. Patterson, 2007. "Bias Reduction through First-order Mean Correction, Bootstrapping and Recursive Mean Adjustment," Journal of Applied Statistics, Taylor & Francis Journals, vol. 34(1), pages 23-45.
    5. João Henrique Gonçalves Mazzeu & Esther Ruiz & Helena Veiga, 2018. "Uncertainty And Density Forecasts Of Arma Models: Comparison Of Asymptotic, Bayesian, And Bootstrap Procedures," Journal of Economic Surveys, Wiley Blackwell, vol. 32(2), pages 388-419, April.
    6. Jae H. Kim & Andrew P. Robinson, 2019. "Interval-Based Hypothesis Testing and Its Applications to Economics and Finance," Econometrics, MDPI, vol. 7(2), pages 1-22, May.
    7. De Gooijer, Jan G. & Hyndman, Rob J., 2006. "25 years of time series forecasting," International Journal of Forecasting, Elsevier, vol. 22(3), pages 443-473.
    8. Kim, Jae & Choi, In, 2015. "Unit Roots in Economic and Financial Time Series: A Re-Evaluation based on Enlightened Judgement," MPRA Paper 68411, University Library of Munich, Germany.
    9. Jan G. De Gooijer & Rob J. Hyndman, 2005. "25 Years of IIF Time Series Forecasting: A Selective Review," Monash Econometrics and Business Statistics Working Papers 12/05, Monash University, Department of Econometrics and Business Statistics.
    10. Dag Kolsrud, 2015. "A Time‐Simultaneous Prediction Box for a Multivariate Time Series," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 34(8), pages 675-693, December.
    11. Dag Kolsrud, 2007. "Time-simultaneous prediction band for a time series," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 26(3), pages 171-188.
    12. Liu, Shen & Maharaj, Elizabeth Ann, 2013. "A hypothesis test using bias-adjusted AR estimators for classifying time series in small samples," Computational Statistics & Data Analysis, Elsevier, vol. 60(C), pages 32-49.
    13. Gonçalves Mazzeu, Joao Henrique & Ruiz Ortega, Esther & Veiga, Helena, 2015. "Model uncertainty and the forecast accuracy of ARMA models: A survey," DES - Working Papers. Statistics and Econometrics. WS ws1508, Universidad Carlos III de Madrid. Departamento de Estadística.

  47. Shamsuddin, Abul F. M. & Kim, Jae H., 2003. "Integration and interdependence of stock and foreign exchange markets: an Australian perspective," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 13(3), pages 237-254, July.

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    1. Ngene, Geoffrey & Post, Jordin A. & Mungai, Ann N., 2018. "Volatility and shock interactions and risk management implications: Evidence from the U.S. and frontier markets," Emerging Markets Review, Elsevier, vol. 37(C), pages 181-198.
    2. Abdelwahab Allali & Amor Oueslati & Abdelwahed Trabelsi, 2011. "Detection of Information Flow in Major International Financial Markets by Interactivity Network Analysis," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 18(3), pages 319-344, September.
    3. Ngene, Geoffrey M. & Lee Kim, Yea & Wang, Jinghua, 2019. "Who poisons the pool? Time-varying asymmetric and nonlinear causal inference between low-risk and high-risk bonds markets," Economic Modelling, Elsevier, vol. 81(C), pages 136-147.
    4. Benjamin Mudiangombe Mudiangombe & John Weirstrass Muteba Mwamba, 2023. "Impacts of U.S. Stock Market Crash on South African Top Sector Indices, Volatility, and Market Linkages: Evidence of Copula-Based BEKK-GARCH Models," IJFS, MDPI, vol. 11(2), pages 1-19, June.
    5. Ping Wang & Tomoe Moore, 2008. "Stock Market Integration For The Transition Economies: Time‐Varying Conditional Correlation Approach," Manchester School, University of Manchester, vol. 76(s1), pages 116-133, September.
    6. Hatemi-J, Abdulnasser & Al-Mohana, Safa, 2019. "Testing for Financial Market Integration of the UAE Market with the Global Market," Economia Internazionale / International Economics, Camera di Commercio Industria Artigianato Agricoltura di Genova, vol. 72(4), pages 475-492.
    7. Yang, Ann Shawing & Pangastuti, Airin, 2016. "Stock market efficiency and liquidity: The Indonesia Stock Exchange merger," Research in International Business and Finance, Elsevier, vol. 36(C), pages 28-40.
    8. Azzam, Islam & El-Masry, Ahmed A. & Yamani, Ehab, 2023. "Foreign exchange market efficiency during COVID-19 pandemic," International Review of Economics & Finance, Elsevier, vol. 86(C), pages 717-730.
    9. Song, Yuegang & Huang, Ruixian & Paramati, Sudharshan Reddy & Zakari, Abdulrasheed, 2021. "Does economic integration lead to financial market integration in the Asian region?," Economic Analysis and Policy, Elsevier, vol. 69(C), pages 366-377.
    10. Anil Sharma & Neha Seth, 2012. "Literature review of stock market integration: a global perspective," Qualitative Research in Financial Markets, Emerald Group Publishing Limited, vol. 4(1), pages 84-122, April.
    11. Ahmed, Walid M.A., 2011. "Comovements and Causality of Sector Price Indices: Evidence from the Egyptian Stock Exchange," MPRA Paper 28127, University Library of Munich, Germany.
    12. Sudharshan Reddy Paramati & Eduardo Roca & Rakesh Gupta, 2016. "Economic integration and stock market dynamic linkages: evidence in the context of Australia and Asia," Applied Economics, Taylor & Francis Journals, vol. 48(44), pages 4210-4226, September.

