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Chung-Ming Kuan

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.

Wikipedia or ReplicationWiki mentions

(Only mentions on Wikipedia that link back to a page on a RePEc service)
  1. Yi-Ting Chen & Chung-Ming Kuan, 2002. "Time irreversibility and EGARCH effects in US stock index returns," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 17(5), pages 565-578.

    Mentioned in:

    1. Time irreversibility and EGARCH effects in US stock index returns (Journal of Applied Econometrics 2002) in ReplicationWiki ()
  2. Kuan, Chung-Ming & Liu, Tung, 1995. "Forecasting Exchange Rates Using Feedforward and Recurrent Neural Networks," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 10(4), pages 347-364, Oct.-Dec..

    Mentioned in:

    1. Forecasting exchange rates using feedforward and recurrent neural networks (Journal of Applied Econometrics 1995) in ReplicationWiki ()

Working papers

  1. Chia-Chang Chuang & Chung-Ming Kuan & Hsin-yi Lin, 2007. "Causality in Quantiles and Dynamic Stock Return-Volume Relations," IEAS Working Paper : academic research 07-A006, Institute of Economics, Academia Sinica, Taipei, Taiwan.

    Cited by:

    1. Baur, Dirk G. & Dimpfl, Thomas & Jung, Robert C., 2012. "Stock return autocorrelations revisited: A quantile regression approach," University of Tübingen Working Papers in Business and Economics 24, University of Tuebingen, Faculty of Economics and Social Sciences, School of Business and Economics.
    2. Broto, Carmen & Díaz-Cassou, Javier & Erce, Aitor, 2011. "Measuring and explaining the volatility of capital flows to emerging countries," Journal of Banking & Finance, Elsevier, vol. 35(8), pages 1941-1953, August.
    3. Haoyuan Ding & Yuying Jin & Cong Qin & Jiezhou Ying, 2020. "Tail Causality between Crude Oil Price and RMB Exchange Rate," China & World Economy, Institute of World Economics and Politics, Chinese Academy of Social Sciences, vol. 28(3), pages 116-134, May.
    4. Riza Demirer & Rangan Gupta & Asli Yuksel & Aydin Yuksel, 2020. "The U.S. Term Structure and Return Volatility in Global REIT Markets," Working Papers 202069, University of Pretoria, Department of Economics.
    5. Taoufik Bouezmarni & Mohamed Doukali & Abderrahim Taamouti, 2023. "Testing Granger Non-Causality in Expectiles," University of East Anglia School of Economics Working Paper Series 2023-02, School of Economics, University of East Anglia, Norwich, UK..
    6. Chen, Yen-Chun & Lin, Ya-Hui & Li, Po-Chien & Chen, Chung-Jen, 2022. "Understanding the interplay between competitor and alliance orientations in product innovativeness: An integrative framework," Technological Forecasting and Social Change, Elsevier, vol. 175(C).
    7. Kenneth A. Tah & Geoffrey Ngene, 2021. "Dynamic linkages between US and Eurodollar interest rates: new evidence from causality in quantiles," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 45(1), pages 200-210, January.
    8. Hau, Liya & Zhu, Huiming & Shahbaz, Muhammad & Sun, Wuqin, 2021. "Does transaction activity predict Bitcoin returns? Evidence from quantile-on-quantile analysis," The North American Journal of Economics and Finance, Elsevier, vol. 55(C).
    9. Jena, Sangram Keshari & Lahiani, Amine & Tiwari, Aviral Kumar & Roubaud, David, 2021. "Uncovering the complex asymmetric relationship between trading activity and commodity futures price: Evidenced from QNARDL study," Resources Policy, Elsevier, vol. 74(C).
    10. Chen, Shiu-Sheng, 2012. "Revisiting the empirical linkages between stock returns and trading volume," Journal of Banking & Finance, Elsevier, vol. 36(6), pages 1781-1788.
    11. Gebka, Bartosz & Wohar, Mark E., 2013. "Causality between trading volume and returns: Evidence from quantile regressions," International Review of Economics & Finance, Elsevier, vol. 27(C), pages 144-159.
    12. Reboredo, Juan C. & Ugolini, Andrea, 2017. "Quantile causality between gold commodity and gold stock prices," Resources Policy, Elsevier, vol. 53(C), pages 56-63.
    13. Balcilar, Mehmet & Bouri, Elie & Gupta, Rangan & Roubaud, David, 2017. "Can volume predict Bitcoin returns and volatility? A quantiles-based approach," Economic Modelling, Elsevier, vol. 64(C), pages 74-81.
    14. Ding, Haoyuan & Chong, Terence Tai-leung & Park, Sung Y., 2014. "Nonlinear dependence between stock and real estate markets in China," Economics Letters, Elsevier, vol. 124(3), pages 526-529.
    15. Naifar, Nader & Hammoudeh, Shawkat, 2016. "Do global financial distress and uncertainties impact GCC and global sukuk return dynamics?," Pacific-Basin Finance Journal, Elsevier, vol. 39(C), pages 57-69.
    16. Baur, Dirk G., 2013. "The structure and degree of dependence: A quantile regression approach," Journal of Banking & Finance, Elsevier, vol. 37(3), pages 786-798.
    17. Abhinava Tripathi, 2021. "The Arrival of Information and Price Adjustment Across Extreme Quantiles: Global Evidence," IIM Kozhikode Society & Management Review, , vol. 10(1), pages 7-19, January.
    18. 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.
    19. Wenjun Chu & Shanglei Chai & Xi Chen & Mo Du, 2020. "Does the Impact of Carbon Price Determinants Change with the Different Quantiles of Carbon Prices? Evidence from China ETS Pilots," Sustainability, MDPI, vol. 12(14), pages 1-19, July.
    20. Wuyi Ye & Kebing Luo & Shaofu Du, 2014. "Measuring Contagion of Subprime Crisis Based on MVMQ-CAViaR Method," Discrete Dynamics in Nature and Society, Hindawi, vol. 2014, pages 1-12, June.
    21. Effiong, Ekpeno L., 2016. "Nonlinear Dependence between Stock Prices and Exchange Rate in Nigeria," MPRA Paper 74336, University Library of Munich, Germany.
    22. Daniel Danau, 2018. "Prudence and preference for flexibility gain," Working Papers hal-01806743, HAL.
    23. Chowdhury, Biplob & Jeyasreedharan, Nagaratnam & Dungey, Mardi, 2017. "Quantile relationships between standard, diffusion and jump betas across Japanese banks," Working Papers 2017-10, University of Tasmania, Tasmanian School of Business and Economics.
    24. Mokni, Khaled & Ajmi, Ahdi Noomen, 2021. "Cryptocurrencies vs. US dollar: Evidence from causality in quantiles analysis," Economic Analysis and Policy, Elsevier, vol. 69(C), pages 238-252.
    25. Li, Haiqi & Zhong, Wanling & Park, Sung Y., 2016. "Generalized cross-spectral test for nonlinear Granger causality with applications to money–output and price–volume relations," Economic Modelling, Elsevier, vol. 52(PB), pages 661-671.
    26. Jiang, Yong & Ren, Yi-Shuai & Narayan, Seema & Ma, Chao-Qun & Yang, Xiao-Guang, 2022. "Heterogeneity dependence between oil prices and exchange rate: Evidence from a parametric test of Granger causality in quantiles," The North American Journal of Economics and Finance, Elsevier, vol. 62(C).
    27. Ramzi Benkraiem & Thi Hong Van Hoang & Amine Lahiani & Anthony Miloudi, 2018. "Crude oil and equity markets in major European countries: New evidence," Post-Print hal-01914607, HAL.
    28. Yi-Ting Chen, 2016. "Testing for Granger Causality in Moments," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 78(2), pages 265-288, April.
    29. Mehmet Balcilar & Elie Bouri & Rangan Gupta & David Roubaud, 2016. "Can Volume Predict Bitcoin Returns and Volatility? A Nonparametric Causality-in-Quantiles Approach," Working Papers 201662, University of Pretoria, Department of Economics.
    30. Zhenghui Li & Zhiming Ao & Bin Mo, 2021. "Revisiting the Valuable Roles of Global Financial Assets for International Stock Markets: Quantile Coherence and Causality-in-Quantiles Approaches," Mathematics, MDPI, vol. 9(15), pages 1-18, July.
    31. Ardalankia, Jamshid & Osoolian, Mohammad & Haven, Emmanuel & Jafari, G. Reza, 2020. "Scaling features of price–volume cross correlation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 549(C).
    32. Hong, Yanran & Li, Pan & Wang, Lu & Zhang, Yaojie, 2023. "New evidence of extreme risk transmission between financial stress and international crude oil markets," Research in International Business and Finance, Elsevier, vol. 64(C).
    33. Lee, Jaeram & Lee, Geul & Ryu, Doojin, 2018. "Difference in the intraday return-volume relationships of spots and futures: A quantile regression approach," Economics Discussion Papers 2018-68, Kiel Institute for the World Economy (IfW Kiel).
    34. Ciner, Cetin, 2015. "Time variation in systematic risk, returns and trading volume: Evidence from precious metals mining stocks," International Review of Financial Analysis, Elsevier, vol. 41(C), pages 277-283.
    35. Siddhartha Bandyopadhyay & Samrat Bhattacharya & Rudra Sensarma, 2015. "An analysis of the factors determining crime in England and Wales: A quantile regression approach," Economics Bulletin, AccessEcon, vol. 35(1), pages 665-679.
    36. Riza Demirer & Asli Yuksel & Aydin Yuksel, 2020. "The U.S. term structure and return volatility in emerging stock markets," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 44(4), pages 687-707, October.
    37. Elina Pradkhan, 2016. "Information Content of Trading Activity in Precious Metals Futures Markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 36(5), pages 421-456, May.
    38. Troster, Victor & Bouri, Elie & Roubaud, David, 2019. "A quantile regression analysis of flights-to-safety with implied volatilities," Resources Policy, Elsevier, vol. 62(C), pages 482-495.
    39. Louhichi, Waël, 2011. "What drives the volume-volatility relationship on Euronext Paris?," International Review of Financial Analysis, Elsevier, vol. 20(4), pages 200-206, August.
    40. Fredj Jawadi & Waël Louhichi & Abdoulkarim Idi Cheffou & Rivo Randrianarivony, 2016. "Intraday jumps and trading volume: a nonlinear Tobit specification," Review of Quantitative Finance and Accounting, Springer, vol. 47(4), pages 1167-1186, November.
    41. Park, Jin Suk & Newaz, Mohammad Khaleq, 2021. "Liquidity and short-run predictability: Evidence from international stock markets," Global Finance Journal, Elsevier, vol. 50(C).
    42. Ben Rejeb, Aymen & Arfaoui, Mongi, 2016. "Financial market interdependencies: A quantile regression analysis of volatility spillover," Research in International Business and Finance, Elsevier, vol. 36(C), pages 140-157.
    43. Batten, Jonathan A. & Ciner, Cetin & Kosedag, Arman & Lucey, Brian M., 2017. "Is the price of gold to gold mining stocks asymmetric?," Economic Modelling, Elsevier, vol. 60(C), pages 402-407.
    44. Pierdzioch, Christian & Risse, Marian & Rohloff, Sebastian, 2015. "A real-time quantile-regression approach to forecasting gold returns under asymmetric loss," Resources Policy, Elsevier, vol. 45(C), pages 299-306.
    45. Soylu, Pınar Kaya & Güloğlu, Bülent, 2019. "Financial contagion and flight to quality between emerging markets and U.S. bond market," The North American Journal of Economics and Finance, Elsevier, vol. 50(C).
    46. Daouda Lawa tan Toe & Salifou Ouedraogo, 2022. "Dynamic relationship between trading volume, returns and returns volatility: an empirical investigation on the main African’s stock markets," Journal of Asset Management, Palgrave Macmillan, vol. 23(5), pages 429-444, September.
    47. Kyritsis, Evangelos & Andersson, Jonas, 2019. "Causality in quantiles and dynamic relations in energy markets: (De)tails matter," Energy Policy, Elsevier, vol. 133(C).
    48. Hong Cheng & Yunqing Wang & Yihong Wang & Tinggan Yang, 2022. "Inferring Causal Interactions in Financial Markets Using Conditional Granger Causality Based on Quantile Regression," Computational Economics, Springer;Society for Computational Economics, vol. 59(2), pages 719-748, February.
    49. Mensi, Walid & Hammoudeh, Shawkat & Reboredo, Juan Carlos & Nguyen, Duc Khuong, 2014. "Do global factors impact BRICS stock markets? A quantile regression approach," Emerging Markets Review, Elsevier, vol. 19(C), pages 1-17.
    50. Juan Carlos Reboredo & Nader Naifar, 2017. "Do Islamic Bond (Sukuk) Prices Reflect Financial and Policy Uncertainty? A Quantile Regression Approach," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 53(7), pages 1535-1546, July.
    51. Shaddady, Ali & Moore, Tomoe, 2019. "Investigation of the effects of financial regulation and supervision on bank stability: The application of CAMELS-DEA to quantile regressions," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 58(C), pages 96-116.
    52. Paulo Sergio Ceretta & Marcelo Brutti Righi & Alexandre Silva Da costa & Fernanda Maria Muller, 2012. "Quantiles autocorrelation in stock markets returns," Economics Bulletin, AccessEcon, vol. 32(3), pages 2065-2075.
    53. Wang, Zijun & Qian, Yan & Wang, Shiwen, 2018. "Dynamic trading volume and stock return relation: Does it hold out of sample?," International Review of Financial Analysis, Elsevier, vol. 58(C), pages 195-210.
    54. Taoufik Bouezmarni & Mohamed Doukali & Abderrahim Taamouti, 2022. "Testing Granger Non-Causality in Expectiles," Working Papers 202207, University of Liverpool, Department of Economics.
    55. Pradkhan, Elina, 2017. "Financial activity in agricultural futures markets: evidence from quantile regressions," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 61(4), October.
    56. Sharma, Gagan Deep & Shahbaz, Muhammad & Singh, Sanjeet & Chopra, Ritika & Cifuentes-Faura, Javier, 2023. "Investigating the nexus between green economy, sustainability, bitcoin and oil prices: Contextual evidence from the United States," Resources Policy, Elsevier, vol. 80(C).
    57. Agapova, Anna & Kaprielyan, Margarita, 2020. "Stock volatility and trading," The North American Journal of Economics and Finance, Elsevier, vol. 54(C).
    58. Gebka, Bartosz & Wohar, Mark E., 2019. "Stock return distribution and predictability: Evidence from over a century of daily data on the DJIA index," International Review of Economics & Finance, Elsevier, vol. 60(C), pages 1-25.
    59. Andre M. Marques & Gilberto Tadeu Lima, 2021. "Testing for Granger Causality in Quantiles Between the Wage Share and Capacity Utilization," Working Papers, Department of Economics 2021_03, University of São Paulo (FEA-USP).
    60. Zheng Yang & Anthony H. Tu & Yong Zeng, 2014. "Dynamic linkages between Asian stock prices and exchange rates: new evidence from causality in quantiles," Applied Economics, Taylor & Francis Journals, vol. 46(11), pages 1184-1201, April.
    61. Chen, Cathy W.S. & Gerlach, Richard & Wei, D.C.M., 2009. "Bayesian causal effects in quantiles: Accounting for heteroscedasticity," Computational Statistics & Data Analysis, Elsevier, vol. 53(6), pages 1993-2007, April.
    62. Cathy W. S. Chen & Muyi Li & Nga T. H. Nguyen & Songsak Sriboonchitta, 2017. "On Asymmetric Market Model with Heteroskedasticity and Quantile Regression," Computational Economics, Springer;Society for Computational Economics, vol. 49(1), pages 155-174, January.
    63. Zhu, Huiming & Li, Shuang & Huang, Zishan, 2023. "Frequency domain quantile dependence and connectedness between crude oil and exchange rates: Evidence from oil-importing and exporting countries," The Quarterly Review of Economics and Finance, Elsevier, vol. 90(C), pages 1-30.
    64. Khamis Hamed Al-Yahyaee & Walid Mensi & Hee-Un Ko & Massimiliano Caporin & Sang Hoon Kang, 2021. "Is the Korean housing market following Gangnam style?," Empirical Economics, Springer, vol. 61(4), pages 2041-2072, October.
    65. Xiao, Di & Wang, Jun, 2020. "Dynamic complexity and causality of crude oil and major stock markets," Energy, Elsevier, vol. 193(C).
    66. Albulescu, C.T. & Bouri, E. & Tiwari, A.K. & Roubaud, D., 2020. "Quantile causality between banking stock and real estate securities returns in the US," The Quarterly Review of Economics and Finance, Elsevier, vol. 78(C), pages 251-260.
    67. Mai, Nhat Chi, 2016. "The Influence Of Macroeconomic Announcements Into Vietnamese Stock Market Volatility," OSF Preprints ydmhx, Center for Open Science.
    68. Marañon, Matias & Kumral, Mustafa, 2021. "Empirical analysis of Chile's copper boom and the Dutch Disease through causality and cointegration tests," Resources Policy, Elsevier, vol. 70(C).
    69. Amir Rubin & Daniel Smith, 2010. "Comparing Different Explanations of the Volatility Trend," NCER Working Paper Series 68, National Centre for Econometric Research.
    70. Ben Rejeb, Aymen, 2017. "On the volatility spillover between lslamic and conventional stock markets: A quantile regression analysis," Research in International Business and Finance, Elsevier, vol. 42(C), pages 794-815.
    71. Peng, Cheng & Zhu, Huiming & Jia, Xianghua & You, Wanhai, 2017. "Stock price synchronicity to oil shocks across quantiles: Evidence from Chinese oil firms," Economic Modelling, Elsevier, vol. 61(C), pages 248-259.
    72. Kao, Yu-Sheng & Zhao, Kai & Chuang, Hwei-Lin & Ku, Yu-Cheng, 2024. "The asymmetric relationships between the Bitcoin futures’ return, volatility, and trading volume," International Review of Economics & Finance, Elsevier, vol. 89(PA), pages 524-542.
    73. Makkonen, Adam & Vallström, Daniel & Uddin, Gazi Salah & Rahman, Md Lutfur & Haddad, Michel Ferreira Cardia, 2021. "The effect of temperature anomaly and macroeconomic fundamentals on agricultural commodity futures returns," Energy Economics, Elsevier, vol. 100(C).
    74. Behrendt, Simon & Schmidt, Alexander, 2021. "Nonlinearity matters: The stock price – trading volume relation revisited," Economic Modelling, Elsevier, vol. 98(C), pages 371-385.
    75. Laura Ferrando & Román Ferrer & Francisco Jareño, 2017. "Interest Rate Sensitivity of Spanish Industries: A Quantile Regression Approach," Manchester School, University of Manchester, vol. 85(2), pages 212-242, March.
    76. Cathy W.S. Chen & Mike K.P. So & Thomas C. Chiang, 2016. "Evidence of Stock Returns and Abnormal Trading Volume: A Threshold Quantile Regression Approach," The Japanese Economic Review, Japanese Economic Association, vol. 67(1), pages 96-124, March.
    77. Zhi Yang & Zhao Fei & Jing Wang, 2024. "Research on the Correlation between the Exchange Rate of Offshore RMB and the Stock Index Futures," Mathematics, MDPI, vol. 12(5), pages 1-15, February.
    78. Qian, Biyu & Wang, Gang-Jin & Feng, Yusen & Xie, Chi, 2022. "Partial cross-quantilogram networks: Measuring quantile connectedness of financial institutions," The North American Journal of Economics and Finance, Elsevier, vol. 60(C).
    79. Reboredo, Juan C. & Uddin, Gazi Salah, 2016. "Do financial stress and policy uncertainty have an impact on the energy and metals markets? A quantile regression approach," International Review of Economics & Finance, Elsevier, vol. 43(C), pages 284-298.
    80. Laura Garcia-Jorcano & Lidia Sanchis-Marco, 2023. "Measuring Systemic Risk Using Multivariate Quantile-Located ES Models," Journal of Financial Econometrics, Oxford University Press, vol. 21(1), pages 1-72.
    81. Youssef, Manel & Mokni, Khaled, 2020. "Modeling the relationship between oil and USD exchange rates: Evidence from a regime-switching-quantile regression approach," Journal of Multinational Financial Management, Elsevier, vol. 55(C).
    82. Panpan Wang & Tsungwu Ho & Yishi Li, 2020. "The Price-Volume Relationship of the Shanghai Stock Index: Structural Change and the Threshold Effect of Volatility," Sustainability, MDPI, vol. 12(8), pages 1-17, April.
    83. Al-Nasseri, Alya & Menla Ali, Faek & Tucker, Allan, 2021. "Investor sentiment and the dispersion of stock returns: Evidence based on the social network of investors," International Review of Financial Analysis, Elsevier, vol. 78(C).
    84. Yang, Lu & Tian, Shuairu & Yang, Wei & Xu, Mingli & Hamori, Shigeyuki, 2018. "Dependence structures between Chinese stock markets and the international financial market: Evidence from a wavelet-based quantile regression approach," The North American Journal of Economics and Finance, Elsevier, vol. 45(C), pages 116-137.
    85. Shahzad, Syed Jawad Hussain & Mensi, Walid & Hammoudeh, Shawkat & Sohail, Asiya & Al-Yahyaee, Khamis Hamed, 2019. "Does gold act as a hedge against different nuances of inflation? Evidence from Quantile-on-Quantile and causality-in- quantiles approaches," Resources Policy, Elsevier, vol. 62(C), pages 602-615.
    86. Dirk G Baur & Thomas Dimpfl, 2012. "State-dependent Momentum in International Stock Markets," Working Paper Series 169, Finance Discipline Group, UTS Business School, University of Technology, Sydney.
    87. Scarcioffolo, Alexandre R. & Etienne, Xiaoli, 2021. "Testing directional predictability between energy prices: A quantile-based analysis," Resources Policy, Elsevier, vol. 74(C).
    88. Jiranyakul, Komain, 2016. "Dynamic relationship between stock return, trading volume, and volatility in the Stock Exchange of Thailand: does the US subprime crisis matter?," MPRA Paper 73791, University Library of Munich, Germany.
    89. Ngene, Geoffrey M. & Mungai, Ann Nduati, 2022. "Stock returns, trading volume, and volatility: The case of African stock markets," International Review of Financial Analysis, Elsevier, vol. 82(C).
    90. Xu, Alan, 2022. "Air pollution and mediation effects in stock market, longitudinal evidence from China," International Review of Financial Analysis, Elsevier, vol. 83(C).
    91. Jammazi, Rania & Ferrer, Román & Jareño, Francisco & Shahzad, Syed Jawad Hussain, 2017. "Time-varying causality between crude oil and stock markets: What can we learn from a multiscale perspective?," International Review of Economics & Finance, Elsevier, vol. 49(C), pages 453-483.
    92. 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.
    93. Marques, André M. & Lima, Gilberto Tadeu, 2022. "Testing for Granger causality in quantiles between the wage share in income and productive capacity utilization," Structural Change and Economic Dynamics, Elsevier, vol. 62(C), pages 290-312.
    94. Gupta, Suman & Das, Debojyoti & Hasim, Haslifah & Tiwari, Aviral Kumar, 2018. "The dynamic relationship between stock returns and trading volume revisited: A MODWT-VAR approach," Finance Research Letters, Elsevier, vol. 27(C), pages 91-98.
    95. Ni, Zhong-Xin & Wang, Da-Zhong & Xue, Wen-Jun, 2015. "Investor sentiment and its nonlinear effect on stock returns—New evidence from the Chinese stock market based on panel quantile regression model," Economic Modelling, Elsevier, vol. 50(C), pages 266-274.
    96. Xianfang Su & Huiming Zhu & Xinxia Yang, 2019. "Heterogeneous Causal Relationships between Spot and Futures Oil Prices: Evidence from Quantile Causality Analysis," Sustainability, MDPI, vol. 11(5), pages 1-17, March.
    97. Zhu, Huiming & Peng, Cheng & You, Wanhai, 2016. "Quantile behaviour of cointegration between silver and gold prices," Finance Research Letters, Elsevier, vol. 19(C), pages 119-125.
    98. Chen, Qitong & Zhu, Huiming & Yu, Dongwei & Hau, Liya, 2022. "How does investor attention matter for crude oil prices and returns? Evidence from time-frequency quantile causality analysis," The North American Journal of Economics and Finance, Elsevier, vol. 59(C).
    99. Maria Sole Pagliari & Swarnali Ahmed Hannan, 2017. "The Volatility of Capital Flows in Emerging Markets: Measures and Determinants," Departmental Working Papers 201710, Rutgers University, Department of Economics.
    100. Ding, Haoyuan & Kim, Hyung-Gun & Park, Sung Y., 2014. "Do net positions in the futures market cause spot prices of crude oil?," Economic Modelling, Elsevier, vol. 41(C), pages 177-190.
    101. Chunpeng Yang & Jun Chi, 2023. "Investor sentiment and volatility of exchange‐traded funds: Evidence from China," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(1), pages 668-680, January.
    102. Shen, Yifan & Shi, Xunpeng & Variam, Hari Malamakkavu Padinjare, 2018. "Risk transmission mechanism between energy markets: A VAR for VaR approach," Energy Economics, Elsevier, vol. 75(C), pages 377-388.
    103. Ye, Wuyi & Zhu, Yangguang & Wu, Yuehua & Miao, Baiqi, 2016. "Markov regime-switching quantile regression models and financial contagion detection," Insurance: Mathematics and Economics, Elsevier, vol. 67(C), pages 21-26.
    104. Zied Ftiti & Fredj Jawadi & Waël Louhichi, 2017. "Modelling the relationship between future energy intraday volatility and trading volume with wavelet," Applied Economics, Taylor & Francis Journals, vol. 49(20), pages 1981-1993, April.
    105. Min Liu & Chien‐Chiang Lee & Wei‐Chong Choo, 2021. "An empirical study on the role of trading volume and data frequency in volatility forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(5), pages 792-816, August.
    106. Kuan, Tsung-Han & Li, Chu-Shiu & Liu, Chwen-Chi, 2012. "Corporate governance and cash holdings: A quantile regression approach," International Review of Economics & Finance, Elsevier, vol. 24(C), pages 303-314.
    107. Ding, Haoyuan & Kim, Hyung-Gun & Park, Sung Y., 2016. "Crude oil and stock markets: Causal relationships in tails?," Energy Economics, Elsevier, vol. 59(C), pages 58-69.
    108. Gonzalo, Jesús & Taamouti, Abderrahim, 2012. "The reaction of stock market returns to anticipated unemployment," UC3M Working papers. Economics we1237, Universidad Carlos III de Madrid. Departamento de Economía.
    109. Lili Li & Shan Leng & Jun Yang & Mei Yu, 2016. "Stock Market Autoregressive Dynamics: A Multinational Comparative Study with Quantile Regression," Mathematical Problems in Engineering, Hindawi, vol. 2016, pages 1-15, September.
    110. Shen, Yifan, 2018. "International risk transmission of stock market movements," Economic Modelling, Elsevier, vol. 69(C), pages 220-236.
    111. Mokni, Khaled, 2021. "When, where, and how economic policy uncertainty predicts Bitcoin returns and volatility? A quantiles-based analysis," The Quarterly Review of Economics and Finance, Elsevier, vol. 80(C), pages 65-73.
    112. Mensi, Walid & Shahzad, Syed Jawad Hussain & Hammoudeh, Shawkat & Zeitun, Rami & Rehman, Mobeen Ur, 2017. "Diversification potential of Asian frontier, BRIC emerging and major developed stock markets: A wavelet-based value at risk approach," Emerging Markets Review, Elsevier, vol. 32(C), pages 130-147.
    113. Fousekis, Panos & Tzaferi, Dimitra, 2021. "Returns and volume: Frequency connectedness in cryptocurrency markets," Economic Modelling, Elsevier, vol. 95(C), pages 13-20.
    114. Troster, Victor & Shahbaz, Muhammad & Uddin, Gazi Salah, 2018. "Renewable Energy, Oil Prices, and Economic Activity: A Granger-causality in Quantiles Analysis," MPRA Paper 84194, University Library of Munich, Germany, revised 19 Jan 2018.
    115. Naifar, Nader & Mroua, Mourad & Bahloul, Slah, 2017. "Do regional and global uncertainty factors affect differently the conventional bonds and sukuk? New evidence," Pacific-Basin Finance Journal, Elsevier, vol. 41(C), pages 65-74.
    116. Stephanos Papadamou & Νikolaos A. Kyriazis & Panayiotis G. Tzeremes, 2020. "US non-linear causal effects on global equity indices in Normal times versus unconventional eras," International Economics and Economic Policy, Springer, vol. 17(2), pages 381-407, May.
    117. Ben Rejeb, Aymen, 2016. "Volatility Spillover between Islamic and conventional stock markets: evidence from Quantile Regression analysis," MPRA Paper 73302, University Library of Munich, Germany.
    118. Marcus Alexander Ong, 2015. "An information theoretic analysis of stock returns, volatility and trading volumes," Applied Economics, Taylor & Francis Journals, vol. 47(36), pages 3891-3906, August.
    119. Park, Sung Y. & Ryu, Doojin & Song, Jeongseok, 2017. "The dynamic conditional relationship between stock market returns and implied volatility," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 482(C), pages 638-648.
    120. Swamy, Vighneswara & Dharani, M. & Takeda, Fumiko, 2019. "Investor attention and Google Search Volume Index: Evidence from an emerging market using quantile regression analysis," Research in International Business and Finance, Elsevier, vol. 50(C), pages 1-17.
    121. Tan Le & Franck Martin & Duc Nguyen, 2018. "Dynamic connectedness of global currencies: a conditional Granger-causality approach," Working Papers hal-01806733, HAL.
    122. Mokni, Khaled & Ben-Salha, Ousama, 2020. "Asymmetric causality in quantiles analysis of the oil-food ‏ ‏nexus since the 1960s," Resources Policy, Elsevier, vol. 69(C).
    123. Yamani, Ehab, 2023. "Return–volume nexus in financial markets: A survey of research," Research in International Business and Finance, Elsevier, vol. 65(C).
    124. Hao, Jing & He, Feng, 2018. "Univariate dependence among sectors in Chinese stock market and systemic risk implication," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 510(C), pages 355-364.
    125. Zhuhua Jiang & Rangan Gupta & Sowmya Subramaniam & Seong-Min Yoon, 2021. "The Effect of Air Quality and Weather on the Chinese Stock: Evidence from Shenzhen Stock Exchange," Sustainability, MDPI, vol. 13(5), pages 1-20, March.
    126. Hong, Yanran & Ma, Feng & Wang, Lu & Liang, Chao, 2022. "How does the COVID-19 outbreak affect the causality between gold and the stock market? New evidence from the extreme Granger causality test," Resources Policy, Elsevier, vol. 78(C).
    127. Lee, Bong Soo & Li, Ming-Yuan Leon, 2012. "Diversification and risk-adjusted performance: A quantile regression approach," Journal of Banking & Finance, Elsevier, vol. 36(7), pages 2157-2173.
    128. Kim, Myeong Jun & Canh, Nguyen Phuc & Park, Sung Y., 2021. "Causal relationship among cryptocurrencies: A conditional quantile approach," Finance Research Letters, Elsevier, vol. 42(C).
    129. Yang, Kun & Wei, Yu & Li, Shouwei & Liu, Liang & Wang, Lei, 2021. "Global financial uncertainties and China’s crude oil futures market: Evidence from interday and intraday price dynamics," Energy Economics, Elsevier, vol. 96(C).
    130. Yang, Lu & Cui, Xue & Yang, Lei & Hamori, Shigeyuki & Cai, Xiaojing, 2023. "Risk spillover from international financial markets and China's macro-economy: A MIDAS-CoVaR-QR model," International Review of Economics & Finance, Elsevier, vol. 84(C), pages 55-69.
    131. Liu, Tangyong & Gong, Xu, 2020. "Analyzing time-varying volatility spillovers between the crude oil markets using a new method," Energy Economics, Elsevier, vol. 87(C).
    132. Abhinava Tripathi & Vipul & Alok Dixit, 2020. "Liquidity commonality beyond best prices: Indian evidence," Journal of Asset Management, Palgrave Macmillan, vol. 21(4), pages 355-373, July.
    133. Su, Chi-Wei & Huang, Shi-Wen & Qin, Meng & Umar, Muhammad, 2021. "Does crude oil price stimulate economic policy uncertainty in BRICS?," Pacific-Basin Finance Journal, Elsevier, vol. 66(C).
    134. Nasiri, S. & Bektas, E. & Jafari, G.R., 2018. "The impact of trading volume on the stock market credibility: Bohmian quantum potential approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 512(C), pages 1104-1112.
    135. You, Wanhai & Guo, Yawei & Peng, Cheng, 2017. "Twitter's daily happiness sentiment and the predictability of stock returns," Finance Research Letters, Elsevier, vol. 23(C), pages 58-64.
    136. Chin, Chang-Chiang & Paphakin, Warinthorn, 2021. "The daily relationship between U.S. asset prices and stock prices of American countries," The North American Journal of Economics and Finance, Elsevier, vol. 57(C).
    137. Radu T. Pruna & Maria Polukarov & Nicholas R. Jennings, 2016. "A new structural stochastic volatility model of asset pricing and its stylized facts," Papers 1604.08824, arXiv.org.
    138. Yin DAI & Jing-wen ZHANG & Xiu-zhen YU & Xin LI, 2017. "Causality between economic policy uncertainty and exchange rate in China with considering quantile differences," Theoretical and Applied Economics, Asociatia Generala a Economistilor din Romania - AGER, vol. 0(3(612), A), pages 29-38, Autumn.
    139. Elina Pradkhan, 2017. "Financial activity in agricultural futures markets: evidence from quantile regressions," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 61(4), pages 610-625, October.
    140. Cheng, Ching-Hsue & Wei, Liang-Ying & Liu, Jing-Wei & Chen, Tai-Liang, 2013. "OWA-based ANFIS model for TAIEX forecasting," Economic Modelling, Elsevier, vol. 30(C), pages 442-448.
    141. Tan, Xue-Ping & Wang, Xin-Yu, 2017. "Dependence changes between the carbon price and its fundamentals: A quantile regression approach," Applied Energy, Elsevier, vol. 190(C), pages 306-325.
    142. Jamshid Ardalankia & Mohammad Osoolian & Emmanuel Haven & G. Reza Jafari, 2019. "Scaling Features of Price-Volume Cross-Correlation," Papers 1903.01744, arXiv.org, revised Aug 2020.
    143. Donald Lien & Zijun Wang, 2019. "Quantile information share," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 39(1), pages 38-55, January.
    144. Hooy, Chee-Wooi & Lee, Meng-Horng & Chong, Terence Tai Leung, 2017. "The Sources of Country and Industry Variations in ASEAN Stock Returns," MPRA Paper 80574, University Library of Munich, Germany.
    145. Zhu, Huiming & Guo, Yawei & You, Wanhai & Xu, Yaqin, 2016. "The heterogeneity dependence between crude oil price changes and industry stock market returns in China: Evidence from a quantile regression approach," Energy Economics, Elsevier, vol. 55(C), pages 30-41.
    146. Kao, Yu-Sheng & Chuang, Hwei-Lin & Ku, Yu-Cheng, 2020. "The empirical linkages among market returns, return volatility, and trading volume: Evidence from the S&P 500 VIX Futures," The North American Journal of Economics and Finance, Elsevier, vol. 54(C).
    147. Zhu, Huiming & Huang, Hui & Peng, Cheng & Yang, Yan, 2016. "Extreme dependence between crude oil and stock markets in Asia-Pacific regions: Evidence from quantile regression," Economics Discussion Papers 2016-46, Kiel Institute for the World Economy (IfW Kiel).

  2. Yu-Chin Hsu & Chung-Ming Kuan, 2006. "Change-Point Estimation of Nonstationary I(d) Processes," IEAS Working Paper : academic research 06-A007, Institute of Economics, Academia Sinica, Taipei, Taiwan.

    Cited by:

    1. Daiqing Xi & Tianxiao Pang, 2021. "Estimating multiple breaks in mean sequentially with fractionally integrated errors," Statistical Papers, Springer, vol. 62(1), pages 451-494, February.
    2. Badi H. Baltagi & Chihwa Kao & Long Liu, 2015. "Estimation and Identification of Change Points in Panel Models with Nonstationary or Stationary Regressors and Error Term," Center for Policy Research Working Papers 178, Center for Policy Research, Maxwell School, Syracuse University.
    3. Giorgio Canarella & Stephen M. Miller, 2016. "Inflation Persistence and Structural Breaks: The Experience of Inflation Targeting Countries and the US," Working papers 2016-11, University of Connecticut, Department of Economics.
    4. Zongwu Cai & Seong Yeon Chang, 2018. "A New Test In A Predictive Regression with Structural Breaks," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 201811, University of Kansas, Department of Economics, revised Dec 2018.
    5. Seong Yeon Chang & Pierre Perron, 2014. "Inference on a Structural Break in Trend with Fractionally Integrated Errors," Boston University - Department of Economics - Working Papers Series wp2015-011, Boston University - Department of Economics, revised 20 Sep 2015.
    6. Chang, Seong Yeon, 2021. "Estimation of a level shift in panel data with fractionally integrated errors," Economics Letters, Elsevier, vol. 206(C).

  3. Chung-Ming Kuan, 2006. "Artificial Neural Networks," IEAS Working Paper : academic research 06-A010, Institute of Economics, Academia Sinica, Taipei, Taiwan.

    Cited by:

    1. Jonathan B. Hill, 2004. "Consistent LM-Tests for Linearity Against Compound Smooth Transition Alternatives," Econometric Society 2004 North American Summer Meetings 42, Econometric Society.
    2. Romulo A. Chumacero, 2004. "Forecasting Chilean Industrial Production with Automated Procedures," Econometric Society 2004 Latin American Meetings 177, Econometric Society.
    3. Atanas Christev, 2007. "Learning Hyperinflations," Money Macro and Finance (MMF) Research Group Conference 2006 126, Money Macro and Finance Research Group.
    4. Romulo A. Chumacero, 2004. "Forecasting Chilean Industrial Production and Sales with Automated Procedures," Computing in Economics and Finance 2004 112, Society for Computational Economics.
    5. Jason Barr & Francesco Saraceno, 2004. "Organization, Learning and Cooperation," Computational Economics 0402001, University Library of Munich, Germany.
    6. Donaldson, R. Glen & Kamstra, Mark, 1997. "An artificial neural network-GARCH model for international stock return volatility," Journal of Empirical Finance, Elsevier, vol. 4(1), pages 17-46, January.
    7. Swanson, N.R. & White, H., 1995. "A Models Selection Approach to Real-Time Macroeconomic Forecasting Using Linear Models and Artificial Neural Networks," Papers 04-95-12, Pennsylvania State - Department of Economics.
    8. Heinemann, Maik, 1997. "Convergence of Adaptive Learning and the Concept of Expectational Stability in Linear Rational Expectations Models with Multiple Equilibria," Hannover Economic Papers (HEP) dp-207, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    9. F. Gonzalez Miranda & N. Burgess, 1997. "Modelling market volatilities: the neural network perspective," The European Journal of Finance, Taylor & Francis Journals, vol. 3(2), pages 137-157.
    10. John Geweke & Gianni Amisano, 2011. "Hierarchical Markov normal mixture models with applications to financial asset returns," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 26(1), pages 1-29, January/F.
    11. Preminger, Arie & Franck, Raphael, 2007. "Forecasting exchange rates: A robust regression approach," International Journal of Forecasting, Elsevier, vol. 23(1), pages 71-84.
    12. Daniel Santin & Francisco Delgado & Aurelia Valino, 2004. "The measurement of technical efficiency: a neural network approach," Applied Economics, Taylor & Francis Journals, vol. 36(6), pages 627-635.
    13. Constantinos VORLOW & Antonios ANTONIOU & Catherine KYRTSOU, 2004. "Surrogate Data Analysis and Stochastic Chaotic Modelling: Application to Stock Exchange Returns Series," Computing in Economics and Finance 2004 27, Society for Computational Economics.
    14. Martha Misas Arango & Enrique López Enciso & Pablo Querubín Borrero, 2002. "La inflación en Colombia: una aproximación desde las redes neuronales," Revista ESPE - Ensayos sobre Política Económica, Banco de la Republica de Colombia, vol. 20(41-42), pages 143-214, June.
    15. Schuhr Roland, 2004. "Ein Prognose- und Simulationswerkzeug zur Unterstützung der kurzfristigen Personalbedarfsplanung in einem Call Center / A Forecasting and Simulation Tool for Personnel Requirement in a Call Center," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 224(1-2), pages 166-184, February.
    16. Greg Tkacz & Sarah Hu, 1999. "Forecasting GDP Growth Using Artificial Neural Networks," Staff Working Papers 99-3, Bank of Canada.
    17. Catherine Kyrtsou & Michel Terraza, 2003. "Is it Possible to Study Chaotic and ARCH Behaviour Jointly? Application of a Noisy Mackey–Glass Equation with Heteroskedastic Errors to the Paris Stock Exchange Returns Series," Computational Economics, Springer;Society for Computational Economics, vol. 21(3), pages 257-276, June.
    18. Elena Olmedo & Ricardo Gimeno & Lorenzo Escot & Ruth Mateos, 2007. "Convergencia y Estabilidad de los Tipos de Cambio Europeos: Una Aplicación de Exponentes de Lyapunov," Latin American Journal of Economics-formerly Cuadernos de Economía, Instituto de Economía. Pontificia Universidad Católica de Chile., vol. 44(129), pages 91-108.
    19. Ubilava, David & Helmers, C Gustav, 2012. "Forecasting ENSO with a smooth transition autoregressive model," MPRA Paper 36890, University Library of Munich, Germany.
    20. Medeiros, Marcelo & Veiga, Alvaro, 2000. "Diagnostic Checking in a Flexible Nonlinear Time Series Model," SSE/EFI Working Paper Series in Economics and Finance 386, Stockholm School of Economics, revised 15 Jan 2001.
    21. Ignacio Olmeda & Joaquin Pérez, 1995. "Non-linear dynamics and chaos in the Spanish stock market," Investigaciones Economicas, Fundación SEPI, vol. 19(2), pages 217-248, May.
    22. Dan Farhat, 2012. "Artificial Neural Networks and Aggregate Consumption Patterns in New Zealand," Working Papers 1205, University of Otago, Department of Economics, revised Dec 2012.
    23. Dan Farhat, 2014. "Artificial Neural Networks and Aggregate Consumption Patterns in New Zealand:," Working Papers 1404, University of Otago, Department of Economics, revised Mar 2014.
    24. Jozef Baruník, 2008. "How Do Neural Networks Enhance the Predictability of Central European Stock Returns?," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 58(07-08), pages 358-376, Oktober.
    25. Jonathan B. Hill, 2004. "LM-Tests for Linearity Against Smooth Transition Alternatives: A Bootstrap Simulation Study," Econometrics 0401004, University Library of Munich, Germany, revised 05 Jul 2004.
    26. Raimundo Soto, "undated". "El Tipo de Cambio Real de Equilibrio: Un modelo no lineal de Series de Tiempo," ILADES-UAH Working Papers inv094, Universidad Alberto Hurtado/School of Economics and Business.
    27. Madden, Gary G & Tan, Joachim, 2008. "Forecasting international bandwidth capacity using linear and ANN methods," MPRA Paper 13005, University Library of Munich, Germany.
    28. R. Glen Donaldson & Mark Kamstra, "undated". "Forecasting Fundamental Asset Return Distributions," Computing in Economics and Finance 1997 176, Society for Computational Economics.
    29. Dilip Nachane & Jose Clavel, 2008. "Forecasting interest rates: a comparative assessment of some second-generation nonlinear models," Journal of Applied Statistics, Taylor & Francis Journals, vol. 35(5), pages 493-514.
    30. Christian A. Johnson, 2005. "Modelos de alerta temprana para pronosticar crisis bancarias: desde la extracción de señales a las redes neuronales," Revista de Analisis Economico – Economic Analysis Review, Universidad Alberto Hurtado/School of Economics and Business, vol. 20(1), pages 95-121, June.
    31. Mariano Matilla-Garcia & Carlos Arguello, 2005. "A hybrid approach based on neural networks and genetic algorithms to the study of profitability in the Spanish Stock Market," Applied Economics Letters, Taylor & Francis Journals, vol. 12(5), pages 303-308.
    32. Sergio Pastorello & Valentin Patilea & Eric Renault, 2003. "Iterative and Recursive Estimation in Structural Non-Adaptive Models," CIRANO Working Papers 2003s-08, CIRANO.
    33. Anders Bredahl Kock & Timo Teräsvirta, 2010. "Forecasting with nonlinear time series models," CREATES Research Papers 2010-01, Department of Economics and Business Economics, Aarhus University.
    34. Jonathan B. Hill, 2004. "Consistent Model Specification Tests Against Smooth Transition Alternatives," Econometrics 0402004, University Library of Munich, Germany, revised 05 Aug 2005.
    35. Martha Misas Arango & Enrique López Enciso & Pablo Querubín Borrero, 2002. "La Inflación en Colombia: Una Aproximación desde las Redes Neuronales," Borradores de Economia 3029, Banco de la Republica.
    36. Ralf Ostermark & Jaana Aaltonen & Henrik Saxen & Kenneth Soderlund, 2004. "Nonlinear modelling of the Finnish Banking and Finance branch index," The European Journal of Finance, Taylor & Francis Journals, vol. 10(4), pages 277-289.
    37. van Dijk, D.J.C. & Franses, Ph.H.B.F. & Boswijk, H.P., 2000. "Asymmetric and common absorption of shocks in nonlinear autoregressive models," Econometric Institute Research Papers EI 2000-01/A, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    38. Anderson, Richard G. & Binner, Jane M. & Schmidt, Vincent A., 2012. "Connectionist-based rules describing the pass-through of individual goods prices into trend inflation in the United States," Economics Letters, Elsevier, vol. 117(1), pages 174-177.
    39. Hassan Belkacem Ghassan & Mohammed Souissi & Mohammed Kbiri Alaoui, 2009. "An Alternative Identification of the Economic Shocks in SVAR Models," Economics Bulletin, AccessEcon, vol. 29(2), pages 1019-1026.
    40. Dan Farhat, 2014. "Information Processing, Pattern Transmission and Aggregate Consumption Patterns in New Zealand:," Working Papers 1405, University of Otago, Department of Economics, revised Mar 2014.
    41. Raimundo Soto, "undated". "Nonlinearities in the Demand for money: A Neural Network Approach," ILADES-UAH Working Papers inv107, Universidad Alberto Hurtado/School of Economics and Business.
    42. PREMINGER, Arie & SAKATA, Shinichi, 2005. "A model selection method for S-estimation," LIDAM Discussion Papers CORE 2005073, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

  4. Wei-Ming Lee & Chung-Ming Kuan, 2006. "Testing Over-Identifying Restrictions without Consistent Estimation of the Asymptotic Covariance Matrix," IEAS Working Paper : academic research 06-A009, Institute of Economics, Academia Sinica, Taipei, Taiwan.

    Cited by:

    1. Wei-Ming Lee & Chung-Ming Kuan, 2006. "Testing Over-Identifying Restrictions without Consistent Estimation of the Asymptotic Covariance Matrix," IEAS Working Paper : academic research 06-A009, Institute of Economics, Academia Sinica, Taipei, Taiwan.

  5. Chung-Ming Kuan & Yu-Wei Hsieh, 2006. "Improved HAC Covariance Matrix Estimation Based on Forecast Errors," IEAS Working Paper : academic research 06-A008, Institute of Economics, Academia Sinica, Taipei, Taiwan.

    Cited by:

    1. Luke Hartigan, 2016. "Alternative HAC Covariance Matrix Estimators with Improved Finite Sample Properties," Discussion Papers 2016-06, School of Economics, The University of New South Wales.

  6. Po-Hsuan Hsu & Chung-Ming Kuan, 2004. "Re-Examining the Profitability of Technical Analysis with White’s Reality Check," IEAS Working Paper : academic research 04-A003, Institute of Economics, Academia Sinica, Taipei, Taiwan.

    Cited by:

    1. Pereira, Pedro L. Valls, 2009. "Predictability of equity models," Textos para discussão 176, FGV EESP - Escola de Economia de São Paulo, Fundação Getulio Vargas (Brazil).

  7. Chung-Ming Kuan & Wei-Ming Lee, 2003. "A New Test of the Martingale Difference Hypothesis," IEAS Working Paper : academic research 03-A001, Institute of Economics, Academia Sinica, Taipei, Taiwan.

    Cited by:

    1. Escanciano, Juan Carlos & Velasco, Carlos, 2003. "Generalized spectral tests for the martingale difference hypothesis," DES - Working Papers. Statistics and Econometrics. WS ws035312, Universidad Carlos III de Madrid. Departamento de Estadística.
    2. Zheng, Tingguo & Xiao, Han & Chen, Rong, 2015. "Generalized ARMA models with martingale difference errors," Journal of Econometrics, Elsevier, vol. 189(2), pages 492-506.
    3. 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.
    4. 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.
    5. Belaire-Franch Jorge & Contreras Dulce, 2010. "Testing the Martingale Property of Exchange Rates: A Replication," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 15(1), pages 1-19, December.
    6. Park, Joon Y. & Whang, Yoon-Jae, 2004. "A Test of the Martingale Hypothesis," Working Papers 2004-11, Rice University, Department of Economics.
    7. Peter C.B. Phillips & Sainan Jin, 2013. "Testing the Martingale Hypothesis," Cowles Foundation Discussion Papers 1912, Cowles Foundation for Research in Economics, Yale University.
    8. Zargar, Faisal Nazir & Kumar, Dilip, 2019. "Informational inefficiency of Bitcoin: A study based on high-frequency data," Research in International Business and Finance, Elsevier, vol. 47(C), pages 344-353.
    9. Hong Cheng & Yunqing Wang & Yihong Wang & Tinggan Yang, 2022. "Inferring Causal Interactions in Financial Markets Using Conditional Granger Causality Based on Quantile Regression," Computational Economics, Springer;Society for Computational Economics, vol. 59(2), pages 719-748, February.
    10. 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.
    11. Yi-Ting Chen & Chung-Ming Kuan, 2003. "A Generalized Jarque-Bera Test of Conditional Normality," IEAS Working Paper : academic research 03-A003, Institute of Economics, Academia Sinica, Taipei, Taiwan.
    12. 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.
    13. Guangming Pan & Jiti Gao & Yanrong Yang & Meihui Guo, 2015. "Cross-sectional Independence Test for a Class of Parametric Panel Data Models," Monash Econometrics and Business Statistics Working Papers 17/15, Monash University, Department of Econometrics and Business Statistics.
    14. Qi Li & Jeffrey Scott Racine, 2006. "Nonparametric Econometrics: Theory and Practice," Economics Books, Princeton University Press, edition 1, volume 1, number 8355.
    15. 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.
    16. Friedrich Geiecke & Mark Trede, 2010. "A Direct Test of Rational Bubbles," CQE Working Papers 1310, Center for Quantitative Economics (CQE), University of Muenster.
    17. Nikolaos A. Kyriazis, 2019. "A Survey on Efficiency and Profitable Trading Opportunities in Cryptocurrency Markets," JRFM, MDPI, vol. 12(2), pages 1-17, April.

  8. Yi-Ting Chen & Chung-Ming Kuan, 2003. "A Generalized Jarque-Bera Test of Conditional Normality," IEAS Working Paper : academic research 03-A003, Institute of Economics, Academia Sinica, Taipei, Taiwan.

    Cited by:

    1. Chama CHIPETA & Daniel Francois MEYER, 2018. "Trade Openness, FDI and Exchange Rate Effects on Job Creation in South Africa's Tradable Sectors," Journal of Economics and Behavioral Studies, AMH International, vol. 10(4), pages 197-212.
    2. Chipeta Chama & Meyer Daniel Francois & Muzindutsi Paul-Francois, 2017. "The Effect of Exchange Rate Movements and Economic Growth on Job Creation," Studia Universitatis Babeș-Bolyai Oeconomica, Sciendo, vol. 62(2), pages 20-41, August.
    3. Lee, Taewook, 2013. "On Jarque–Bera normality and cusum parameter change tests for BCTT-GARCH models," Economics Letters, Elsevier, vol. 119(1), pages 50-54.

  9. Yi-Ting Chen & Chung-Ming Kuan, 2000. "The Pseudo-True Score Encompassing Test for Non-Nested Hypothesis," Econometric Society World Congress 2000 Contributed Papers 1723, Econometric Society.

    Cited by:

    1. Taisuke Otsu & Yoon-Jae Whang, 2005. "Testing for Non-nested Conditional Moment Retrictions via Conditional Empirical Likelihood," Cowles Foundation Discussion Papers 1533, Cowles Foundation for Research in Economics, Yale University.
    2. Malmsten, Hans, 2004. "Evaluating exponential GARCH models," SSE/EFI Working Paper Series in Economics and Finance 564, Stockholm School of Economics, revised 03 Sep 2004.
    3. Teräsvirta, Timo, 2006. "An introduction to univariate GARCH models," SSE/EFI Working Paper Series in Economics and Finance 646, Stockholm School of Economics.
    4. Malmsten, Hans & Teräsvirta, Timo, 2004. "Stylized Facts of Financial Time Series and Three Popular Models of Volatility," SSE/EFI Working Paper Series in Economics and Finance 563, Stockholm School of Economics, revised 03 Sep 2004.
    5. Kuan, Chung-Ming & Lin, Hsin-Yi, 2010. "An encompassing test for non-nested quantile regression models," Economics Letters, Elsevier, vol. 107(2), pages 257-260, May.
    6. Chen, Yi-Ting, 2003. "Discriminating between competing STAR models," Economics Letters, Elsevier, vol. 79(2), pages 161-167, May.

  10. Chu, C.S.J. & Hornik, K. & Kuan, C.M., 1993. "Mosum Tests for Parameter Constancy," Papers 9319, Southern California - Department of Economics.

    Cited by:

    1. Deng, Ai & Perron, Pierre, 2008. "A non-local perspective on the power properties of the CUSUM and CUSUM of squares tests for structural change," Journal of Econometrics, Elsevier, vol. 142(1), pages 212-240, January.
    2. Giacomini, Raffaella & Rossi, Barbara, 2008. "Forecast Comparisons in Unstable Environments," Working Papers 08-04, Duke University, Department of Economics.
    3. Pierre Perron & Tomoyoshi Yabu, 2007. "Estimating Deterministic Trend with an Integrated or Stationary Noise Component," Boston University - Department of Economics - Working Papers Series WP2007-020, Boston University - Department of Economics.
    4. Jamel Jouini, 2010. "Bootstrap methods for single structural change tests: power versus corrected size and empirical illustration," Statistical Papers, Springer, vol. 51(1), pages 85-109, January.
    5. Heinen, Florian & Willert, Juliane, 2011. "Monitoring a change in persistence of a long range dependent time series," Hannover Economic Papers (HEP) dp-479, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.

  11. Kuan, C.M. & White, H., 1991. "Strong Convergence of Recursive M-Estimators for Models with Dynamic Latent Variables," Papers 25, Stanford - Institute for Thoretical Economics.

    Cited by:

    1. Albert Marcet & Thomas J. Sargent, 1992. "Speed of convergence of recursive least squares learning with ARMA perceptions," Economics Working Papers 15, Department of Economics and Business, Universitat Pompeu Fabra.

Articles

  1. Wei‐Ming Lee & Yu‐Chin Hsu & Chung‐Ming Kuan, 2015. "Robust hypothesis tests for M‐estimators with possibly non‐differentiable estimating functions," Econometrics Journal, Royal Economic Society, vol. 18(1), pages 95-116, February.

    Cited by:

    1. Wei-Ming Lee & Chung-Ming Kuan, 2006. "Testing Over-Identifying Restrictions without Consistent Estimation of the Asymptotic Covariance Matrix," IEAS Working Paper : academic research 06-A009, Institute of Economics, Academia Sinica, Taipei, Taiwan.

  2. Hsu, Shih-Hsun & Kuan, Chung-Ming, 2014. "Constructing smooth tests without estimating the eigenpairs of the limiting process," Journal of Econometrics, Elsevier, vol. 178(P1), pages 71-79.

    Cited by:

    1. Guo, Xu & Li, Gao Rong & Wong, Wing Keung, 2014. "Specification Testing of Production Frontier Function in Stochastic Frontier Model," MPRA Paper 57999, University Library of Munich, Germany.

  3. Lee, Wei-Ming & Kuan, Chung-Ming & Hsu, Yu-Chin, 2014. "Testing over-identifying restrictions without consistent estimation of the asymptotic covariance matrix," Journal of Econometrics, Elsevier, vol. 181(2), pages 181-193.
    See citations under working paper version above.
  4. Yu-Chin Hsu & Chung-Ming Kuan & Meng-Feng Yen, 2014. "A Generalized Stepwise Procedure with Improved Power for Multiple Inequalities Testing," Journal of Financial Econometrics, Oxford University Press, vol. 12(4), pages 730-755.

    Cited by:

    1. Hassanniakalager, Arman & Sermpinis, Georgios & Stasinakis, Charalampos, 2021. "Trading the foreign exchange market with technical analysis and Bayesian Statistics," Journal of Empirical Finance, Elsevier, vol. 63(C), pages 230-251.
    2. Chiang, Mi-Hsiu & Chiu, Hsin-Yu & Kuo, Wei-Yu, 2021. "Predictive ability of similarity-based futures trading strategies," Pacific-Basin Finance Journal, Elsevier, vol. 68(C).
    3. Hsu, Po-Hsuan & Han, Qiheng & Wu, Wensheng & Cao, Zhiguang, 2018. "Asset allocation strategies, data snooping, and the 1 / N rule," Journal of Banking & Finance, Elsevier, vol. 97(C), pages 257-269.
    4. Hubert Dichtl, 2020. "Investing in the S&P 500 index: Can anything beat the buy‐and‐hold strategy?," Review of Financial Economics, John Wiley & Sons, vol. 38(2), pages 352-378, April.
    5. Dichtl, Hubert & Drobetz, Wolfgang & Neuhierl, Andreas & Wendt, Viktoria-Sophie, 2021. "Data snooping in equity premium prediction," International Journal of Forecasting, Elsevier, vol. 37(1), pages 72-94.
    6. Hubert Dichtl & Wolfgang Drobetz & Viktoria‐Sophie Wendt, 2021. "How to build a factor portfolio: Does the allocation strategy matter?," European Financial Management, European Financial Management Association, vol. 27(1), pages 20-58, January.
    7. Minyou Fan & Youwei Li & Ming Liao & Jiadong Liu, 2022. "A reexamination of factor momentum: How strong is it?," The Financial Review, Eastern Finance Association, vol. 57(3), pages 585-615, August.
    8. 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).
    9. Vincent, Kendro & Hsu, Yu-Chin & Lin, Hsiou-Wei, 2021. "Investment styles and the multiple testing of cross-sectional stock return predictability," Journal of Financial Markets, Elsevier, vol. 56(C).
    10. Yu-Chin Hsu & Hsiou-Wei Lin & Kendro Vincent, 2017. "Do Cross-Sectional Stock Return Predictors Pass the Test without Data-Snooping Bias?," IEAS Working Paper : academic research 17-A003, Institute of Economics, Academia Sinica, Taipei, Taiwan.
    11. Yang, Junmin & Cao, Zhiguang & Han, Qiheng & Wang, Qiyu, 2019. "Tactical asset allocation on technical trading rules and data snooping," Pacific-Basin Finance Journal, Elsevier, vol. 57(C).

  5. Ying, Yung-Hsiang & Kuan, Chung-Ming & Tung, Chris Y. & Chang, Koyin, 2013. "“Capital mobility in East Asian Countries is not so high”: Examining the impact of sterilization on capital flows," China Economic Review, Elsevier, vol. 24(C), pages 55-64.

    Cited by:

    1. Eslamloueyan, Karim & Jafari, Mahboubeh, 2014. "Financial crisis and saving–investment dynamics in the presence of cross-sectional dependence: The case of East Asia," China Economic Review, Elsevier, vol. 30(C), pages 209-220.
    2. Baharumshah, Ahmad Zubaidi & Soon, Siew-Voon & Wohar, Mark E., 2017. "Markov-switching analysis of exchange rate pass-through: Perspective from Asian countries," International Review of Economics & Finance, Elsevier, vol. 51(C), pages 245-257.

  6. Chung-Ming Kuan, 2013. "Markov switching model (in Russian)," Quantile, Quantile, issue 11, pages 13-40, December.

    Cited by:

    1. Agata Lozinskaia & Anastasiia Saltykova, 2019. "Fundamental Factors Affecting The Moex Russia Index: Structural Break Detection In A Long-Term Time Series," HSE Working papers WP BRP 77/FE/2019, National Research University Higher School of Economics.