  48. Kim, Jae H., 2003. "Forecasting autoregressive time series with bias-corrected parameter estimators," International Journal of Forecasting, Elsevier, vol. 19(3), pages 493-502.

    Cited by:

    1. Kim, Jae H. & Wong, Kevin & Athanasopoulos, George & Liu, Shen, 2011. "Beyond point forecasting: Evaluation of alternative prediction intervals for tourist arrivals," International Journal of Forecasting, Elsevier, vol. 27(3), pages 887-901, July.
    2. Medel, Carlos A., 2017. "Forecasting Chilean Inflation with the Hybrid New Keynesian Phillips Curve: Globalisation, Combination, and Accuracy," MPRA Paper 78439, University Library of Munich, Germany.
    3. Mohitosh Kejriwal & Xuewen Yu, 2019. "Generalized Forecasr Averaging in Autoregressions with a Near Unit Root," Purdue University Economics Working Papers 1318, Purdue University, Department of Economics.
    4. Zi‐Yi Guo, 2021. "Out‐of‐sample performance of bias‐corrected estimators for diffusion processes," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(2), pages 243-268, March.
    5. Rodolfo Cermeño, 2007. "Median-Unbiased Estimation in Panel Data: Methodology and Applications to the GDP Convergence and Purchasing Power Parity Hypotheses," Working papers DTE 407, CIDE, División de Economía.
    6. Giorgio Canarella & Stephen M. Miller & Stephen K. Pollard, 2013. "Unemployment Rate Hysteresis and the Great Recession: Exploring the Metropolitan Evidence," Working papers 2013-19, University of Connecticut, Department of Economics.
    7. K. D. Patterson, 2007. "Bias Reduction through First-order Mean Correction, Bootstrapping and Recursive Mean Adjustment," Journal of Applied Statistics, Taylor & Francis Journals, vol. 34(1), pages 23-45.
    8. Jonas Andersson, 2006. "Searching for the DGP when forecasting - Is it always meaningful for small samples?," Economics Bulletin, AccessEcon, vol. 3(28), pages 1-9.
    9. Tom Engsted & Thomas Q. Pedersen, 2014. "Bias-Correction in Vector Autoregressive Models: A Simulation Study," Econometrics, MDPI, vol. 2(1), pages 1-27, March.
    10. Kruse, Yves Robinson & Kaufmann, Hendrik, 2015. "Bias-corrected estimation in mildly explosive autoregressions," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 112897, Verein für Socialpolitik / German Economic Association.
    11. Kim, Hyeongwoo & Durmaz, Nazif, 2012. "Bias correction and out-of-sample forecast accuracy," International Journal of Forecasting, Elsevier, vol. 28(3), pages 575-586.
    12. Kruse, Robinson & Kaufmann, Hendrik & Wegener, Christoph, 2018. "Bias-corrected estimation for speculative bubbles in stock prices," Economic Modelling, Elsevier, vol. 73(C), pages 354-364.
    13. André M. Marques & Gilberto Tadeu Lima, Victor Troster, 2016. "Unemployment Persistence in OECD Countries after the Great Recession," Working Papers, Department of Economics 2016_16, University of São Paulo (FEA-USP).
    14. Medel, Carlos A., 2015. "Forecasting Inflation with the Hybrid New Keynesian Phillips Curve: A Compact-Scale Global VAR Approach," MPRA Paper 67081, University Library of Munich, Germany.
    15. De Gooijer, Jan G. & Hyndman, Rob J., 2006. "25 years of time series forecasting," International Journal of Forecasting, Elsevier, vol. 22(3), pages 443-473.