  7. Chung-Ming Kuan & Chien-Liang Chen, 2013. "Effects of National Health Insurance on precautionary saving: new evidence from Taiwan," Empirical Economics, Springer, vol. 44(2), pages 921-943, April.

    Cited by:

    1. Sheu, Ji-Tian & Lu, Jui-fen Rachel, 2014. "The spillover effect of National Health Insurance on household consumption patterns: Evidence from a natural experiment in Taiwan," Social Science & Medicine, Elsevier, vol. 111(C), pages 41-49.
    2. Manger, Mark S. & Matthews, J. Scott, 2021. "Knowing when to splurge: Precautionary saving and Chinese-Canadians," Journal of Asian Economics, Elsevier, vol. 76(C).
    3. Chen, Chien-Hsun, 2023. "Is Taiwan’s Declining Public Investment a Crisis in the Making?," MPRA Paper 116513, University Library of Munich, Germany.
    4. Juan Rodriguez-Poo & Alexandra Soberón, 2015. "Differencing techniques in semi-parametric panel data varying coefficient models with fixed effects: a Monte Carlo study," Computational Statistics, Springer, vol. 30(3), pages 885-906, September.
    5. Lee, Daeyong, 2016. "Effects of dependent coverage mandate on household precautionary savings: Evidence from the 2010 Affordable Care Act," Economics Letters, Elsevier, vol. 147(C), pages 32-37.
    6. Joan Costa-i-Font & Cristina Vilaplana, 2016. "Does the Expansion of Public Long-Term Care Funding Affect Savings Behaviour?," CESifo Working Paper Series 6135, CESifo.
    7. Mark S. Manger & J. Scott Matthews, 2021. "Knowing When to Splurge: Precautionary Saving and Chinese-Canadians," Papers 2108.00519, arXiv.org.
    8. Lugilde, Alba & Bande, Roberto & Riveiro, Dolores, 2017. "Precautionary Saving: a review of the theory and the evidence," MPRA Paper 77511, University Library of Munich, Germany.

  8. Kao, Yi-Cheng & Kuan, Chung-Ming & Chen, Shikuan, 2013. "Testing the predictive power of the term structure without data snooping bias," Economics Letters, Elsevier, vol. 121(3), pages 546-549.

    Cited by:

    1. Ohnsorge,Franziska Lieselotte & Stocker,Marc & Some,Modeste Y., 2016. "Quantifying uncertainties in global growth forecasts," Policy Research Working Paper Series 7770, The World Bank.
    2. Gebka, Bartosz & Wohar, Mark E., 2018. "The predictive power of the yield spread for future economic expansions: Evidence from a new approach," Economic Modelling, Elsevier, vol. 75(C), pages 181-195.

  9. Hsu, Shih-Hsun & Kuan, Chung-Ming, 2011. "Estimation of conditional moment restrictions without assuming parameter identifiability in the implied unconditional moments," Journal of Econometrics, Elsevier, vol. 165(1), pages 87-99.

    Cited by:

    1. Parente, Paulo M.D.C. & Smith, Richard J., 2017. "Tests of additional conditional moment restrictions," Journal of Econometrics, Elsevier, vol. 200(1), pages 1-16.
    2. Xuexin WANG, 2021. "Instrumental variable estimation via a continuum of instruments with an application to estimating the elasticity of intertemporal substitution in consumption," Working Papers 2021-11-06, Wang Yanan Institute for Studies in Economics (WISE), Xiamen University.
    3. Laurent Davezies & Xavier D'Haultfoeuille & Martin Mugnier, 2020. "Fixed Effects Binary Choice Models with Three or More Periods," Papers 2009.08108, arXiv.org, revised Sep 2022.
    4. Han, Hyojin, 2020. "On the identification of models with conditional characteristic functions," Economics Letters, Elsevier, vol. 186(C).
    5. Sadat, Nafis, 2015. "Estimation of International Financial Integration: Evidence from European Countries," MPRA Paper 66283, University Library of Munich, Germany, revised 25 Aug 2015.

  10. Kuan, Chung-Ming & Lin, Hsin-Yi, 2010. "An encompassing test for non-nested quantile regression models," Economics Letters, Elsevier, vol. 107(2), pages 257-260, May.

    Cited by:

    1. Hsin-Yi Lin, 2011. "A robust test for non-nested hypotheses," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 95(1), pages 93-111, March.

  11. Hsu, Po-Hsuan & Hsu, Yu-Chin & Kuan, Chung-Ming, 2010. "Testing the predictive ability of technical analysis using a new stepwise test without data snooping bias," Journal of Empirical Finance, Elsevier, vol. 17(3), pages 471-484, June.

    Cited by:

    1. Coakley, Jerry & Marzano, Michele & Nankervis, John, 2016. "How profitable are FX technical trading rules?," International Review of Financial Analysis, Elsevier, vol. 45(C), pages 273-282.
    2. Costantini, Mauro & Crespo Cuaresma, Jesus & Hlouskova, Jaroslava, 2014. "Can Macroeconomists Get Rich Forecasting Exchange Rates?," Department of Economics Working Paper Series 176, WU Vienna University of Economics and Business.
    3. Lu, Tsung-Hsun & Chen, Yi-Chi & Hsu, Yu-Chin, 2015. "Trend definition or holding strategy: What determines the profitability of candlestick charting?," Journal of Banking & Finance, Elsevier, vol. 61(C), pages 172-183.
    4. Andriosopoulos, Kostas & Doumpos, Michael & Papapostolou, Nikos C. & Pouliasis, Panos K., 2013. "Portfolio optimization and index tracking for the shipping stock and freight markets using evolutionary algorithms," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 52(C), pages 16-34.
    5. Wang, Shan & Jiang, Zhi-Qiang & Li, Sai-Ping & Zhou, Wei-Xing, 2015. "Testing the performance of technical trading rules in the Chinese markets based on superior predictive test," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 439(C), pages 114-123.
    6. Bajgrowicz, Pierre & Scaillet, Olivier, 2012. "Technical trading revisited: False discoveries, persistence tests, and transaction costs," Journal of Financial Economics, Elsevier, vol. 106(3), pages 473-491.
    7. Hassanniakalager, Arman & Sermpinis, Georgios & Stasinakis, Charalampos, 2021. "Trading the foreign exchange market with technical analysis and Bayesian Statistics," Journal of Empirical Finance, Elsevier, vol. 63(C), pages 230-251.
    8. Yang Zhao & Charalampos Stasinakis & Georgios Sermpinis & Filipa Da Silva Fernandes, 2019. "Revisiting Fama–French factors' predictability with Bayesian modelling and copula‐based portfolio optimization," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 24(4), pages 1443-1463, October.
    9. Chiang, Mi-Hsiu & Chiu, Hsin-Yu & Kuo, Wei-Yu, 2021. "Predictive ability of similarity-based futures trading strategies," Pacific-Basin Finance Journal, Elsevier, vol. 68(C).
    10. Taylor, Mark & Hsu, Po-Hsuan & Wang, Zigan, 2020. "The Out-of-Sample Performance of Carry Trades," CEPR Discussion Papers 15052, C.E.P.R. Discussion Papers.
    11. Hsu, Po-Hsuan & Han, Qiheng & Wu, Wensheng & Cao, Zhiguang, 2018. "Asset allocation strategies, data snooping, and the 1 / N rule," Journal of Banking & Finance, Elsevier, vol. 97(C), pages 257-269.
    12. Zarrabi, Nima & Snaith, Stuart & Coakley, Jerry, 2017. "FX technical trading rules can be profitable sometimes!," International Review of Financial Analysis, Elsevier, vol. 49(C), pages 113-127.
    13. Jesus Crespo Cuaresma & Ines Fortin & Jaroslava Hlouskova, 2018. "Exchange rate forecasting and the performance of currency portfolios," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 37(5), pages 519-540, August.
    14. Hung, Chiayu & Lai, Hung-Neng, 2022. "Information asymmetry and the profitability of technical analysis," Journal of Banking & Finance, Elsevier, vol. 134(C).
    15. 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).
    16. Kuang, P. & Schröder, M. & Wang, Q., 2014. "Illusory profitability of technical analysis in emerging foreign exchange markets," International Journal of Forecasting, Elsevier, vol. 30(2), pages 192-205.
    17. Shynkevich, Andrei, 2012. "Short-term predictability of equity returns along two style dimensions," Journal of Empirical Finance, Elsevier, vol. 19(5), pages 675-685.
    18. Kevin Rink, 2023. "The predictive ability of technical trading rules: an empirical analysis of developed and emerging equity markets," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 37(4), pages 403-456, December.
    19. Kearney, Fearghal & Cummins, Mark & Murphy, Finbarr, 2014. "Outperformance in exchange-traded fund pricing deviations: Generalized control of data snooping bias," Journal of Financial Markets, Elsevier, vol. 19(C), pages 86-109.
    20. Jying‐Nan Wang & Hung‐Chun Liu & Jiangze Du & Yuan‐Teng Hsu, 2019. "Economic benefits of technical analysis in portfolio management: Evidence from global stock markets," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 24(2), pages 890-902, April.
    21. Christopher J. Neely & Paul A. Weller, 2011. "Technical analysis in the foreign exchange market," Working Papers 2011-001, Federal Reserve Bank of St. Louis.
    22. Suzuki, Tomoya & Ohkura, Yuushi, 2016. "Financial technical indicator based on chaotic bagging predictors for adaptive stock selection in Japanese and American markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 442(C), pages 50-66.
    23. Huang, Jing-Zhi & Huang, Zhijian (James), 2020. "Testing moving average trading strategies on ETFs," Journal of Empirical Finance, Elsevier, vol. 57(C), pages 16-32.
    24. Zongwu Cai & Jiancheng Jiang & Jingshuang Zhang & Xibin Zhang, 2015. "A new semiparametric test for superior predictive ability," Empirical Economics, Springer, vol. 48(1), pages 389-405, February.
    25. Joseph P. Romano & Michael Wolf, 2017. "Multiple testing of one-sided hypotheses: combining Bonferroni and the bootstrap," ECON - Working Papers 254, Department of Economics - University of Zurich.
    26. Taylor, Mark & Hsu, Po-Hsuan, 2014. "Forty Years, Thirty Currencies and 21,000 Trading Rules: A Large-scale, Data-Snooping Robust Analysis of Technical Trading in t," CEPR Discussion Papers 10018, C.E.P.R. Discussion Papers.
    27. Shynkevich, Andrei, 2012. "Performance of technical analysis in growth and small cap segments of the US equity market," Journal of Banking & Finance, Elsevier, vol. 36(1), pages 193-208.
    28. Shynkevich, Andrei, 2016. "Predictability in bond returns using technical trading rules," Journal of Banking & Finance, Elsevier, vol. 70(C), pages 55-69.
    29. Hong, Hui & Chen, Naiwei & O’Brien, Fergal & Ryan, James, 2018. "Stock return predictability and model instability: Evidence from mainland China and Hong Kong," The Quarterly Review of Economics and Finance, Elsevier, vol. 68(C), pages 132-142.
    30. Hubert Dichtl, 2020. "Investing in the S&P 500 index: Can anything beat the buy‐and‐hold strategy?," Review of Financial Economics, John Wiley & Sons, vol. 38(2), pages 352-378, April.
    31. Xiaoye Jin, 2022. "Evaluating the predictive power of intraday technical trading in China's crude oil market," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(7), pages 1416-1432, November.
    32. Dichtl, Hubert & Drobetz, Wolfgang & Neuhierl, Andreas & Wendt, Viktoria-Sophie, 2021. "Data snooping in equity premium prediction," International Journal of Forecasting, Elsevier, vol. 37(1), pages 72-94.
    33. Hubert Dichtl & Wolfgang Drobetz & Viktoria‐Sophie Wendt, 2021. "How to build a factor portfolio: Does the allocation strategy matter?," European Financial Management, European Financial Management Association, vol. 27(1), pages 20-58, January.
    34. Sermpinis, Georgios & Hassanniakalager, Arman & Stasinakis, Charalampos & Psaradellis, Ioannis, 2021. "Technical analysis profitability and Persistence: A discrete false discovery approach on MSCI indices," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 73(C).
    35. Christopher J. Bennett & Shabana Mitra, 2011. "Multidimensional Poverty: Measurement, Estimation, and Inference," OPHI Working Papers ophiwp047, Queen Elizabeth House, University of Oxford.
    36. Jin, Xiaoye, 2022. "Performance of intraday technical trading in China’s gold market," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 76(C).
    37. Hambuckers, J. & Ulm, M., 2023. "On the role of interest rate differentials in the dynamic asymmetry of exchange rates," Economic Modelling, Elsevier, vol. 129(C).
    38. Isakov, Dusan & Marti, Didier, 2011. "Technical Analysis with a Long-Term Perspective: Trading Strategies and Market Timing Ability," FSES Working Papers 421, Faculty of Economics and Social Sciences, University of Freiburg/Fribourg Switzerland.
    39. Flavio Ivo Riedlinger & João Nicolau, 2020. "The Profitability in the FTSE 100 Index: A New Markov Chain Approach," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 27(1), pages 61-81, March.
    40. Nima Zarrabi & Stuart Snaith & Jerry Coakley, 2022. "Exchange rate forecasting using economic models and technical trading rules," The European Journal of Finance, Taylor & Francis Journals, vol. 28(10), pages 997-1018, July.
    41. 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.
    42. 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.
    43. Eero P䴤ri & Mika Vilska, 2014. "Performance of moving average trading strategies over varying stock market conditions: the Finnish evidence," Applied Economics, Taylor & Francis Journals, vol. 46(24), pages 2851-2872, August.
    44. Urquhart, Andrew & Zhang, Hanxiong, 2019. "The performance of technical trading rules in Socially Responsible Investments," International Review of Economics & Finance, Elsevier, vol. 63(C), pages 397-411.
    45. Psaradellis, Ioannis & Laws, Jason & Pantelous, Athanasios A. & Sermpinis, Georgios, 2023. "Technical analysis, spread trading, and data snooping control," International Journal of Forecasting, Elsevier, vol. 39(1), pages 178-191.
    46. Hsu, Po-Hsuan & Taylor, Mark P. & Wang, Zigan, 2016. "Technical trading: Is it still beating the foreign exchange market?," Journal of International Economics, Elsevier, vol. 102(C), pages 188-208.
    47. Dan Anghel, 2013. "How Reliable is the Moving Average Crossover Rule for an Investor on the Romanian Stock Market?," 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. 5(2), pages 089-115, December.
    48. Qing Zhou & Robert Faff, 2017. "The complementary role of cross-sectional and time-series information in forecasting stock returns," Australian Journal of Management, Australian School of Business, vol. 42(1), pages 113-139, February.
    49. Christopher J. Bennett, 2009. "p-Value Adjustments for Asymptotic Control of the Generalized Familywise Error Rate," Vanderbilt University Department of Economics Working Papers 0905, Vanderbilt University Department of Economics.
    50. Mihai Cristian Dinică & Erica Cristina (Balea) Dinică, 2015. "Testing the Weak-Form Market Eficiency of the Euronext Wheat," Romanian Economic Journal, Department of International Business and Economics from the Academy of Economic Studies Bucharest, vol. 18(55), pages 25-38, March.
    51. 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).
    52. Hui Hong & Zhicun Bian & Chien-Chiang Lee, 2021. "COVID-19 and instability of stock market performance: evidence from the U.S," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-18, December.
    53. Vincent, Kendro & Hsu, Yu-Chin & Lin, Hsiou-Wei, 2021. "Investment styles and the multiple testing of cross-sectional stock return predictability," Journal of Financial Markets, Elsevier, vol. 56(C).
    54. Shynkevich, Andrei, 2013. "Time-series momentum as an intra- and inter-industry effect: Implications for market efficiency," Journal of Economics and Business, Elsevier, vol. 69(C), pages 64-85.
    55. Kao, Yi-Cheng & Kuan, Chung-Ming & Chen, Shikuan, 2013. "Testing the predictive power of the term structure without data snooping bias," Economics Letters, Elsevier, vol. 121(3), pages 546-549.
    56. Anghel, Dan Gabriel, 2022. "No pain, no gain: You should always incorporate trading costs for a bias-free evaluation of trading rule overperformance," Economics Letters, Elsevier, vol. 216(C).
    57. Yu-Chin Hsu & Hsiou-Wei Lin & Kendro Vincent, 2017. "Do Cross-Sectional Stock Return Predictors Pass the Test without Data-Snooping Bias?," IEAS Working Paper : academic research 17-A003, Institute of Economics, Academia Sinica, Taipei, Taiwan.
    58. Georgios Sermpinis & Arman Hassanniakalager & Charalampos Stasinakis & Ioannis Psaradellis, 2018. "Technical Analysis and Discrete False Discovery Rate: Evidence from MSCI Indices," Papers 1811.06766, arXiv.org, revised Jun 2019.
    59. Chen, Shi & Bao, Si & Zhou, Yu, 2016. "The predictive power of Japanese candlestick charting in Chinese stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 457(C), pages 148-165.
    60. Zongwu Cai & Jiancheng Jiang & Jingshuang Zhang, 2013. "A New Test for Superior Predictive Ability," Working Papers 2013-10-14, Wang Yanan Institute for Studies in Economics (WISE), Xiamen University.
    61. Yang, Junmin & Cao, Zhiguang & Han, Qiheng & Wang, Qiyu, 2019. "Tactical asset allocation on technical trading rules and data snooping," Pacific-Basin Finance Journal, Elsevier, vol. 57(C).

  12. Chuang, Chia-Chang & Kuan, Chung-Ming & Lin, Hsin-Yi, 2009. "Causality in quantiles and dynamic stock return-volume relations," Journal of Banking & Finance, Elsevier, vol. 33(7), pages 1351-1360, July.
    See citations under working paper version above.
  13. Kuan, Chung-Ming & Yeh, Jin-Huei & Hsu, Yu-Chin, 2009. "Assessing value at risk with CARE, the Conditional Autoregressive Expectile models," Journal of Econometrics, Elsevier, vol. 150(2), pages 261-270, June.

    Cited by:

    1. Taoufik Bouezmarni & Mohamed Doukali & Abderrahim Taamouti, 2023. "Testing Granger Non-Causality in Expectiles," University of East Anglia School of Economics Working Paper Series 2023-02, School of Economics, University of East Anglia, Norwich, UK..
    2. Xiu Xu & Andrija Mihoci & Wolfgang Karl Hardle, 2020. "lCARE -- localizing Conditional AutoRegressive Expectiles," Papers 2009.13215, arXiv.org.
    3. Hamidi, Benjamin & Maillet, Bertrand & Prigent, Jean-Luc, 2014. "A dynamic autoregressive expectile for time-invariant portfolio protection strategies," Journal of Economic Dynamics and Control, Elsevier, vol. 46(C), pages 1-29.
    4. Daouia, Abdelaati & Girard, Stéphane & Stupfler, Gilles, 2017. "Extreme M-quantiles as risk measures: From L1 to Lp optimization," TSE Working Papers 17-841, Toulouse School of Economics (TSE).
    5. Alex Huang, 2013. "Value at risk estimation by quantile regression and kernel estimator," Review of Quantitative Finance and Accounting, Springer, vol. 41(2), pages 225-251, August.
    6. Edgars Jakobsons & Steven Vanduffel, 2015. "Dependence Uncertainty Bounds for the Expectile of a Portfolio," Risks, MDPI, vol. 3(4), pages 1-25, December.
    7. López-Espinosa, Germán & Moreno, Antonio & Rubia, Antonio & Valderrama, Laura, 2015. "Systemic risk and asymmetric responses in the financial industry," Journal of Banking & Finance, Elsevier, vol. 58(C), pages 471-485.
    8. Song, Song & Ritov, Ya’acov & Härdle, Wolfgang K., 2012. "Bootstrap confidence bands and partial linear quantile regression," Journal of Multivariate Analysis, Elsevier, vol. 107(C), pages 244-262.
    9. Daouia, Abdelaati & Girard, Stéphane & Stupfler, Gilles, 2018. "Tail expectile process and risk assessment," TSE Working Papers 18-944, Toulouse School of Economics (TSE).
    10. Yundong Tu & Siwei Wang, 2023. "Variable Screening and Model Averaging for Expectile Regressions," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 85(3), pages 574-598, June.
    11. Litimein, Ouahiba & Laksaci, Ali & Mechab, Boubaker & Bouzebda, Salim, 2023. "Local linear estimate of the functional expectile regression," Statistics & Probability Letters, Elsevier, vol. 192(C).
    12. Tran, Ngoc M. & Burdejová, Petra & Ospienko, Maria & Härdle, Wolfgang K., 2019. "Principal component analysis in an asymmetric norm," Journal of Multivariate Analysis, Elsevier, vol. 171(C), pages 1-21.
    13. Wang, Bingling & Li, Yingxing & Härdle, Wolfgang, 2021. "K-expectiles clustering," IRTG 1792 Discussion Papers 2021-003, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    14. Daouia, Abdelaati & Padoan, Simone A. & Stupfler, Gilles, 2023. "Extreme expectile estimation for short-tailed data, with an application to market risk assessment," TSE Working Papers 23-1414, Toulouse School of Economics (TSE).
    15. Stéphane Girard & Gilles Claude Stupfler & Antoine Usseglio-Carleve, 2021. "Extreme Conditional Expectile Estimation in Heavy-Tailed Heteroscedastic Regression Models," Post-Print hal-03306230, HAL.
    16. Jakobsons Edgars, 2016. "Scenario aggregation method for portfolio expectile optimization," Statistics & Risk Modeling, De Gruyter, vol. 33(1-2), pages 51-65, September.
    17. Natalia Nolde & Johanna F. Ziegel, 2016. "Elicitability and backtesting: Perspectives for banking regulation," Papers 1608.05498, arXiv.org, revised Feb 2017.
    18. Carol Alexander & José María Sarabia, 2012. "Quantile Uncertainty and Value‐at‐Risk Model Risk," Risk Analysis, John Wiley & Sons, vol. 32(8), pages 1293-1308, August.
    19. Andrea Bastianin & Marzio Galeotti & Matteo Manera, 2013. "Food versus Fuel: Causality and Predictability in Distribution," Working Papers 2013.23, Fondazione Eni Enrico Mattei.
    20. Ngoc Mai Tran & Maria Osipenko & Wolfgang Karl Härdle, 2014. "Principal Component Analysis in an Asymmetric Norm," SFB 649 Discussion Papers SFB649DP2014-001, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    21. Dingshi Tian & Zongwu Cai & Ying Fang, 2018. "Econometric Modeling of Risk Measures: A Selective Review of the Recent Literature," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 201807, University of Kansas, Department of Economics, revised Oct 2018.
    22. Abdelaati Daouia & Stéphane Girard & Gilles Stupfler, 2018. "Estimation of tail risk based on extreme expectiles," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 80(2), pages 263-292, March.
    23. Mohammedi, Mustapha & Bouzebda, Salim & Laksaci, Ali, 2021. "The consistency and asymptotic normality of the kernel type expectile regression estimator for functional data," Journal of Multivariate Analysis, Elsevier, vol. 181(C).
    24. Marcelo Bianconi & Xiaxin Hua & Chih Ming Tan, 2013. "Determinants of Systemic Risk and Information Dissemination," Working Paper series 67_13, Rimini Centre for Economic Analysis.
    25. Tu, Yundong & Wang, Siwei, 2020. "Jackknife model averaging for expectile regressions in increasing dimension," Economics Letters, Elsevier, vol. 197(C).
    26. Shih-Kang Chao & Wolfgang K. Härdle & Chen Huang, 2016. "Multivariate Factorisable Sparse Asymmetric Least Squares Regression," SFB 649 Discussion Papers SFB649DP2016-058, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    27. Tae-Hwy Lee & Aman Ullah & He Wang, 2018. "The Second-order Asymptotic Properties of Asymmetric Least Squares Estimation," Working Papers 201910, University of California at Riverside, Department of Economics.
    28. Taoufik Bouezmarni & Mohamed Doukali & Abderrahim Taamouti, 2022. "Testing Granger Non-Causality in Expectiles," Working Papers 202207, University of Liverpool, Department of Economics.
    29. Xu, Xiu & Mihoci, Andrija & Härdle, Wolfgang Karl, 2018. "lCARE - localizing conditional autoregressive expectiles," Journal of Empirical Finance, Elsevier, vol. 48(C), pages 198-220.
    30. Zhang, Yue-Jun & Bouri, Elie & Gupta, Rangan & Ma, Shu-Jiao, 2021. "Risk spillover between Bitcoin and conventional financial markets: An expectile-based approach," The North American Journal of Economics and Finance, Elsevier, vol. 55(C).
    31. Härdle, Wolfgang Karl & Ling, Chengxiu, 2018. "How Sensitive are Tail-related Risk Measures in a Contamination Neighbourhood?," IRTG 1792 Discussion Papers 2018-010, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    32. Garcia-Jorcano, Laura & Sanchis-Marco, Lidia, 2021. "Systemic-systematic risk in financial system: A dynamic ranking based on expectiles," International Review of Economics & Finance, Elsevier, vol. 75(C), pages 330-365.
    33. Yao, Yinhong & Li, Jianping & Sun, Xiaolei, 2021. "Measuring the risk of Chinese Fintech industry: evidence from the stock index," Finance Research Letters, Elsevier, vol. 39(C).
    34. Ren, Rui & Lu, Meng-Jou & Li, Yingxing & Härdle, Wolfgang, 2021. "Financial Risk Meter based on expectiles," IRTG 1792 Discussion Papers 2021-008, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    35. Marcel, Bräutigam & Marie, Kratz, 2018. "On the Dependence between Quantiles and Dispersion Estimators," ESSEC Working Papers WP1807, ESSEC Research Center, ESSEC Business School.
    36. Stupfler, Gilles & Yang, Fan, 2018. "Analyzing And Predicting Cat Bond Premiums: A Financial Loss Premium Principle And Extreme Value Modeling," ASTIN Bulletin, Cambridge University Press, vol. 48(1), pages 375-411, January.
    37. Marcel Brautigam & Marie Kratz, 2020. "The Impact of the Choice of Risk and Dispersion Measure on Procyclicality," Papers 2001.00529, arXiv.org.
    38. Ying Fu & Kien Ng & Boray Huang & Huei Huang, 2015. "Portfolio optimization with transaction costs: a two-period mean-variance model," Annals of Operations Research, Springer, vol. 233(1), pages 135-156, October.
    39. Lina Liao & Cheolwoo Park & Hosik Choi, 2019. "Penalized expectile regression: an alternative to penalized quantile regression," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 71(2), pages 409-438, April.
    40. Zongwu Cai & Ying Fang & Dingshi Tian, 2018. "Assessing Tail Risk Using Expectile Regressions with Partially Varying Coefficients," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 201804, University of Kansas, Department of Economics, revised Oct 2018.
    41. Ren, Rui & Lu, Meng-Jou & Li, Yingxing & Härdle, Wolfgang Karl, 2022. "Financial Risk Meter FRM based on Expectiles," Journal of Multivariate Analysis, Elsevier, vol. 189(C).
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    43. Johanna F. Ziegel, 2013. "Coherence and elicitability," Papers 1303.1690, arXiv.org, revised Mar 2014.
    44. James Ming Chen, 2018. "On Exactitude in Financial Regulation: Value-at-Risk, Expected Shortfall, and Expectiles," Risks, MDPI, vol. 6(2), pages 1-28, June.
    45. Daouia, Abdelaati & Girard, Stéphane & Stupfler, Gilles, 2021. "ExpectHill estimation, extreme risk and heavy tails," Journal of Econometrics, Elsevier, vol. 221(1), pages 97-117.
    46. Laura Garcia-Jorcano & Lidia Sanchis-Marco, 2023. "Measuring Systemic Risk Using Multivariate Quantile-Located ES Models," Journal of Financial Econometrics, Oxford University Press, vol. 21(1), pages 1-72.
    47. Fabio Busetti & Michele Caivano & Davide Delle Monache & Claudia Pacella, 2020. "The time-varying risk of Italian GDP," Temi di discussione (Economic working papers) 1288, Bank of Italy, Economic Research and International Relations Area.
    48. Yingying Jiang & Fuming Lin & Yong Zhou, 2021. "The kth power expectile regression," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 73(1), pages 83-113, February.
    49. Zhang, Feipeng & Li, Qunhua, 2017. "A continuous threshold expectile model," Computational Statistics & Data Analysis, Elsevier, vol. 116(C), pages 49-66.
    50. Shangyu Xie & Yong Zhou & Alan T. K. Wan, 2014. "A Varying-Coefficient Expectile Model for Estimating Value at Risk," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 32(4), pages 576-592, October.
    51. Francesca Mariani & Gloria Polinesi & Maria Cristina Recchioni, 2022. "A tail-revisited Markowitz mean-variance approach and a portfolio network centrality," Computational Management Science, Springer, vol. 19(3), pages 425-455, July.
    52. Zongxia Liang & Jianming Xia & Keyu Zhang, 2023. "Equilibrium stochastic control with implicitly defined objective functions," Papers 2312.15173, arXiv.org, revised Dec 2023.
    53. Andrea C. Hupman & Jay Simon, 2023. "The Legacy of Peter Fishburn: Foundational Work and Lasting Impact," Decision Analysis, INFORMS, vol. 20(1), pages 1-15, March.
    54. Damiano Rossello, 2022. "Performance measurement with expectiles," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 45(1), pages 343-374, June.
    55. Taylor, James W., 2021. "Evaluating quantile-bounded and expectile-bounded interval forecasts," International Journal of Forecasting, Elsevier, vol. 37(2), pages 800-811.
    56. Carol Alexander & Jose Maria Sarabia, 2010. "Endogenizing Model Risk to Quantile Estimates," ICMA Centre Discussion Papers in Finance icma-dp2010-07, Henley Business School, University of Reading.
    57. Daouia, Abdelaati & Paindaveine, Davy, 2019. "Multivariate Expectiles, Expectile Depth and Multiple-Output Expectile Regression," TSE Working Papers 19-1022, Toulouse School of Economics (TSE), revised Feb 2023.
    58. Huang, Xiaolin & Shi, Lei & Suykens, Johan A.K., 2014. "Asymmetric least squares support vector machine classifiers," Computational Statistics & Data Analysis, Elsevier, vol. 70(C), pages 395-405.
    59. Huang, Alex YiHou, 2010. "An optimization process in Value-at-Risk estimation," Review of Financial Economics, Elsevier, vol. 19(3), pages 109-116, August.
    60. Daouia, Abdelaati & Stupfler, Gilles & Usseglio-Carleve, Antoine, 2023. "An expectile computation cookbook," TSE Working Papers 23-1458, Toulouse School of Economics (TSE).
    61. Zhang, Yue-Jun & Ma, Shu-Jiao, 2019. "How to effectively estimate the time-varying risk spillover between crude oil and stock markets? Evidence from the expectile perspective," Energy Economics, Elsevier, vol. 84(C).
    62. Girard, Stéphane & Stupfler, Gilles & Usseglio-Carleve, Antoine, 2022. "Functional estimation of extreme conditional expectiles," Econometrics and Statistics, Elsevier, vol. 21(C), pages 131-158.
    63. Zaevski, Tsvetelin S. & Nedeltchev, Dragomir C., 2023. "From BASEL III to BASEL IV and beyond: Expected shortfall and expectile risk measures," International Review of Financial Analysis, Elsevier, vol. 87(C).
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    66. Mucahit Aygun & Fabio Bellini & Roger J. A. Laeven, 2023. "Elicitability of Return Risk Measures," Papers 2302.13070, arXiv.org, revised Mar 2023.
    67. Alex YiHou Huang, 2010. "An optimization process in Value‐at‐Risk estimation," Review of Financial Economics, John Wiley & Sons, vol. 19(3), pages 109-116, August.
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    69. Antonio Rubia Serrano & Lidia Sanchis-Marco, 2015. "Measuring Tail-Risk Cross-Country Exposures in the Banking Industry," Working Papers. Serie AD 2015-01, Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie).
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    72. Wolfgang Karl Härdle & Ya’acov Ritov & Song Song, 2010. "Partial Linear Quantile Regression and Bootstrap Confidence Bands," SFB 649 Discussion Papers SFB649DP2010-002, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    73. Shih-Kang Chao & Wolfgang Karl Härdle & Weining Wang, 2012. "Quantile Regression in Risk Calibration," SFB 649 Discussion Papers SFB649DP2012-006, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    74. Gao, Suhao & Yu, Zhen, 2023. "Parametric expectile regression and its application for premium calculation," Insurance: Mathematics and Economics, Elsevier, vol. 111(C), pages 242-256.
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    76. Yen, Yu-Min & Yen, Tso-Jung, 2021. "Testing forecast accuracy of expectiles and quantiles with the extremal consistent loss functions," International Journal of Forecasting, Elsevier, vol. 37(2), pages 733-758.

  14. Kuan, Chung-Ming & Hsieh, Yu-Wei, 2008. "Improved HAC covariance matrix estimation based on forecast errors," Economics Letters, Elsevier, vol. 99(1), pages 89-92, April.
    See citations under working paper version above.
  15. Huang, Yu-Lieh & Huang, Chao-Hsi & Kuan, Chung-Ming, 2008. "Reexamining the permanent income hypothesis with uncertainty in permanent and transitory innovation states," Journal of Macroeconomics, Elsevier, vol. 30(4), pages 1816-1836, December.

    Cited by:

    1. Garz, Marcel, 2014. "Consumption, labor income uncertainty, and economic news coverage," MPRA Paper 56076, University Library of Munich, Germany.
    2. Rolando Peláez, 2012. "The housing bubble in real-time: the end of innocence," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 36(1), pages 211-225, January.
    3. Mowlaei , Mohammad & Intezar , Aburaihan, 2019. "The Effects of Social Characteristics of Iranian Households on Food Consumption Expenditures," Journal of Money and Economy, Monetary and Banking Research Institute, Central Bank of the Islamic Republic of Iran, vol. 14(4), pages 555-572, October.
    4. Liping Gao & Hyeongwoo Kim & Yaoqi Zhang, 2013. "Revisiting the Empirical Inconsistency of the Permanent Income Hypothesis: Evidence from Rural China," Auburn Economics Working Paper Series auwp2013-05, Department of Economics, Auburn University.

  16. Hsu, Yu-Chin & Kuan, Chung-Ming, 2008. "Change-point estimation of nonstationary I(d) processes," Economics Letters, Elsevier, vol. 98(2), pages 115-121, February.
    See citations under working paper version above.
  17. Chen, Yi-Ting & Kuan, Chung-Ming, 2007. "Corrigendum to "The pseudo-true score encompassing test for non-nested hypotheses": [Journal of Econometrics 106, 271-295]," Journal of Econometrics, Elsevier, vol. 141(2), pages 1412-1417, December.

    Cited by:

    1. Kuan, Chung-Ming & Lin, Hsin-Yi, 2010. "An encompassing test for non-nested quantile regression models," Economics Letters, Elsevier, vol. 107(2), pages 257-260, May.

  18. Chen, Chien-Liang & Kuan, Chung-Ming & Lin, Chu-Chia, 2007. "Saving and housing of Taiwanese households: New evidence from quantile regression analyses," Journal of Housing Economics, Elsevier, vol. 16(2), pages 102-126, June.

    Cited by:

    1. Yi-Hsien Wang & Jui-Cheng Hung & Yen-Hsien Lee & Chung-Chu Chuang, 2012. "Computing regression quantiles to analysis the relationship between market behavior and political risk," Quality & Quantity: International Journal of Methodology, Springer, vol. 46(4), pages 1047-1055, June.
    2. Carlos P. Barros & Luis A. Gil-Alana, 2013. "The Housing Markets in Spain and Portugal: Evidence of Persistence," Review of Economics & Finance, Better Advances Press, Canada, vol. 3, pages 19-32, November.
    3. Yi-Hsien Wang & Jui-Cheng Hung & Hsiu-Hsueh Kao & Kuang-Hsun Shih, 2011. "Long-term relationship between political behavior and stock market return: new evidence from quantile regression," Quality & Quantity: International Journal of Methodology, Springer, vol. 45(6), pages 1361-1367, October.
    4. JINJI Naoto & ZHANG Xingyuan & HARUNA Shoji, 2011. "Does Tobin's q Matter for Firms' Choices of Globalization Mode?," Discussion papers 11061, Research Institute of Economy, Trade and Industry (RIETI).
    5. A. Talha Yalta, 2011. "A Model of Down Payment Saving," Working Papers 1101, TOBB University of Economics and Technology, Department of Economics.
    6. Peng, Ying & Tian, Chuanhao & Wen, Haizhen, 2021. "How does school district adjustment affect housing prices: An empirical investigation from Hangzhou, China," China Economic Review, Elsevier, vol. 69(C).
    7. Kelly, Connor & McCann, Fergal, 2016. "Rental markets, savings and the accumulation of mortgage deposits," Quarterly Bulletin Articles, Central Bank of Ireland, pages 56-70, October.
    8. Carmiña O: Vargas, 2011. "Desigualdad de salarios en Colombia: evidencia a partir de encuestas de hogares 1984 - 2010," Borradores de Economia 8808, Banco de la Republica.
    9. Bussière, Matthieu & Kalantzis, Yannick & Lafarguette, Romain & Sicular, Terry, 2013. "Understanding household savings in China: the role of the housing market and borrowing constraints," MPRA Paper 44611, University Library of Munich, Germany.
    10. Juanita Cifuentes González & John Werner Meisterl Reyes, 2014. "El Ahorro de los Hogares Colombianos: un análisis microeconómico mediante regresión cuantílica," Vniversitas Económica 12541, Universidad Javeriana - Bogotá.
    11. Can Xu & Andreas Steiner, 2022. "Does Public Employment Affect Household Saving Rates? Evidence from Chinese Household Data," CESifo Working Paper Series 9741, CESifo.
    12. Jose Torres-Pruñonosa & Pablo García-Estévez & Josep Maria Raya & Camilo Prado-Román, 2022. "How on Earth Did Spanish Banking Sell the Housing Stock?," SAGE Open, , vol. 12(1), pages 21582440221, March.

  19. Kuan, Chung-Ming & Lee, Wei-Ming, 2006. "Robust M Tests Without Consistent Estimation of the Asymptotic Covariance Matrix," Journal of the American Statistical Association, American Statistical Association, vol. 101, pages 1264-1275, September.

    Cited by:

    1. Heejoon Han & Oliver Linton & Tatsushi Oka & Yoon-Jae Whang, 2014. "The Cross-Quantilogram: Measuring Quantile Dependence and Testing Directional Predictability between Time Series," Cambridge Working Papers in Economics 1452, Faculty of Economics, University of Cambridge.
    2. Ippei Fujiwara & Lena Mareen Korber & Daisuke Nagakura, 2011. "How much asymmetry is there in bond returns and exchange rates?," Globalization Institute Working Papers 93, Federal Reserve Bank of Dallas.
    3. Wei-Ming Lee & Chung-Ming Kuan, 2006. "Testing Over-Identifying Restrictions without Consistent Estimation of the Asymptotic Covariance Matrix," IEAS Working Paper : academic research 06-A009, Institute of Economics, Academia Sinica, Taipei, Taiwan.
    4. Lee, Wei-Ming, 2007. "Robust M tests using kernel-based estimators with bandwidth equal to sample size," Economics Letters, Elsevier, vol. 96(3), pages 295-300, September.
    5. Yi-Ting Chen & Zhongjun Qu, 2015. "M Tests with a New Normalization Matrix," Econometric Reviews, Taylor & Francis Journals, vol. 34(5), pages 617-652, May.
    6. Chen Yi-Ting & Lin Chang-Ching, 2008. "On the Robustness of Symmetry Tests for Stock Returns," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 12(2), pages 1-40, May.
    7. Yacouba Boubacar Maïnassara & Youssef Esstafa & Bruno Saussereau, 2021. "Estimating FARIMA models with uncorrelated but non-independent error terms," Statistical Inference for Stochastic Processes, Springer, vol. 24(3), pages 549-608, October.
    8. Guay, Alain & Guerre, Emmanuel & Lazarová, Štěpána, 2013. "Robust adaptive rate-optimal testing for the white noise hypothesis," Journal of Econometrics, Elsevier, vol. 176(2), pages 134-145.
    9. Sun, Yixiao & Kaplan, David M., 2011. "A New Asymptotic Theory for Vector Autoregressive Long-run Variance Estimation and Autocorrelation Robust Testing," University of California at San Diego, Economics Working Paper Series qt8cx0t4gc, Department of Economics, UC San Diego.
    10. Zhang, Xianyang & Shao, Xiaofeng, 2013. "On a general class of long run variance estimators," Economics Letters, Elsevier, vol. 120(3), pages 437-441.