    16. Medel, Carlos & Pincheira, Pablo, 2015. "The Out-of-sample Performance of an Exact Median-Unbiased Estimator for the Near-Unity AR(1) Model," MPRA Paper 62552, University Library of Munich, Germany.
    17. João Valle e Azevedo, 2013. "Macroeconomic Forecasting Using Low-Frequency Filters," Working Papers w201301, Banco de Portugal, Economics and Research Department.
    18. Jan G. De Gooijer & Rob J. Hyndman, 2005. "25 Years of IIF Time Series Forecasting: A Selective Review," Monash Econometrics and Business Statistics Working Papers 12/05, Monash University, Department of Econometrics and Business Statistics.
    19. Gustavsson, Magnus & Österholm, Pär, 2014. "Does the labor-income process contain a unit root? Evidence from individual-specific time series," Journal of Economic Dynamics and Control, Elsevier, vol. 47(C), pages 152-167.
    20. Hendrik Kaufmannz & Robinson Kruse, 2013. "Bias-corrected estimation in potentially mildly explosive autoregressive models," CREATES Research Papers 2013-10, Department of Economics and Business Economics, Aarhus University.
    21. Falk, Barry & Roy, Anindya, 2005. "Forecasting using the trend model with autoregressive errors," International Journal of Forecasting, Elsevier, vol. 21(2), pages 291-302.
    22. Sigrunn H. Sørbye & Pedro G. Nicolau & Håvard Rue, 2022. "Finite-sample properties of estimators for first and second order autoregressive processes," Statistical Inference for Stochastic Processes, Springer, vol. 25(3), pages 577-598, October.

  49. Kim, Jae H, 2002. "Bootstrap Prediction Intervals for Autoregressive Models of Unknown or Infinite Lag Order," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 21(4), pages 265-280, July.

    Cited by:

    1. Jing Li, 2021. "Block bootstrap prediction intervals for parsimonious first‐order vector autoregression," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(3), pages 512-527, April.
    2. Clements, Michael P. & Kim, Jae H., 2007. "Bootstrap prediction intervals for autoregressive time series," Computational Statistics & Data Analysis, Elsevier, vol. 51(7), pages 3580-3594, April.
    3. Kim, Jae H., 2004. "Bootstrap prediction intervals for autoregression using asymptotically mean-unbiased estimators," International Journal of Forecasting, Elsevier, vol. 20(1), pages 85-97.
    4. Li, Jing, 2011. "Bootstrap prediction intervals for SETAR models," International Journal of Forecasting, Elsevier, vol. 27(2), pages 320-332.
    5. Anna Staszewska‐Bystrova, 2011. "Bootstrap prediction bands for forecast paths from vector autoregressive models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 30(8), pages 721-735, December.
    6. Jing, Li, 2009. "Bootstrap prediction intervals for threshold autoregressive models," MPRA Paper 13086, University Library of Munich, Germany.
    7. Anna Staszewska-Bystrova, 2009. "Bootstrap Confidence Bands for Forecast Paths," Working Papers 024, COMISEF.
    8. Li, Jing, 2011. "Bootstrap prediction intervals for SETAR models," International Journal of Forecasting, Elsevier, vol. 27(2), pages 320-332, April.

  50. Kim, Jae H, 2001. "Bootstrap-after-Bootstrap Prediction Intervals for Autoregressive Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 19(1), pages 117-128, January.

    Cited by:

    1. Kim, Jae H. & Wong, Kevin & Athanasopoulos, George & Liu, Shen, 2011. "Beyond point forecasting: Evaluation of alternative prediction intervals for tourist arrivals," International Journal of Forecasting, Elsevier, vol. 27(3), pages 887-901, July.
    2. Reeves, Jonathan J., 2005. "Bootstrap prediction intervals for ARCH models," International Journal of Forecasting, Elsevier, vol. 21(2), pages 237-248.
    3. Mohitosh Kejriwal & Xuewen Yu, 2019. "Generalized Forecasr Averaging in Autoregressions with a Near Unit Root," Purdue University Economics Working Papers 1318, Purdue University, Department of Economics.
    4. Pascual, Lorenzo & Ruiz Ortega, Esther & Fresoli, Diego Eduardo, 2011. "Bootstrap forecast of multivariate VAR models without using the backward representation," DES - Working Papers. Statistics and Econometrics. WS ws113426, Universidad Carlos III de Madrid. Departamento de Estadística.
    5. Kim, Jae H., 2003. "Forecasting autoregressive time series with bias-corrected parameter estimators," International Journal of Forecasting, Elsevier, vol. 19(3), pages 493-502.
    6. Jae H. Kim, 2004. "Bias-corrected bootstrap prediction regions for vector autoregression," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 23(2), pages 141-154.
    7. Stefan Bruder, 2014. "Comparing several methods to compute joint prediction regions for path forecasts generated by vector autoregressions," ECON - Working Papers 181, Department of Economics - University of Zurich, revised Dec 2015.
    8. Liu, Shen & Maharaj, Elizabeth Ann & Inder, Brett, 2014. "Polarization of forecast densities: A new approach to time series classification," Computational Statistics & Data Analysis, Elsevier, vol. 70(C), pages 345-361.
    9. Song, Haiyan & Wen, Long & Liu, Chang, 2019. "Density tourism demand forecasting revisited," Annals of Tourism Research, Elsevier, vol. 75(C), pages 379-392.
    10. Tom Engsted & Thomas Q. Pedersen, 2014. "Bias-Correction in Vector Autoregressive Models: A Simulation Study," Econometrics, MDPI, vol. 2(1), pages 1-27, March.
    11. Jing Li, 2021. "Block bootstrap prediction intervals for parsimonious first‐order vector autoregression," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(3), pages 512-527, April.
    12. Clements, Michael P. & Kim, Jae H., 2007. "Bootstrap prediction intervals for autoregressive time series," Computational Statistics & Data Analysis, Elsevier, vol. 51(7), pages 3580-3594, April.
    13. Anna Staszewska-Bystrova & Peter Winker, 2016. "Improved bootstrap prediction intervals for SETAR models," Statistical Papers, Springer, vol. 57(1), pages 89-98, March.
    14. João Henrique Gonçalves Mazzeu & Esther Ruiz & Helena Veiga, 2018. "Uncertainty And Density Forecasts Of Arma Models: Comparison Of Asymptotic, Bayesian, And Bootstrap Procedures," Journal of Economic Surveys, Wiley Blackwell, vol. 32(2), pages 388-419, April.
    15. Kim, Jae H., 2014. "Testing for parameter restrictions in a stationary VAR model: A bootstrap alternative," Economic Modelling, Elsevier, vol. 41(C), pages 267-273.
    16. Kim, Jae H., 2004. "Bootstrap prediction intervals for autoregression using asymptotically mean-unbiased estimators," International Journal of Forecasting, Elsevier, vol. 20(1), pages 85-97.
    17. Lee, Yun Shin & Scholtes, Stefan, 2014. "Empirical prediction intervals revisited," International Journal of Forecasting, Elsevier, vol. 30(2), pages 217-234.
    18. Li, Jing, 2011. "Bootstrap prediction intervals for SETAR models," International Journal of Forecasting, Elsevier, vol. 27(2), pages 320-332.
    19. Rushdi, Mustabshira & Kim, Jae H. & Silvapulle, Param, 2012. "ARDL bounds tests and robust inference for the long run relationship between real stock returns and inflation in Australia," Economic Modelling, Elsevier, vol. 29(3), pages 535-543.
    20. Raffaella Giacomini & Dimitris N. Politis & Halbert White, 2012. "A warp-speed method for conducting Monte Carlo experiments involving bootstrap estimators," CeMMAP working papers CWP11/12, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    21. Imad Moosa & Jae Kim, 2004. "Direct and indirect forecasting of the money multiplier and velocity of circulation in the United Kingdom," International Economic Journal, Taylor & Francis Journals, vol. 18(1), pages 103-118.
    22. Anna Staszewska‐Bystrova, 2011. "Bootstrap prediction bands for forecast paths from vector autoregressive models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 30(8), pages 721-735, December.
    23. Fresoli, Diego & Ruiz, Esther & Pascual, Lorenzo, 2015. "Bootstrap multi-step forecasts of non-Gaussian VAR models," International Journal of Forecasting, Elsevier, vol. 31(3), pages 834-848.
    24. Jae Kim & Mahbuba Yeasmin, 2005. "The Size and Power of the Bias-Corrected Bootstrap Test for Regression Models with Autocorrelated Errors," Computational Economics, Springer;Society for Computational Economics, vol. 25(3), pages 255-267, June.
    25. Jing, Li, 2009. "Bootstrap prediction intervals for threshold autoregressive models," MPRA Paper 13086, University Library of Munich, Germany.
    26. Anna Staszewska-Bystrova, 2009. "Bootstrap Confidence Bands for Forecast Paths," Working Papers 024, COMISEF.
    27. Li, Jing, 2011. "Bootstrap prediction intervals for SETAR models," International Journal of Forecasting, Elsevier, vol. 27(2), pages 320-332, April.
    28. Xu, Yuan & Zhang, Mingqing & Ye, Liangliang & Zhu, Qunxiong & Geng, Zhiqiang & He, Yan-Lin & Han, Yongming, 2018. "A novel prediction intervals method integrating an error & self-feedback extreme learning machine with particle swarm optimization for energy consumption robust prediction," Energy, Elsevier, vol. 164(C), pages 137-146.
    29. Gonçalves Mazzeu, Joao Henrique & Ruiz Ortega, Esther & Veiga, Helena, 2015. "Model uncertainty and the forecast accuracy of ARMA models: A survey," DES - Working Papers. Statistics and Econometrics. WS ws1508, Universidad Carlos III de Madrid. Departamento de Estadística.