  20. Kuan, Chung-Ming & Huang, Yu-Lieh & Tsay, Ruey S., 2005. "An Unobserved-Component Model With Switching Permanent and Transitory Innovations," Journal of Business & Economic Statistics, American Statistical Association, vol. 23, pages 443-454, October.

    Cited by:

    1. Yu-Lieh Huang, 2009. "Identifying turbulent and calm regimes in stock prices: evidence from the Taiwan stock market," Applied Economics Letters, Taylor & Francis Journals, vol. 16(14), pages 1477-1481.
    2. Huang, Yu-Lieh & Huang, Chao-Hsi & Kuan, Chung-Ming, 2008. "Reexamining the permanent income hypothesis with uncertainty in permanent and transitory innovation states," Journal of Macroeconomics, Elsevier, vol. 30(4), pages 1816-1836, December.
    3. Huang, Yu-Lieh, 2012. "Measuring business cycles: A temporal disaggregation model with regime switching," Economic Modelling, Elsevier, vol. 29(2), pages 283-290.
    4. 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.
    5. Lee, Hwa-Taek & Yoon, Gawon, 2007. "Does Purchasing Power Parity Hold Sometimes? Regime Switching in Real Exchange Rates," Economics Working Papers 2007-24, Christian-Albrechts-University of Kiel, Department of Economics.
    6. Sinclair Tara M, 2009. "Asymmetry in the Business Cycle: Friedman's Plucking Model with Correlated Innovations," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 14(1), pages 1-31, December.
    7. Yu-Lieh Huang & Chao-Hsi Huang, 2007. "The persistence of Taiwan's output fluctuations: an empirical study using innovation regime-switching model," Applied Economics, Taylor & Francis Journals, vol. 39(20), pages 2673-2679.
    8. Gloria González-Rivera & Tae-Hwy Lee, 2007. "Nonlinear Time Series in Financial Forecasting," Working Papers 200803, University of California at Riverside, Department of Economics, revised Feb 2008.
    9. Huang, Yu-Lieh & Huang, Chao-Hsi, 2015. "Uncertain Effects Of Shocks Vs. Uncertain Unit Root: An Alternative View Of U.S. Real Gdp," Hitotsubashi Journal of Economics, Hitotsubashi University, vol. 56(1), pages 117-134, June.
    10. Yu-Lieh Huang & Chia-Wen Ho, 2008. "Demarcating stable and turbulent regimes in Taiwan's stock market," Economics Bulletin, AccessEcon, vol. 3(35), pages 1-11.
    11. Marian Vavra, 2016. "Testing the Validity of Assumptions of UC-ARIMA Models for Trend-Cycle Decompositions," Working and Discussion Papers WP 4/2016, Research Department, National Bank of Slovakia.

  21. Po-Hsuan Hsu & Chung-Ming Kuan, 2005. "Reexamining the Profitability of Technical Analysis with Data Snooping Checks," Journal of Financial Econometrics, Oxford University Press, vol. 3(4), pages 606-628.

    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. Coakley, Jerry & Marzano, Michele & Nankervis, John, 2016. "How profitable are FX technical trading rules?," International Review of Financial Analysis, Elsevier, vol. 45(C), pages 273-282.
    3. Wang, Shan & Jiang, Zhi-Qiang & Li, Sai-Ping & Zhou, Wei-Xing, 2015. "Testing the performance of technical trading rules in the Chinese markets based on superior predictive test," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 439(C), pages 114-123.
    4. Bajgrowicz, Pierre & Scaillet, Olivier, 2012. "Technical trading revisited: False discoveries, persistence tests, and transaction costs," Journal of Financial Economics, Elsevier, vol. 106(3), pages 473-491.
    5. Hassanniakalager, Arman & Sermpinis, Georgios & Stasinakis, Charalampos, 2021. "Trading the foreign exchange market with technical analysis and Bayesian Statistics," Journal of Empirical Finance, Elsevier, vol. 63(C), pages 230-251.
    6. Chiang, Mi-Hsiu & Chiu, Hsin-Yu & Kuo, Wei-Yu, 2021. "Predictive ability of similarity-based futures trading strategies," Pacific-Basin Finance Journal, Elsevier, vol. 68(C).
    7. Bekiros, Stelios D., 2015. "Heuristic learning in intraday trading under uncertainty," Journal of Empirical Finance, Elsevier, vol. 30(C), pages 34-49.
    8. Taylor, Mark & Hsu, Po-Hsuan & Wang, Zigan, 2020. "The Out-of-Sample Performance of Carry Trades," CEPR Discussion Papers 15052, C.E.P.R. Discussion Papers.
    9. Siroos Khademalomoom & Paresh Kumar Narayan & Susan Sunila Sharma, 2019. "Higher Moments and Exchange Rate Behavior," The Financial Review, Eastern Finance Association, vol. 54(1), pages 201-229, February.
    10. Lu, Tsung-Hsun, 2014. "The profitability of candlestick charting in the Taiwan stock market," Pacific-Basin Finance Journal, Elsevier, vol. 26(C), pages 65-78.
    11. Hsu, Po-Hsuan & Han, Qiheng & Wu, Wensheng & Cao, Zhiguang, 2018. "Asset allocation strategies, data snooping, and the 1 / N rule," Journal of Banking & Finance, Elsevier, vol. 97(C), pages 257-269.
    12. Jurdi, Doureige & Kim, Jae, 2019. "Predicting the U.S. Stock Market Return: Evidence from the Improved Augmented Regression Method," MPRA Paper 94028, University Library of Munich, Germany.
    13. Zarrabi, Nima & Snaith, Stuart & Coakley, Jerry, 2017. "FX technical trading rules can be profitable sometimes!," International Review of Financial Analysis, Elsevier, vol. 49(C), pages 113-127.
    14. Amélie Charles & Olivier Darné & Jae H. Kim, 2010. "Exchange-Rate Return Predictability and the Adaptive Markets Hypothesis: Evidence from Major Foreign Exchange Rates," Working Papers hal-00547722, HAL.
    15. Vlad Pavlov & Stan Hurn, 2009. "Testing the Profitability of Technical Analysis as a Portfolio Selection Strategy," NCER Working Paper Series 52, National Centre for Econometric Research.
    16. Yafeng Qin & Guoyao Pan & Min Bai, 2020. "Improving market timing of time series momentum in the Chinese stock market," Applied Economics, Taylor & Francis Journals, vol. 52(43), pages 4711-4725, September.
    17. Stelios Bekiros & Dimitris Georgoutsos, 2008. "Non-linear dynamics in financial asset returns: the predictive power of the CBOE volatility index," The European Journal of Finance, Taylor & Francis Journals, vol. 14(5), pages 397-408.
    18. Nikolai Dokuchaev, 2007. "Mean-Reverting Market Model: Speculative Opportunities and Non-Arbitrage," Applied Mathematical Finance, Taylor & Francis Journals, vol. 14(4), pages 319-337.
    19. Hung, Chiayu & Lai, Hung-Neng, 2022. "Information asymmetry and the profitability of technical analysis," Journal of Banking & Finance, Elsevier, vol. 134(C).
    20. 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.
    21. Kuang, P. & Schröder, M. & Wang, Q., 2014. "Illusory profitability of technical analysis in emerging foreign exchange markets," International Journal of Forecasting, Elsevier, vol. 30(2), pages 192-205.
    22. A. Olasolo & M. A. Pérez & V. Ruiz, 2016. "Active investment strategies in the Spanish futures market: a solution to avoid data snooping bias," Applied Economics Letters, Taylor & Francis Journals, vol. 23(9), pages 609-613, June.
    23. Shynkevich, Andrei, 2012. "Short-term predictability of equity returns along two style dimensions," Journal of Empirical Finance, Elsevier, vol. 19(5), pages 675-685.
    24. Fong, Tom Pak Wing & Wu, Shui Tang, 2020. "Predictability in sovereign bond returns using technical trading rules: Do developed and emerging markets differ?," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
    25. Kevin Rink, 2023. "The predictive ability of technical trading rules: an empirical analysis of developed and emerging equity markets," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 37(4), pages 403-456, December.
    26. Tsung-Hsun Lu & Yung-Ming Shiu, 2016. "Can 1-day candlestick patterns be profitable on the 30 component stocks of the DJIA?," Applied Economics, Taylor & Francis Journals, vol. 48(35), pages 3345-3354, July.
    27. Taylor, Mark & Hsu, Po-Hsuan, 2014. "Forty Years, Thirty Currencies and 21,000 Trading Rules: A Large-scale, Data-Snooping Robust Analysis of Technical Trading in t," CEPR Discussion Papers 10018, C.E.P.R. Discussion Papers.
    28. Qingwei Wang, 2010. "Sentiment, Convergence of Opinion, and Market Crash," Working Papers 10012, Bangor Business School, Prifysgol Bangor University (Cymru / Wales).
    29. Shynkevich, Andrei, 2012. "Performance of technical analysis in growth and small cap segments of the US equity market," Journal of Banking & Finance, Elsevier, vol. 36(1), pages 193-208.
    30. Shynkevich, Andrei, 2016. "Predictability in bond returns using technical trading rules," Journal of Banking & Finance, Elsevier, vol. 70(C), pages 55-69.
    31. Paskalis Glabadanidis, 2014. "The Market Timing Power of Moving Averages: Evidence from US REITs and REIT Indexes," International Review of Finance, International Review of Finance Ltd., vol. 14(2), pages 161-202, June.
    32. Hubert Dichtl, 2020. "Investing in the S&P 500 index: Can anything beat the buy‐and‐hold strategy?," Review of Financial Economics, John Wiley & Sons, vol. 38(2), pages 352-378, April.
    33. Dushmanta Kumar Padhi & Neelamadhab Padhy & Akash Kumar Bhoi & Jana Shafi & Muhammad Fazal Ijaz, 2021. "A Fusion Framework for Forecasting Financial Market Direction Using Enhanced Ensemble Models and Technical Indicators," Mathematics, MDPI, vol. 9(21), pages 1-31, October.
    34. Dichtl, Hubert & Drobetz, Wolfgang & Neuhierl, Andreas & Wendt, Viktoria-Sophie, 2021. "Data snooping in equity premium prediction," International Journal of Forecasting, Elsevier, vol. 37(1), pages 72-94.
    35. Bekiros, Stelios D., 2013. "Irrational fads, short-term memory emulation, and asset predictability," Review of Financial Economics, Elsevier, vol. 22(4), pages 213-219.
    36. S. D. Bekiros & D. A. Georgoutsos, 2008. "Direction-of-change forecasting using a volatility-based recurrent neural network," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(5), pages 407-417.
    37. Menkhoff, Lukas & Taylor, Mark P., 2006. "The Obstinate Passion of Foreign Exchange Professionals : Technical Analysis," The Warwick Economics Research Paper Series (TWERPS) 769, University of Warwick, Department of Economics.
    38. Isakov, Dusan & Marti, Didier, 2011. "Technical Analysis with a Long-Term Perspective: Trading Strategies and Market Timing Ability," FSES Working Papers 421, Faculty of Economics and Social Sciences, University of Freiburg/Fribourg Switzerland.
    39. Nikolai Dokuchaev, 2015. "Modelling Possibility of Short-Term Forecasting of Market Parameters for Portfolio Selection," Annals of Economics and Finance, Society for AEF, vol. 16(1), pages 143-161, May.
    40. Paskalis Glabadanidis, 2015. "Market Timing With Moving Averages," International Review of Finance, International Review of Finance Ltd., vol. 15(3), pages 387-425, September.
    41. Chen Su & Hanxiong Zhang & Nathan Lael Joseph, 2022. "The performance of UK stock recommendation revisions: Does brokerage house reputation matter?," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(3), pages 3051-3070, July.
    42. Paskalis Glabadanidis, 2017. "Timing the Market with a Combination of Moving Averages," International Review of Finance, International Review of Finance Ltd., vol. 17(3), pages 353-394, September.
    43. 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.
    44. 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.
    45. Psaradellis, Ioannis & Laws, Jason & Pantelous, Athanasios A. & Sermpinis, Georgios, 2023. "Technical analysis, spread trading, and data snooping control," International Journal of Forecasting, Elsevier, vol. 39(1), pages 178-191.
    46. Hsu, Po-Hsuan & Taylor, Mark P. & Wang, Zigan, 2016. "Technical trading: Is it still beating the foreign exchange market?," Journal of International Economics, Elsevier, vol. 102(C), pages 188-208.
    47. Shuenn-Jyi Sheu & Li-Hsien Sun & Zheng Zhang, 2018. "Portfolio Optimization with Delay Factor Models," Papers 1805.01118, arXiv.org.
    48. Hsu, Po-Hsuan & Hsu, Yu-Chin & Kuan, Chung-Ming, 2010. "Testing the predictive ability of technical analysis using a new stepwise test without data snooping bias," Journal of Empirical Finance, Elsevier, vol. 17(3), pages 471-484, June.
    49. Dan Anghel, 2013. "How Reliable is the Moving Average Crossover Rule for an Investor on the Romanian Stock Market?," 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. 5(2), pages 089-115, December.
    50. Nomikos, Nikos K. & Doctor, Kaizad, 2013. "Economic significance of market timing rules in the Forward Freight Agreement markets," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 52(C), pages 77-93.
    51. Qing Zhou & Robert Faff, 2017. "The complementary role of cross-sectional and time-series information in forecasting stock returns," Australian Journal of Management, Australian School of Business, vol. 42(1), pages 113-139, February.
    52. Mihai Cristian Dinică & Erica Cristina (Balea) Dinică, 2015. "Testing the Weak-Form Market Eficiency of the Euronext Wheat," Romanian Economic Journal, Department of International Business and Economics from the Academy of Economic Studies Bucharest, vol. 18(55), pages 25-38, March.
    53. Bekiros, Stelios D., 2010. "Heterogeneous trading strategies with adaptive fuzzy Actor-Critic reinforcement learning: A behavioral approach," Journal of Economic Dynamics and Control, Elsevier, vol. 34(6), pages 1153-1170, June.
    54. Chronopoulos, Dimitris K. & Papadimitriou, Fotios I. & Vlastakis, Nikolaos, 2018. "Information demand and stock return predictability," Journal of International Money and Finance, Elsevier, vol. 80(C), pages 59-74.
    55. Jin, Xiaoye, 2021. "What do we know about the popularity of technical analysis in foreign exchange markets? A skewness preference perspective," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 71(C).
    56. Shynkevich, Andrei, 2013. "Time-series momentum as an intra- and inter-industry effect: Implications for market efficiency," Journal of Economics and Business, Elsevier, vol. 69(C), pages 64-85.
    57. Bertrand B. Maillet & Jean-Philippe R. M�decin, 2010. "Extreme Volatilities, Financial Crises and L-moment Estimations of Tail-indexes," Working Papers 2010_10, Department of Economics, University of Venice "Ca' Foscari".
    58. Ghandar, Adam & Michalewicz, Zbigniew & Zurbruegg, Ralf, 2016. "The relationship between model complexity and forecasting performance for computer intelligence optimization in finance," International Journal of Forecasting, Elsevier, vol. 32(3), pages 598-613.
    59. Dockery, Everton & Todorov, Ivan, 2023. "Further evidence on the returns to technical trading rules: Insights from fourteen currencies," Journal of Multinational Financial Management, Elsevier, vol. 69(C).
    60. Chen, Shi & Bao, Si & Zhou, Yu, 2016. "The predictive power of Japanese candlestick charting in Chinese stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 457(C), pages 148-165.
    61. Bekiros, Stelios D., 2010. "Fuzzy adaptive decision-making for boundedly rational traders in speculative stock markets," European Journal of Operational Research, Elsevier, vol. 202(1), pages 285-293, April.
    62. Yang, Junmin & Cao, Zhiguang & Han, Qiheng & Wang, Qiyu, 2019. "Tactical asset allocation on technical trading rules and data snooping," Pacific-Basin Finance Journal, Elsevier, vol. 57(C).
    63. Martin Scholtus & Dick van Dijk, 2012. "High-Frequency Technical Trading: The Importance of Speed," Tinbergen Institute Discussion Papers 12-018/4, Tinbergen Institute.

  22. Kuan Chung-Ming & Lee Wei-Ming, 2004. "A New Test of the Martingale Difference Hypothesis," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 8(4), pages 1-26, December.
    See citations under working paper version above.
  23. Yi-Ting Chen & Chung-Ming Kuan, 2002. "Time irreversibility and EGARCH effects in US stock index returns," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 17(5), pages 565-578.

    Cited by:

    1. Giacomini, Raffaella & Gottschling, Andreas & Haefke, Christian & White, Halbert, 2007. "Mixtures of t-distributions for Finance and Forecasting," Economics Series 216, Institute for Advanced Studies.
    2. Isao Ishida & Toshiaki Watanabe, 2009. "Modeling and Forecasting the Volatility of the Nikkei 225 Realized Volatility Using the ARFIMA-GARCH Model," CARF F-Series CARF-F-145, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
    3. Evzen Kocenda & Lubos Briatka, 2004. "Advancing the iid Test Based on Integration across the Correlation Integral: Ranges, Competition, and Power," Econometrics 0409001, University Library of Munich, Germany.
    4. Beare, Brendan K. & Seo, Juwon, 2014. "Time Irreversible Copula-Based Markov Models," Econometric Theory, Cambridge University Press, vol. 30(5), pages 923-960, October.
    5. Yi-Ting Chen, 2008. "A unified approach to standardized-residuals-based correlation tests for GARCH-type models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 23(1), pages 111-133.
    6. Esparcia, Carlos & Jareño, Francisco & Umar, Zaghum, 2022. "Revisiting the safe haven role of Gold across time and frequencies during the COVID-19 pandemic," The North American Journal of Economics and Finance, Elsevier, vol. 61(C).
    7. Belaire-Franch, Jorge & Contreras, Dulce, 2003. "Tests for time reversibility: a complementarity analysis," Economics Letters, Elsevier, vol. 81(2), pages 187-195, November.
    8. Hachmi Ben Ameur & Waël Louhichi, 2022. "The Brexit impact on European market co-movements," Annals of Operations Research, Springer, vol. 313(2), pages 1387-1403, June.
    9. Ben Ameur, H. & Prigent, J.L., 2014. "Portfolio insurance: Gap risk under conditional multiples," European Journal of Operational Research, Elsevier, vol. 236(1), pages 238-253.
    10. Kirt C. Butler & Katsushi Okada, 2008. "Higher-Order Terms in Bivariate Returns to International Stock Market Indices," Multinational Finance Journal, Multinational Finance Journal, vol. 12(1-2), pages 127-155, March-Jun.
    11. Ben Ameur, Hachmi & Le Fur, Eric, 2020. "Volatility transmission to the fine wine market," Economic Modelling, Elsevier, vol. 85(C), pages 307-316.
    12. C. W. Granger & E. Maasoumi & J. Racine, 2004. "A Dependence Metric for Possibly Nonlinear Processes," Journal of Time Series Analysis, Wiley Blackwell, vol. 25(5), pages 649-669, September.
    13. Shibin Zhang, 2023. "A copula spectral test for pairwise time reversibility," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 75(5), pages 705-729, October.
    14. Evzen Kocenda & Lubos Briatka, 2005. "Optimal Range for the iid Test Based on Integration Across the Correlation Integral," Econometric Reviews, Taylor & Francis Journals, vol. 24(3), pages 265-296.

  24. Chen, Yi-Ting & Kuan, Chung-Ming, 2002. "The pseudo-true score encompassing test for non-nested hypotheses," Journal of Econometrics, Elsevier, vol. 106(2), pages 271-295, February.
    See citations under working paper version above.
  25. Chih-Chiang Hsu & Chung-Ming Kuan, 2001. "Distinguishing between trend-break models: method and empirical evidence," Econometrics Journal, Royal Economic Society, vol. 4(2), pages 1-1.

    Cited by:

    1. Mohitosh Kejriwal, 2020. "A Robust Sequential Procedure for Estimating the Number of Structural Changes in Persistence," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 82(3), pages 669-685, June.
    2. Mohitosh Kejriwal & Pierre Perron & Xuewen Yu, 2020. "A Two Step Procedure for Testing Partial Parameter Stability in Cointegrated Regression Models," Boston University - Department of Economics - Working Papers Series WP2020-011, Boston University - Department of Economics.
    3. Amélie Charles & Olivier Darné, 2012. "Trends and random walks in macroeconomic time series: A reappraisal," Post-Print hal-00956937, HAL.
    4. Nazif Durmaz & Hyeongwoo Kim & Hyejin Lee & Yanfei Sun, 2023. "Trend Breaks and the Persistence of Closed-End Mutual Fund Discounts," Auburn Economics Working Paper Series auwp2023-03, Department of Economics, Auburn University.
    5. Nazif Durmaz & Hyeongwoo Kim & Hyejin Lee & Yanfei Sun, 2023. "Trend Breaks and the Persistence of Closed-End Fund Discounts," Auburn Economics Working Paper Series auwp2023-08, Department of Economics, Auburn University.
    6. Olivier Darné & Amélie Charles, 2011. "Large shocks in U.S. macroeconomic time series: 1860-1988," Cliometrica, Journal of Historical Economics and Econometric History, Association Française de Cliométrie (AFC), vol. 5(1), pages 79-100, January.
    7. Hsu, Chih-Chiang, 2008. "A note on tests of partial parameter stability in the cointegrated system," Economics Letters, Elsevier, vol. 99(3), pages 500-503, June.

  26. Chen, Yi-Ting & Chou, Ray Y. & Kuan, Chung-Ming, 2000. "Testing time reversibility without moment restrictions," Journal of Econometrics, Elsevier, vol. 95(1), pages 199-218, March.

    Cited by:

    1. Wang, Yuanyuan & Shang, Pengjian, 2018. "A new measurement of financial time irreversibility based on information measures method," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 503(C), pages 221-230.
    2. Yi-Ting Chen & Chung-Ming Kuan, 2002. "Time irreversibility and EGARCH effects in US stock index returns," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 17(5), pages 565-578.
    3. Jorge Belaire-Franch & Dulce Contreras, 2004. "A power comparison among tests for time reversibility," Economics Bulletin, AccessEcon, vol. 3(23), pages 1-17.
    4. Steven Cook & Alan Speight, 2006. "International Business Cycle Asymmetry and Time Irreversible Nonlinearities," Journal of Applied Statistics, Taylor & Francis Journals, vol. 33(10), pages 1051-1065.
    5. Isao Ishida & Toshiaki Watanabe, 2009. "Modeling and Forecasting the Volatility of the Nikkei 225 Realized Volatility Using the ARFIMA-GARCH Model," CARF F-Series CARF-F-145, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
    6. Leucht, Anne, 2012. "Characteristic function-based hypothesis tests under weak dependence," Journal of Multivariate Analysis, Elsevier, vol. 108(C), pages 67-89.
    7. Beare, Brendan K. & Seo, Juwon, 2014. "Time Irreversible Copula-Based Markov Models," Econometric Theory, Cambridge University Press, vol. 30(5), pages 923-960, October.
    8. Ippei Fujiwara & Lena Mareen Korber & Daisuke Nagakura, 2011. "How much asymmetry is there in bond returns and exchange rates?," Globalization Institute Working Papers 93, Federal Reserve Bank of Dallas.
    9. Yi-Ting Chen, 2008. "A unified approach to standardized-residuals-based correlation tests for GARCH-type models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 23(1), pages 111-133.
    10. Kuan Chung-Ming & Lee Wei-Ming, 2004. "A New Test of the Martingale Difference Hypothesis," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 8(4), pages 1-26, December.
    11. Belaire-Franch Jorge & Contreras Dulce, 2010. "Testing the Martingale Property of Exchange Rates: A Replication," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 15(1), pages 1-19, December.
    12. Steven Cook & Alan Speight, 2007. "Time Irreversibility in Consumers' Expenditure: An Analysis of Disaggregated Data," International Review of Applied Economics, Taylor & Francis Journals, vol. 21(4), pages 561-575.
    13. Francesco Giancaterini & Alain Hecq & Claudio Morana, 2022. "Is climate change time reversible?," Working Paper series 22-08, Rimini Centre for Economic Analysis, revised Dec 2022.
    14. Zargar, Faisal Nazir & Kumar, Dilip, 2019. "Informational inefficiency of Bitcoin: A study based on high-frequency data," Research in International Business and Finance, Elsevier, vol. 47(C), pages 344-353.
    15. Belaire-Franch, Jorge & Contreras, Dulce, 2003. "Tests for time reversibility: a complementarity analysis," Economics Letters, Elsevier, vol. 81(2), pages 187-195, November.
    16. Zacharias Psaradakis & Marián Vávra, 2015. "A Quantile-based Test for Symmetry of Weakly Dependent Processes," Journal of Time Series Analysis, Wiley Blackwell, vol. 36(4), pages 587-598, July.
    17. Zacharias Psaradakis, 2008. "Assessing Time‐Reversibility Under Minimal Assumptions," Journal of Time Series Analysis, Wiley Blackwell, vol. 29(5), pages 881-905, September.
    18. Chen Yi-Ting & Lin Chang-Ching, 2008. "On the Robustness of Symmetry Tests for Stock Returns," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 12(2), pages 1-40, May.
    19. Sebastian Schweer & Christian H. Weiß, 2016. "Testing for Poisson arrivals in INAR(1) processes," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 25(3), pages 503-524, September.
    20. Wu, Zhenyu & Shang, Pengjian & Xiong, Hui, 2018. "An improvement of the measurement of time series irreversibility with visibility graph approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 502(C), pages 370-378.
    21. Chen Yi-Ting, 2003. "Testing Serial Independence against Time Irreversibility," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 7(3), pages 1-30, October.
    22. Zacharias Psaradakis & Marian Vavra, 2018. "Bootstrap Assisted Tests of Symmetry for Dependent Data," Working and Discussion Papers WP 5/2018, Research Department, National Bank of Slovakia.
    23. Yuichi Goto & Tobias Kley & Ria Van Hecke & Stanislav Volgushev & Holger Dette & Marc Hallin, 2021. "The Integrated Copula Spectrum," Working Papers ECARES 2021-29, ULB -- Universite Libre de Bruxelles.
    24. Phillip Wild & John Foster, 2012. "On testing for non-linear and time irreversible probabilistic structure in high frequency ASX financial time series data," Discussion Papers Series 466, School of Economics, University of Queensland, Australia.
    25. McCAUSLAND, William J., 2004. "Time Reversibility of Stationary Regular Finite State Markov Chains," Cahiers de recherche 09-2004, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
    26. Zacharias Psaradakis & Marian Vavra, 2020. "On Using Triples to Assess Symmetry Under Weak Dependence," Working and Discussion Papers WP 7/2020, Research Department, National Bank of Slovakia.
    27. Andrea Bastianin, 2020. "Robust measures of skewness and kurtosis for macroeconomic and financial time series," Applied Economics, Taylor & Francis Journals, vol. 52(7), pages 637-670, February.
    28. 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.
    29. Fernandez, Viviana, 2009. "The behavior of stock returns in the mining industry following the Iraq war," Research in International Business and Finance, Elsevier, vol. 23(3), pages 274-292, September.
    30. Amit Shelef & Edna Schechtman, 2019. "A Gini-based time series analysis and test for reversibility," Statistical Papers, Springer, vol. 60(3), pages 687-716, June.
    31. Qi Li & Jeffrey Scott Racine, 2006. "Nonparametric Econometrics: Theory and Practice," Economics Books, Princeton University Press, edition 1, volume 1, number 8355.
    32. Chen, Yi-Ting, 2012. "A simple approach to standardized-residuals-based higher-moment tests," Journal of Empirical Finance, Elsevier, vol. 19(4), pages 427-453.
    33. Fong, Wai Mun, 2003. "Time reversibility tests of volume-volatility dynamics for stock returns," Economics Letters, Elsevier, vol. 81(1), pages 39-45, October.
    34. Gilles Zumbach, 2007. "Time reversal invariance in finance," Papers 0708.4022, arXiv.org.
    35. Tommaso Proietti, 2020. "Peaks, Gaps, and Time Reversibility of Economic Time Series," CEIS Research Paper 492, Tor Vergata University, CEIS, revised 17 Jun 2020.
    36. Zacharias Psaradakis & Martin Sola, 2003. "On detrending and cyclical asymmetry," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(3), pages 271-289.
    37. Park, Sung Y. & Bera, Anil K., 2009. "Maximum entropy autoregressive conditional heteroskedasticity model," Journal of Econometrics, Elsevier, vol. 150(2), pages 219-230, June.
    38. Rothman Philip, 2016. "Introduction to Studies in Nonlinear Dynamics & Econometrics Issue in Honor of James B. Ramsey," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 20(4), pages 343-346, September.
    39. Jessica Morales Herrera & Ra'ul Salgado-Garc'ia, 2023. "Trend patterns statistics for assessing irreversibility in cryptocurrencies: time-asymmetry versus inefficiency," Papers 2307.08612, arXiv.org.
    40. Shibin Zhang, 2023. "A copula spectral test for pairwise time reversibility," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 75(5), pages 705-729, October.
    41. Li, Jinyang & Shang, Pengjian, 2018. "Time irreversibility of financial time series based on higher moments and multiscale Kullback–Leibler divergence," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 502(C), pages 248-255.

  27. Leisch, Friedrich & Hornik, Kurt & Kuan, Chung-Ming, 2000. "Monitoring Structural Changes With The Generalized Fluctuation Test," Econometric Theory, Cambridge University Press, vol. 16(6), pages 835-854, December.

    Cited by:

    1. William Kengne & Isidore S. Ngongo, 2022. "Inference for nonstationary time series of counts with application to change-point problems," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 74(4), pages 801-835, August.
    2. Mengrui Zhu & Hua Xu & Xingyu Gao & Minggang Wang & André L. M. Vilela & Lixin Tian, 2022. "Identification of Breakpoints in Carbon Market Based on Probability Density Recurrence Network," Energies, MDPI, vol. 15(15), pages 1-18, July.
    3. David I. Harvey & Stephen J. Leybourne & A. M. Robert Taylor, 2010. "Robust methods for detecting multiple level breaks in autocorrelated time series," Discussion Papers 10/01, University of Nottingham, Granger Centre for Time Series Econometrics.
    4. Christis Katsouris, 2023. "Break-Point Date Estimation for Nonstationary Autoregressive and Predictive Regression Models," Papers 2308.13915, arXiv.org.
    5. Jana Eklund & George Kapetanios & Simon Price, 2013. "Robust Forecast Methods and Monitoring during Structural Change," Manchester School, University of Manchester, vol. 81, pages 3-27, October.
    6. Šárka Hudecová & Marie Hušková & Simos G. Meintanis, 2017. "Tests for Structural Changes in Time Series of Counts," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 44(4), pages 843-865, December.
    7. Bernales, Alejandro & Chen, Louisa & Valenzuela, Marcela, 2017. "Learning and forecasts about option returns through the volatility risk premium," Journal of Economic Dynamics and Control, Elsevier, vol. 82(C), pages 312-330.
    8. Bardet, Jean-Marc & Kengne, William, 2014. "Monitoring procedure for parameter change in causal time series," Journal of Multivariate Analysis, Elsevier, vol. 125(C), pages 204-221.
    9. Lee, Sangyeol & Park, Siyun, 2009. "The monitoring test for the stability of regression models with nonstationary regressors," Economics Letters, Elsevier, vol. 105(3), pages 250-252, December.
    10. Mikkel Bennedsen, 2020. "Designing a sequential testing procedure for verifying global CO2 emissions," CREATES Research Papers 2020-01, Department of Economics and Business Economics, Aarhus University.
    11. Andreou, Elena & Ghysels, Eric, 2006. "Monitoring disruptions in financial markets," Journal of Econometrics, Elsevier, vol. 135(1-2), pages 77-124.
    12. Tatsuru Kikuchi & Toranosuke Onishi & Kenichi Ueda, 2021. "Price Stability of Cryptocurrencies as a Medium of Exchange," Papers 2111.08390, arXiv.org.
    13. Eklund, J. & Kapetanios, G. & Price, S., 2011. "Forecasting in the presence of recent structural change," Working Papers 11/05, Department of Economics, City University London.
    14. Achim Zeileis & Friedrich Leisch & Christian Kleiber & Kurt Hornik, 2005. "Monitoring structural change in dynamic econometric models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(1), pages 99-121, January.
    15. Yudong Chen & Tengyao Wang & Richard J. Samworth, 2022. "High‐dimensional, multiscale online changepoint detection," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 84(1), pages 234-266, February.
    16. Pouliot, William, 2016. "Robust tests for change in intercept and slope in linear regression models with application to manager performance in the mutual fund industry," Economic Modelling, Elsevier, vol. 58(C), pages 523-534.
    17. Julien Chevallier, 2011. "Detecting Instability in the Volatility of Carbon Prices," Post-Print hal-00991957, HAL.
    18. Alexander Aue & Lajos Horváth & Piotr Kokoszka & Josef Steinebach, 2008. "Monitoring shifts in mean: Asymptotic normality of stopping times," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 17(3), pages 515-530, November.
    19. Czinkota, Thomas, 2012. "Das Halteproblem bei Strukturbrüchen in Finanzmarktzeitreihen [The Halting Problem applied to Structural Breaks in Financial Time Series]," MPRA Paper 37072, University Library of Munich, Germany.
    20. Hsu, Chih-Chiang, 2007. "The MOSUM of squares test for monitoring variance changes," Finance Research Letters, Elsevier, vol. 4(4), pages 254-260, December.
    21. Abhijit Sharma & Kelvin G Balcombe & Iain M Fraser, 2009. "Non-renewable resource prices: Structural breaks and long term trends," Economics Bulletin, AccessEcon, vol. 29(2), pages 805-819.
    22. Otto, Sven & Breitung, Jörg, 2020. "Backward CUSUM for Testing and Monitoring Structural Change," VfS Annual Conference 2020 (Virtual Conference): Gender Economics 224533, Verein für Socialpolitik / German Economic Association.
    23. KUROZUMI, Eiji & 黒住, 英司, 2016. "Monitoring Parameter Constancy with Endogenous Regressors," Discussion Papers 2016-01, Graduate School of Economics, Hitotsubashi University.
    24. Stanislav Anatolyev, 2006. "Nonparametric retrospection and monitoring of predictability of financial returns," Working Papers w0071, New Economic School (NES).
    25. Aue, Alexander & Horváth, Lajos & Reimherr, Matthew L., 2009. "Delay times of sequential procedures for multiple time series regression models," Journal of Econometrics, Elsevier, vol. 149(2), pages 174-190, April.
    26. Elena Andreou & Eric Ghysels, 2007. "Quality Control for Structural Credit Risk Models," University of Cyprus Working Papers in Economics 3-2007, University of Cyprus Department of Economics.
    27. Jan Verbesselt & Achim Zeileis & Martin Herold, 2011. "Near Real-Time Disturbance Detection in Terrestrial Ecosystems Using Satellite Image Time Series: Drought Detection in Somalia," Working Papers 2011-18, Faculty of Economics and Statistics, Universität Innsbruck.
    28. Bock, David, 2007. "Consequences of using the probability of a false alarm as the false alarm measure," Research Reports 2007:3, University of Gothenburg, Statistical Research Unit, School of Business, Economics and Law.
    29. Gabriela Ciuperca, 2022. "Real-time detection of a change-point in a linear expectile model," Statistical Papers, Springer, vol. 63(4), pages 1323-1367, August.
    30. Christis Katsouris, 2023. "Structural Break Detection in Quantile Predictive Regression Models with Persistent Covariates," Papers 2302.05193, arXiv.org.
    31. Choi, Hanbok & Eom, Young Ho & Jang, Woon Wook & Kim, Don H., 2017. "Covered interest parity deviation and counterparty default risk: U.S. Dollar/Korean Won FX swap market," Pacific-Basin Finance Journal, Elsevier, vol. 44(C), pages 47-63.
    32. Olmo Jose & Pouliot William, 2011. "Early Detection Techniques for Market Risk Failure," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 15(4), pages 1-55, September.
    33. Chen, Yudong & Wang, Tengyao & Samworth, Richard J., 2022. "High-dimensional, multiscale online changepoint detection," LSE Research Online Documents on Economics 113665, London School of Economics and Political Science, LSE Library.
    34. Jan J.J. Groen & George Kapetanios & Simon Price, 2010. "Multivariate Methods for Monitoring Structural Change," Working Papers 658, Queen Mary University of London, School of Economics and Finance.
    35. Skrobotov, Anton, 2020. "Survey on structural breaks and unit root tests," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 58, pages 96-141.
    36. Mamadou Lamine Diop & William Kengne, 2022. "Poisson QMLE for change-point detection in general integer-valued time series models," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 85(3), pages 373-403, April.
    37. Stanislav Anatolyev & Grigory Kosenok, 2011. "Sequential Testing with Uniformly Distributed Size," Working Papers w0123, New Economic School (NES).
    38. Sven Otto & Jorg Breitung, 2020. "Backward CUSUM for Testing and Monitoring Structural Change with an Application to COVID-19 Pandemic Data," Papers 2003.02682, arXiv.org, revised Mar 2022.
    39. Carsten J. Crede, 2019. "A Structural Break Cartel Screen for Dating and Detecting Collusion," Review of Industrial Organization, Springer;The Industrial Organization Society, vol. 54(3), pages 543-574, May.
    40. Josua Gösmann & Tobias Kley & Holger Dette, 2021. "A new approach for open‐end sequential change point monitoring," Journal of Time Series Analysis, Wiley Blackwell, vol. 42(1), pages 63-84, January.
    41. Carsten J. Crede, 2015. "A structural break cartel screen for dating and detecting collusion," Working Paper series, University of East Anglia, Centre for Competition Policy (CCP) 2015-11, Centre for Competition Policy, University of East Anglia, Norwich, UK..
    42. Bernales, Alejandro & Guidolin, Massimo, 2015. "Learning to smile: Can rational learning explain predictable dynamics in the implied volatility surface?," Journal of Financial Markets, Elsevier, vol. 26(C), pages 1-37.
    43. David I. Harvey & Stephen J. Leybourne & A. M. Robert Taylor, 2009. "Robust methods for detecting multiple level breaks in autocorrelated time series [Revised to become No. 10/01 above]," Discussion Papers 09/01, University of Nottingham, Granger Centre for Time Series Econometrics.
    44. Okyoung Na & Youngmi Lee & Sangyeol Lee, 2011. "Monitoring parameter change in time series models," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 20(2), pages 171-199, June.
    45. Haitham A. Al-Zoubi & Aktham Maghyereh, 2007. "Stationary Component in Stock Prices: A Reappraisal of Empirical Findings," Multinational Finance Journal, Multinational Finance Journal, vol. 11(3-4), pages 287-322, September.
    46. Heinen, Florian & Willert, Juliane, 2011. "Monitoring a change in persistence of a long range dependent time series," Hannover Economic Papers (HEP) dp-479, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
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    1. A. M. Robert Taylor, 2005. "Fluctuation Tests for a Change in Persistence," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 67(2), pages 207-230, April.
    2. Pollock, D. S. G., 2003. "Recursive estimation in econometrics," Computational Statistics & Data Analysis, Elsevier, vol. 44(1-2), pages 37-75, October.
    3. Kuan, Chung-Ming, 1999. "A note on tests for partial parameter instability in the trend stationary model," Economics Letters, Elsevier, vol. 65(3), pages 285-291, December.
    4. Paulo M.M. Rodrigues & Matei Demetrescu, 2019. "Testing for Episodic Predictability in Stock Returns," Working Papers w201906, Banco de Portugal, Economics and Research Department.
    5. Juhl, Ted & Xiao, Zhijie, 2005. "A nonparametric test for changing trends," Journal of Econometrics, Elsevier, vol. 127(2), pages 179-199, August.
    6. Erhua Zhang & Xiaojun Song & Jilin Wu, 2022. "A non‐parametric test for multi‐variate trend functions," Journal of Time Series Analysis, Wiley Blackwell, vol. 43(6), pages 856-871, November.
    7. Lajos Horváth & Gregory Rice, 2014. "Extensions of some classical methods in change point analysis," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 23(2), pages 219-255, June.