  51. Jae H. Kim & Monique T. Ngo, 2001. "Modelling and Forecasting Monthly Airline Passenger Flows among Three Major Australian Cities," Tourism Economics, , vol. 7(4), pages 397-412, December.

    Cited by:

    1. Chunla Liu & Yingjie Qin & Yufei Wang & Yue Yu & Guanghui Li, 2022. "Spatio-Temporal Distribution of Tourism Flows and Network Analysis of Traditional Villages in Western Hunan," Sustainability, MDPI, vol. 14(13), pages 1-16, June.
    2. John Trevor Coshall, 2005. "A Selection Strategy for Modelling UK Tourism Flows by Air to European Destinations," Tourism Economics, , vol. 11(2), pages 141-158, June.
    3. Amitrajeet Batabyal, 2007. "A probabilistic analysis of a scheduling problem in the economics of tourism," Economics Bulletin, AccessEcon, vol. 12(4), pages 1-7.
    4. Coshall, John T. & Charlesworth, Richard, 2011. "A management orientated approach to combination forecasting of tourism demand," Tourism Management, Elsevier, vol. 32(4), pages 759-769.
    5. Liang Zhu & Christine Lim & Wenjun Xie & Yuan Wu, 2017. "Analysis of tourism demand serial dependence structure for forecasting," Tourism Economics, , vol. 23(7), pages 1419-1436, November.
    6. Athanasopoulos, George & Deng, Minfeng & Li, Gang & Song, Haiyan, 2014. "Modelling substitution between domestic and outbound tourism in Australia: A system-of-equations approach," Tourism Management, Elsevier, vol. 45(C), pages 159-170.

  52. Jae H. Kim & Imad Moosa, 2001. "Seasonal Behaviour of Monthly International Tourist Flows: Specification and Implications for Forecasting Models," Tourism Economics, , vol. 7(4), pages 381-396, December.

    Cited by:

    1. Kim, Jae H. & Wong, Kevin & Athanasopoulos, George & Liu, Shen, 2011. "Beyond point forecasting: Evaluation of alternative prediction intervals for tourist arrivals," International Journal of Forecasting, Elsevier, vol. 27(3), pages 887-901, July.
    2. Andrea Saayman & Ilsé Botha, 2017. "Non-linear models for tourism demand forecasting," Tourism Economics, , vol. 23(3), pages 594-613, May.
    3. Elisa Jorge-González & Enrique González-Dávila & Raquel Martín-Rivero & Domingo Lorenzo-Díaz, 2020. "Univariate and multivariate forecasting of tourism demand using state-space models," Tourism Economics, , vol. 26(4), pages 598-621, June.
    4. Yılmaz, Engin, 2015. "Forecasting tourist arrivals to Turkey," MPRA Paper 68616, University Library of Munich, Germany.
    5. Guglielmo Maria Caporale & Luis Alberiko Gil-Alana, 2019. "UK overseas visitors: Seasonality and persistence," Tourism Economics, , vol. 25(5), pages 827-831, August.
    6. Ghialy Yap, 2009. "Modelling domestic tourism demand in Australia a dynamic panel data approach," Economic Journal of Emerging Markets, Universitas Islam Indonesia, vol. 1(1), pages 1-11, April.

  53. Denzil Fiebig & Jae Kim, 2000. "Estimation and inference in sur models when the number of equations is large," Econometric Reviews, Taylor & Francis Journals, vol. 19(1), pages 105-130.

    Cited by:

    1. Alkhamisi, M.A. & Shukur, Ghazi, 2007. "Developing Ridge Parameters for SUR Models," Working Paper Series in Economics and Institutions of Innovation 80, Royal Institute of Technology, CESIS - Centre of Excellence for Science and Innovation Studies.
    2. Zeebari, Zangin & Shukur, Ghazi & Kibria, B. M. Golam, 2010. "Modified Ridge Parameters for Seemingly Unrelated Regression Model," HUI Working Papers 43, HUI Research.
    3. Benjamin Verhelst & Dirk Van den Poel, 2014. "Deep habits in consumption: a spatial panel analysis using scanner data," Empirical Economics, Springer, vol. 47(3), pages 959-976, November.
    4. Voxi Heinrich Amavilah & Antonio Rodriguez Andres, 2022. "Knowledge Economy and the Economic Performance of African Countries: A Seemingly Unrelated and Recursive Approach," Working Papers 57, The German University in Cairo, Faculty of Management Technology.
    5. Griffiths, W.E., 2001. "Bayesian Inference in the Seemingly Unrelated Regressions Models," Department of Economics - Working Papers Series 793, The University of Melbourne.
    6. Rulon D. Pope & Jeffrey T. LaFrance & Richard E. Just, 2007. "Imperfect Price Deflation in Production Systems," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 89(3), pages 738-754.
    7. Yihui Lan, 2001. "The Long-Run Value of Currencies: A Big Mac Perspective," Economics Discussion / Working Papers 01-17, The University of Western Australia, Department of Economics.
    8. Chotikapanich, D. & Griffiths, W.E. & Skeels, C.L., 2001. "Sample Size Requirements for Estimation in SUR Models," Department of Economics - Working Papers Series 794, The University of Melbourne.
    9. Zhao, Li & Xu, Xingzhong, 2017. "Generalized canonical correlation variables improved estimation in high dimensional seemingly unrelated regression models," Statistics & Probability Letters, Elsevier, vol. 126(C), pages 119-126.
    10. Yihui Lan, 2003. "The Long-Term Behaviour of Exchange Rates, Part V: The Stationarity of Exchange Rates," Economics Discussion / Working Papers 03-09, The University of Western Australia, Department of Economics.