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    1. Thomas Barnay & Olivier Damette, 2012. "What drives Health Care Expenditure in France since 1950?," Working Papers hal-00717435, HAL.
    2. Prakash Singh & Manoj K. Pandey, 2009. "Structural Break, Stability and Demand for Money in India," ASARC Working Papers 2009-07, The Australian National University, Australia South Asia Research Centre.
    3. Pan, Guochen & Chang, Hsu-Ling & Su, Chi-Wei, 2012. "Regional differences in development of life insurance markets in China," Emerging Markets Review, Elsevier, vol. 13(4), pages 548-558.
    4. Jewell, Todd & Lee, Junsoo & Tieslau, Margie & Strazicich, Mark C., 2003. "Stationarity of health expenditures and GDP: evidence from panel unit root tests with heterogeneous structural breaks," Journal of Health Economics, Elsevier, vol. 22(2), pages 313-323, March.
    5. Brittle, Shane, 2009. "Ricardian Equivalence and the Efficacy of Fiscal Policy in Australia," Economics Working Papers wp09-10, School of Economics, University of Wollongong, NSW, Australia.
    6. Junsoo Lee & John A. List & Mark Strazicich, 2005. "Nonrenewable Resource Prices: Deterministic or Stochastic Trends?," NBER Working Papers 11487, National Bureau of Economic Research, Inc.
    7. Mohsen Bahmani-Oskooee & Tsangyao Chang & Kuei-Chiu Lee, 2014. "Purchasing Power Parity in the BRICS and the MIST Countries: Sequential Panel Selection Method," Review of Economics & Finance, Better Advances Press, Canada, vol. 4, pages 1-12, Feburary.
    8. Rishika Nayyar & Jaydeep Mukherjee, 2018. "Outward FDI from India: A macro level examination in the presence of structural breaks," Working Papers 1833, Indian Institute of Foreign Trade.
    9. Chi-Wei Su & Yu-Shao Liu & Meng-Nan Zhu & Kuei-Chiu Lee, 2012. "Purchasing power parity in major OPEC countries: flexible Fourier stationary test," Applied Economics Letters, Taylor & Francis Journals, vol. 19(1), pages 19-24, January.
    10. Payne, James & Lee, Junsoo & Hofler, Richard, 2005. "Purchasing power parity: Evidence from a transition economy," Journal of Policy Modeling, Elsevier, vol. 27(6), pages 665-672, September.
    11. Vasco De & A. Gabriel & Artur C. B. Da Silva Lopes & Luis Nunes, 2003. "Instability in cointegration regressions: a brief review with an application to money demand in Portugal," Applied Economics, Taylor & Francis Journals, vol. 35(8), pages 893-900.
    12. Chakraborty, Debashis & Mukherjee, Jaydeep & Lee, Jaewook, 2016. "Do FDI Inflows influence Merchandise Exports? Causality Analysis on India over 1991-2016," MPRA Paper 74851, University Library of Munich, Germany.
    13. Ranajoy Bhattacharyya & Jaydeep Mukherjee, 2014. "Do Exchange Rates Affect Exports in India?," South Asian Journal of Macroeconomics and Public Finance, , vol. 3(2), pages 175-193, December.
    14. Paresh Kumar Narayan, 2005. "New evidence on purchasing power parity from 17 OECD countries," Applied Economics, Taylor & Francis Journals, vol. 37(9), pages 1063-1071.
    15. Amélie Charles & Olivier Darné, 2012. "Trends and random walks in macroeconomic time series: A reappraisal," Post-Print hal-00956937, HAL.
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    17. Fantazzini, Dean & Toktamysova, Zhamal, 2015. "Forecasting German Car Sales Using Google Data and Multivariate Models," MPRA Paper 67110, University Library of Munich, Germany.
    18. Popp, Stephan, 2007. "Identification of the true break date in innovational outlier unit root tests," IBES Diskussionsbeiträge 152, University of Duisburg-Essen, Institute of Business and Economic Studie (IBES).
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    23. Chakraborty Debashis & Mukherjee Jaydeep & Lee Jaewook, 2017. "FDI Inflows Influence Merchandise Exports? Causality Analysis for India over 1991-2016 : Causality Analysis for India Over 1991–2016," Global Economy Journal, De Gruyter, vol. 17(3), pages 1-10, September.
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    55. Erwin Bulte & John A. List & Mark C. Strazicich, 2004. "Regulatory Federalism and the Distribution of Air Pollutant Emissions," Working Papers 04-16, Department of Economics, Appalachian State University.
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    Cited by:

    1. Wang, Dabin & Tomek, William G., 2004. "Commodity Prices And Unit Root Tests," 2004 Annual meeting, August 1-4, Denver, CO 20141, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    2. Todd E. Clark, 2003. "Disaggregate evidence on the persistence of consumer price inflation," Research Working Paper RWP 03-11, Federal Reserve Bank of Kansas City.
    3. Hyung, Namwon & Franses, Philip Hans & Penm, Jack, 2006. "Structural breaks and long memory in US inflation rates: Do they matter for forecasting?," Research in International Business and Finance, Elsevier, vol. 20(1), pages 95-110, March.
    4. Magnus Gustavsson & Pär Österholm, 2007. "Does Unemployment Hysteresis Equal Employment Hysteresis?," The Economic Record, The Economic Society of Australia, vol. 83(261), pages 159-173, June.
    5. Rasmus Tangsgaard Varneskov & Pierre Perron, 2011. "Combining Long Memory and Level Shifts in Modeling and Forecasting the Volatility of Asset Returns," CREATES Research Papers 2011-26, Department of Economics and Business Economics, Aarhus University.
    6. Ibrahim Ahamada & Jamel Jouini & Mohamed Boutahar, 2004. "Detecting Multiple Breaks in Time Series Covariance Structure: a Nonparametric Approach Based on the Evolutionary Spectral Density," Post-Print halshs-00272867, HAL.
    7. Altissimo, Filippo & Corradi, Valentina, 2003. "Strong rules for detecting the number of breaks in a time series," Journal of Econometrics, Elsevier, vol. 117(2), pages 207-244, December.
    8. Ibrahim Ahamada & Jamel Jouini & Mohamed Boutahar, 2004. "Detecting Multiple Breaks in Time Series Covariance Structure: a Nonparametric Approach Based on the Evolutionary Spectral Density," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-00272867, HAL.
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    4. Laura Mayoral, 2005. "The persistence of inflation in OECD countries: A fractionally integrated approach," Economics Working Papers 958, Department of Economics and Business, Universitat Pompeu Fabra, revised Oct 2005.
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    6. Rodríguez, Gabriel, 2017. "Modeling Latin-American stock and Forex markets volatility: Empirical application of a model with random level shifts and genuine long memory," The North American Journal of Economics and Finance, Elsevier, vol. 42(C), pages 393-420.
    7. Kim, Dukpa & Perron, Pierre, 2009. "Unit root tests allowing for a break in the trend function at an unknown time under both the null and alternative hypotheses," Journal of Econometrics, Elsevier, vol. 148(1), pages 1-13, January.
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    9. Jin, Hao & Tian, Zheng & Qin, Ruibing, 2009. "Bootstrap tests for structural change with infinite variance observations," Statistics & Probability Letters, Elsevier, vol. 79(19), pages 1985-1995, October.
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    3. David E. Allen & Michael McAleer & Shelton Peiris & Abhay K. Singh, 2015. "Nonlinear Time Series and Neural-Network Models of Exchange Rates between the US Dollar and Major Currencies," Tinbergen Institute Discussion Papers 15-125/III, Tinbergen Institute.
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    95. Panda, Chakradhara & Narasimhan, V., 2007. "Forecasting exchange rate better with artificial neural network," Journal of Policy Modeling, Elsevier, vol. 29(2), pages 227-236.
    96. Zhang, Guoqiang & Eddy Patuwo, B. & Y. Hu, Michael, 1998. "Forecasting with artificial neural networks:: The state of the art," International Journal of Forecasting, Elsevier, vol. 14(1), pages 35-62, March.
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    98. Longhi, Simonetta & Nijkamp, Peter & Reggiani, Aura & Blien, Uwe, 2002. "Forecasting regional labour markets in Germany: an evaluation of the performance of neural network analysis," ERSA conference papers ersa02p117, European Regional Science Association.
    99. Panagiotis Papaioannou & Lucia Russo & George Papaioannou & Constantinos Siettos, 2013. "Can social microblogging be used to forecast intraday exchange rates?," Netnomics, Springer, vol. 14(1), pages 47-68, November.

  33. Chu, Chia-Shang James & Hornik, Kurt & Kuan, Chung-Ming, 1995. "The Moving-Estimates Test for Parameter Stability," Econometric Theory, Cambridge University Press, vol. 11(4), pages 699-720, August.

    Cited by:

    1. Achim Zeileis, 2005. "A Unified Approach to Structural Change Tests Based on ML Scores, F Statistics, and OLS Residuals," Econometric Reviews, Taylor & Francis Journals, vol. 24(4), pages 445-466.
    2. Liu, Guan-Chun & Lee, Chien-Chiang & Lee, Chi-Chuan, 2016. "The nexus between insurance activity and economic growth: A bootstrap rolling window approach," International Review of Economics & Finance, Elsevier, vol. 43(C), pages 299-319.
    3. Luis Fernando Melo & Martha Misas A., 2004. "Modelos Estructurales de Inflación en Colombia: Estimación a Través de Mínimos Cuadrados Flexibles," Borradores de Economia 283, Banco de la Republica de Colombia.
    4. Raphael Markellos & Terence Mills, 2003. "Asset pricing dynamics," The European Journal of Finance, Taylor & Francis Journals, vol. 9(6), pages 533-556.
    5. Davide De Gaetano, 2016. "Forecast Combinations For Realized Volatility In Presence Of Structural Breaks," Departmental Working Papers of Economics - University 'Roma Tre' 0208, Department of Economics - University Roma Tre.
    6. Cho, Jin Seo & White, Halbert, 2011. "Generalized runs tests for the IID hypothesis," Journal of Econometrics, Elsevier, vol. 162(2), pages 326-344, June.
    7. Davide De Gaetano, 2018. "Forecast Combinations in the Presence of Structural Breaks: Evidence from U.S. Equity Markets," Mathematics, MDPI, vol. 6(3), pages 1-19, March.
    8. Christis Katsouris, 2023. "Predictability Tests Robust against Parameter Instability," Papers 2307.15151, arXiv.org.
    9. Mehmet Balcilar & Rangan Gupta & Stephen M. Miller, 2013. "Housing and the Great Depression," Working Papers 201308, University of Pretoria, Department of Economics.
    10. Achim Zeileis & Friedrich Leisch & Christian Kleiber & Kurt Hornik, 2005. "Monitoring structural change in dynamic econometric models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(1), pages 99-121, January.
    11. Altissimo, Filippo & Corradi, Valentina, 2003. "Strong rules for detecting the number of breaks in a time series," Journal of Econometrics, Elsevier, vol. 117(2), pages 207-244, December.
    12. Luis Fernando Melo Velandia & Martha Alicia Misas Arango, 2004. "Modelos Estructurales de Inflación en Colombia: Estimación a través de Mínimos Cuadrados Flexibles," Borradores de Economia 3244, Banco de la Republica.
    13. Liu, Guanchun & He, Lei & Yue, Yiding & Wang, Jiying, 2014. "The linkage between insurance activity and banking credit: Some evidence from dynamic analysis," The North American Journal of Economics and Finance, Elsevier, vol. 29(C), pages 239-265.
    14. Chung-Ming Kuan & Mai-Yuan Chen, 2002. "Response surfaces of MOSUM critical values," Applied Economics Letters, Taylor & Francis Journals, vol. 9(2), pages 133-136.
    15. Fan, Ying & Xu, Jin-Hua, 2011. "What has driven oil prices since 2000? A structural change perspective," Energy Economics, Elsevier, vol. 33(6), pages 1082-1094.
    16. Juergen Amann & Paul Middleditch, 2017. "Growth in a time of austerity: evidence from the UK," Scottish Journal of Political Economy, Scottish Economic Society, vol. 64(4), pages 349-375, September.
    17. Pollock, D. S. G., 2003. "Recursive estimation in econometrics," Computational Statistics & Data Analysis, Elsevier, vol. 44(1-2), pages 37-75, October.
    18. Stanislav Anatolyev, 2006. "Nonparametric retrospection and monitoring of predictability of financial returns," Working Papers w0071, New Economic School (NES).
    19. Aue, Alexander & Horváth, Lajos & Reimherr, Matthew L., 2009. "Delay times of sequential procedures for multiple time series regression models," Journal of Econometrics, Elsevier, vol. 149(2), pages 174-190, April.
    20. Zeileis, Achim & Leisch, Friedrich & Hornik, Kurt & Kleiber, Christian, 2002. "strucchange: An R Package for Testing for Structural Change in Linear Regression Models," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 7(i02).
    21. S. Avouyi-Dovi & G. Horny & P. Sevestre, 2015. "The stability of short-term interest rates pass-through in the euro area during the financial market and sovereign debt crises," Working papers 547, Banque de France.
    22. Raffella Giacomini & Barbara Rossi, 2005. "Detecting and Predicting Forecast Breakdowns," UCLA Economics Working Papers 845, UCLA Department of Economics.
    23. Stanislav Anatolyev & Grigory Kosenok, 2011. "Sequential Testing with Uniformly Distributed Size," Working Papers w0123, New Economic School (NES).
    24. Carsten J. Crede, 2019. "A Structural Break Cartel Screen for Dating and Detecting Collusion," Review of Industrial Organization, Springer;The Industrial Organization Society, vol. 54(3), pages 543-574, May.
    25. Carsten J. Crede, 2015. "A structural break cartel screen for dating and detecting collusion," Working Paper series, University of East Anglia, Centre for Competition Policy (CCP) 2015-11, Centre for Competition Policy, University of East Anglia, Norwich, UK..
    26. Zeileis, Achim & Kleiber, Christian & Krämer, Walter & Hornik, Kurt, 2002. "Testing and dating of structural changes in practice," Technical Reports 2002,39, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    27. Marques, André M. & Carvalho, André R., 2022. "Testing the neo-fisherian hypothesis in Brazil," The Quarterly Review of Economics and Finance, Elsevier, vol. 86(C), pages 407-419.
    28. Chen, Gongmeng & Choi, Yoon K. & Zhou, Yong, 2005. "Nonparametric estimation of structural change points in volatility models for time series," Journal of Econometrics, Elsevier, vol. 126(1), pages 79-114, May.
    29. Na, Okyoung & Lee, Sangyeol, 2007. "Moving estimates test with time varying bandwidth," Journal of Multivariate Analysis, Elsevier, vol. 98(7), pages 1356-1375, August.
    30. Kuan, Chung-Ming, 1998. "Tests for changes in models with a polynomial trend," Journal of Econometrics, Elsevier, vol. 84(1), pages 75-91, May.
    31. Haitham A. Al-Zoubi & Aktham Maghyereh, 2007. "Stationary Component in Stock Prices: A Reappraisal of Empirical Findings," Multinational Finance Journal, Multinational Finance Journal, vol. 11(3-4), pages 287-322, September.
    32. Christis Katsouris, 2022. "Partial Sum Processes of Residual-Based and Wald-type Break-Point Statistics in Time Series Regression Models," Papers 2202.00141, arXiv.org, revised Feb 2022.

  34. Kuan, Chung-Ming & Chen, Mei-Yuan, 1994. "Implementing the fluctuation and moving-estimates tests in dynamic econometric models," Economics Letters, Elsevier, vol. 44(3), pages 235-239.

    Cited by:

    1. Mehmet Balcilar & Rangan Gupta & Stephen M. Miller, 2013. "Housing and the Great Depression," Working Papers 201308, University of Pretoria, Department of Economics.
    2. Achim Zeileis & Friedrich Leisch & Christian Kleiber & Kurt Hornik, 2005. "Monitoring structural change in dynamic econometric models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(1), pages 99-121, January.
    3. Stanislav Anatolyev, 2006. "Nonparametric retrospection and monitoring of predictability of financial returns," Working Papers w0071, New Economic School (NES).
    4. Zeileis, Achim & Leisch, Friedrich & Hornik, Kurt & Kleiber, Christian, 2002. "strucchange: An R Package for Testing for Structural Change in Linear Regression Models," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 7(i02).
    5. Christis Katsouris, 2023. "Structural Break Detection in Quantile Predictive Regression Models with Persistent Covariates," Papers 2302.05193, arXiv.org.
    6. Christis Katsouris, 2022. "Partial Sum Processes of Residual-Based and Wald-type Break-Point Statistics in Time Series Regression Models," Papers 2202.00141, arXiv.org, revised Feb 2022.

  35. Kuan, Chung-Ming & White, Halbert, 1994. "Adaptive Learning with Nonlinear Dynamics Driven by Dependent Processes," Econometrica, Econometric Society, vol. 62(5), pages 1087-1114, September.

    Cited by:

    1. Atanas Christev, 2007. "Learning Hyperinflations," Money Macro and Finance (MMF) Research Group Conference 2006 126, Money Macro and Finance Research Group.
    2. Barucci, Emilio & Landi, Leonardo, 1996. "Speculative dynamics with bounded rationality learning," European Journal of Operational Research, Elsevier, vol. 91(2), pages 284-300, June.
    3. Heinemann, Maik, 2000. "Adaptive learning of rational expectations using neural networks," Journal of Economic Dynamics and Control, Elsevier, vol. 24(5-7), pages 1007-1026, June.
    4. Chen, Xiaohong & White, Halbert, 1998. "Nonparametric Adaptive Learning with Feedback," Journal of Economic Theory, Elsevier, vol. 82(1), pages 190-222, September.
    5. Christis Katsouris, 2023. "Quantile Time Series Regression Models Revisited," Papers 2308.06617, arXiv.org, revised Aug 2023.
    6. Ulrich Horst & Jan Wezelburger, 2006. "Non-ergodic Behavior in a Financial Market with Interacting Investors," 2006 Meeting Papers 229, Society for Economic Dynamics.
    7. Guidolin, Massimo & Timmermann, Allan, 2007. "Properties of equilibrium asset prices under alternative learning schemes," Journal of Economic Dynamics and Control, Elsevier, vol. 31(1), pages 161-217, January.
    8. Peter Woehrmann & Willi Semmler & Martin Lettau, "undated". "Nonparametric Estimation of the Time-varying Sharpe Ratio in Dynamic Asset Pricing Models," IEW - Working Papers 225, Institute for Empirical Research in Economics - University of Zurich.
    9. Evans, George W. & Honkapohja, S., 1998. "Stochastic gradient learning in the cobweb model," Economics Letters, Elsevier, vol. 61(3), pages 333-337, December.
    10. Evans, George W. & Honkapohja, Seppo, 1998. "Convergence of learning algorithms without a projection facility," Journal of Mathematical Economics, Elsevier, vol. 30(1), pages 59-86, August.
    11. Chen Xiaohong & White Halbert, 2002. "Asymptotic Properties of Some Projection-based Robbins-Monro Procedures in a Hilbert Space," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 6(1), pages 1-55, April.
    12. Sergio Pastorello & Valentin Patilea & Eric Renault, 2003. "Iterative and Recursive Estimation in Structural Non-Adaptive Models," CIRANO Working Papers 2003s-08, CIRANO.
    13. Alan Beggs, 2002. "On the Convergence of Reinforcement Learning," Economics Series Working Papers 96, University of Oxford, Department of Economics.
    14. Gregoir, Stephane & Weill, Pierre-Olivier, 2007. "Restricted perception equilibria and rational expectation equilibrium," Journal of Economic Dynamics and Control, Elsevier, vol. 31(1), pages 81-109, January.
    15. Alexander Mayer, 2022. "Estimation and inference in adaptive learning models with slowly decreasing gains," Journal of Time Series Analysis, Wiley Blackwell, vol. 43(5), pages 720-749, September.
    16. Myles Callan & Eric Ghysels & Norman R. Swanson, 1998. "Monetary Policy Rules with Model and Data Uncertainty," CIRANO Working Papers 98s-40, CIRANO.
    17. Timothy Kam, 2004. "Two-sided Learning and Optimal Monetary Policy in an Open Economy Model," Economics Discussion / Working Papers 04-07, The University of Western Australia, Department of Economics.
    18. Heinemann, Maik & Lange, Carsten, 1997. "Modellierung von Preiserwartungen durch neuronale Netze," Hannover Economic Papers (HEP) dp-203, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    19. Flam, Sjur Didrik, 1996. "Approaches to economic equilibrium," Journal of Economic Dynamics and Control, Elsevier, vol. 20(9-10), pages 1505-1522.

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