  54. Jae H. Kim, 1999. "Forecasting Monthly Tourist Departures from Australia," Tourism Economics, , vol. 5(3), pages 277-291, September.

    Cited by:

    1. Luis Alberiko Gil-Alaña, 2010. "Tourism in South Africa. Time series persistence and the nature of shocks. Are they transitory or permament?," NCID Working Papers 06/2011, Navarra Center for International Development, University of Navarra.
    2. Duro Moreno, Juan Antonio & Turrión Prats, Judith, 2018. "Tourism seasonality worldwide," Working Papers 2072/351586, Universitat Rovira i Virgili, Department of Economics.
    3. Tihomir Stučka, 2002. "A Comparison of Two Econometric Models (OLS and SUR) for Forecasting Croatian Tourism Arrivals," Working Papers 8, The Croatian National Bank, Croatia.
    4. Saroja Selvanathan, 2007. "The effect of war and other factors on Sri Lankan tourism," Applied Economics Letters, Taylor & Francis Journals, vol. 14(1), pages 35-38.
    5. Christine Lim & Michael McAleer, 2001. "Time Series Forecasts of International Tourism Demand for Australia," ISER Discussion Paper 0533, Institute of Social and Economic Research, Osaka University.
    6. Paz Rico & Bernardí Cabrer-Borrás & Francisco Morillas-Jurado, 2021. "Seasonality in Tourism: Do Senior Programs Mitigate It?," Mathematics, MDPI, vol. 9(16), pages 1-27, August.
    7. Ms. Evridiki Tsounta, 2008. "What Attracts Tourists to Paradise?," IMF Working Papers 2008/277, International Monetary Fund.
    8. Nicholas Apergis & Andrea Mervar & James E. Payne, 2017. "Forecasting disaggregated tourist arrivals in Croatia," Tourism Economics, , vol. 23(1), pages 78-98, February.
    9. Song, Haiyan & Qiu, Richard T.R. & Park, Jinah, 2019. "A review of research on tourism demand forecasting," Annals of Tourism Research, Elsevier, vol. 75(C), pages 338-362.

  55. Kim, Jae H., 1999. "Asymptotic and bootstrap prediction regions for vector autoregression," International Journal of Forecasting, Elsevier, vol. 15(4), pages 393-403, October.

    Cited by:

    1. Kim, Jae H. & Wong, Kevin & Athanasopoulos, George & Liu, Shen, 2011. "Beyond point forecasting: Evaluation of alternative prediction intervals for tourist arrivals," International Journal of Forecasting, Elsevier, vol. 27(3), pages 887-901, July.
    2. Reeves, Jonathan J., 2005. "Bootstrap prediction intervals for ARCH models," International Journal of Forecasting, Elsevier, vol. 21(2), pages 237-248.
    3. Fady Barsoum, 2015. "Point and Density Forecasts Using an Unrestricted Mixed-Frequency VAR Model," Working Paper Series of the Department of Economics, University of Konstanz 2015-19, Department of Economics, University of Konstanz.
    4. Pascual, Lorenzo & Ruiz Ortega, Esther & Fresoli, Diego Eduardo, 2011. "Bootstrap forecast of multivariate VAR models without using the backward representation," DES - Working Papers. Statistics and Econometrics. WS ws113426, Universidad Carlos III de Madrid. Departamento de Estadística.
    5. Jae H. Kim, 2004. "Bias-corrected bootstrap prediction regions for vector autoregression," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 23(2), pages 141-154.
    6. Jing Li, 2021. "Block bootstrap prediction intervals for parsimonious first‐order vector autoregression," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(3), pages 512-527, April.
    7. Clements, Michael P. & Kim, Jae H., 2007. "Bootstrap prediction intervals for autoregressive time series," Computational Statistics & Data Analysis, Elsevier, vol. 51(7), pages 3580-3594, April.
    8. Helmut Luetkepohl, 2011. "Vector Autoregressive Models," Economics Working Papers ECO2011/30, European University Institute.
    9. De Gooijer, Jan G. & Hyndman, Rob J., 2006. "25 years of time series forecasting," International Journal of Forecasting, Elsevier, vol. 22(3), pages 443-473.
    10. Kim, Jae H., 2004. "Bootstrap prediction intervals for autoregression using asymptotically mean-unbiased estimators," International Journal of Forecasting, Elsevier, vol. 20(1), pages 85-97.
    11. Helmut Lütkepohl & Anna Staszewska-Bystrova & Peter Winker, 2014. "Confidence Bands for Impulse Responses: Bonferroni versus Wald," CESifo Working Paper Series 4634, CESifo.
    12. Marcellino, Massimiliano & Knüppel, Malte & Jordà , Òscar, 2010. "Empirical Simultaneous Confidence Regions for Path-Forecasts," CEPR Discussion Papers 7797, C.E.P.R. Discussion Papers.
    13. Li, Jing, 2011. "Bootstrap prediction intervals for SETAR models," International Journal of Forecasting, Elsevier, vol. 27(2), pages 320-332.
    14. Jan G. De Gooijer & Rob J. Hyndman, 2005. "25 Years of IIF Time Series Forecasting: A Selective Review," Monash Econometrics and Business Statistics Working Papers 12/05, Monash University, Department of Econometrics and Business Statistics.
    15. Liew, Venus Khim-Sen, 2008. "An overview on various ways of bootstrap methods," MPRA Paper 7163, University Library of Munich, Germany.
    16. Dag Kolsrud, 2015. "A Time‐Simultaneous Prediction Box for a Multivariate Time Series," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 34(8), pages 675-693, December.
    17. Giovanni Fonseca & Federica Giummolè & Paolo Vidoni, 2021. "A note on simultaneous calibrated prediction intervals for time series," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 30(1), pages 317-330, March.
    18. Anna Staszewska‐Bystrova, 2011. "Bootstrap prediction bands for forecast paths from vector autoregressive models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 30(8), pages 721-735, December.
    19. Diego Fresoli, 2022. "Bootstrap VAR forecasts: The effect of model uncertainties," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(2), pages 279-293, March.
    20. Fresoli, Diego & Ruiz, Esther & Pascual, Lorenzo, 2015. "Bootstrap multi-step forecasts of non-Gaussian VAR models," International Journal of Forecasting, Elsevier, vol. 31(3), pages 834-848.
    21. Stanislav Anatolyev, 2007. "The basics of bootstrapping (in Russian)," Quantile, Quantile, issue 3, pages 1-12, September.
    22. Jing, Li, 2009. "Bootstrap prediction intervals for threshold autoregressive models," MPRA Paper 13086, University Library of Munich, Germany.
    23. Helmut Luetkepohl, 2009. "Forecasting Aggregated Time Series Variables: A Survey," Economics Working Papers ECO2009/17, European University Institute.
    24. Anna Staszewska-Bystrova, 2009. "Bootstrap Confidence Bands for Forecast Paths," Working Papers 024, COMISEF.
    25. Li, Jing, 2011. "Bootstrap prediction intervals for SETAR models," International Journal of Forecasting, Elsevier, vol. 27(2), pages 320-332, April.
    26. Mulubrhan G. Haile & Lingling Zhang & David J. Olive, 2024. "Predicting Random Walks and a Data-Splitting Prediction Region," Stats, MDPI, vol. 7(1), pages 1-11, January.
    27. Gonçalves Mazzeu, Joao Henrique & Ruiz Ortega, Esther & Veiga, Helena, 2015. "Model uncertainty and the forecast accuracy of ARMA models: A survey," DES - Working Papers. Statistics and Econometrics. WS ws1508, Universidad Carlos III de Madrid. Departamento de Estadística.
    28. Staszewska-Bystrova, Anna & Winker, Peter, 2013. "Constructing narrowest pathwise bootstrap prediction bands using threshold accepting," International Journal of Forecasting, Elsevier, vol. 29(2), pages 221-233.
    29. Òscar Jordà & Malte Knuppel & Massimiliano Marcellino, 2012. "Empirical simultaneous prediction regions for path-forecasts," Working Paper Series 2012-05, Federal Reserve Bank of San Francisco.
    30. Lam, J. -P. & Veall, M. R., 2002. "Bootstrap prediction intervals for single period regression forecasts," International Journal of Forecasting, Elsevier, vol. 18(1), pages 125-130.

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