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Cathy W. S. Chen

Citations

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

Working papers

  1. Chen, Cathy W.S. & Gerlach, Richard & Lin, Edward M.H., 2014. "Bayesian Assessment of Dynamic Quantile Forecasts," Working Papers 2014-04, University of Sydney Business School, Discipline of Business Analytics.

    Cited by:

    1. Rangika Peiris & Minh-Ngoc Tran & Chao Wang & Richard Gerlach, 2024. "Loss-based Bayesian Sequential Prediction of Value at Risk with a Long-Memory and Non-linear Realized Volatility Model," Papers 2408.13588, arXiv.org.
    2. Ando, Tomohiro & Bai, Jushan, 2018. "Quantile co-movement in financial markets: A panel quantile model with unobserved heterogeneity," MPRA Paper 88765, University Library of Munich, Germany.

  2. Chen, Cathy W.S. & Gerlach, Richard, 2014. "Semi-parametric Expected Shortfall Forecasting," Working Papers 2014_02, University of Sydney Business School, Discipline of Business Analytics.

    Cited by:

    1. Xu, Xiu & Mihoci, Andrija & Härdle, Wolfgang Karl, 2018. "lCARE - localizing conditional autoregressive expectiles," Journal of Empirical Finance, Elsevier, vol. 48(C), pages 198-220.
    2. Richard Gerlach & Chao Wang, 2016. "Bayesian Semi-parametric Realized-CARE Models for Tail Risk Forecasting Incorporating Realized Measures," Papers 1612.08488, arXiv.org.

  3. Chen, Cathy W.S. & Gerlach, Richard & Lin, Liou-Yan, 2012. "Bayesian Semi-parametric Expected Shortfall Forecasting in Financial M arkets," Working Papers 12 BAWP, University of Sydney Business School, Discipline of Business Analytics.

    Cited by:

    1. Xu, Xiu & Mihoci, Andrija & Härdle, Wolfgang Karl, 2018. "lCARE - localizing conditional autoregressive expectiles," Journal of Empirical Finance, Elsevier, vol. 48(C), pages 198-220.
    2. Marco Bottone & Lea Petrella & Mauro Bernardi, 2021. "Unified Bayesian conditional autoregressive risk measures using the skew exponential power distribution," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 30(3), pages 1079-1107, September.

  4. Chen, Cathy W.S. & Gerlach, Richard & Lee, Wcw & Lin, Edward M.H., 2011. "Bayesian Forecasting for Financial Risk Management, Pre and Post the Global Financial Crisis," Working Papers 03/2011, University of Sydney Business School, Discipline of Business Analytics.

    Cited by:

    1. Chang, Carolyn W. & Li, Xiaodan & Lin, Edward M.H. & Yu, Min-Teh, 2018. "Systemic risk, interconnectedness, and non-core activities in Taiwan insurance industry," International Review of Economics & Finance, Elsevier, vol. 55(C), pages 273-284.
    2. Cathy W. S. Chen & Richard Gerlach & Bruce B. K. Hwang & Michael McAleer, 2011. "Forecasting Value-at-Risk Using Nonlinear Regression Quantiles and the Intra-day Range," KIER Working Papers 775, Kyoto University, Institute of Economic Research.
    3. Wenting Zhang & Shigeyuki Hamori, 2020. "Do Machine Learning Techniques and Dynamic Methods Help Forecast US Natural Gas Crises?," Energies, MDPI, vol. 13(9), pages 1-22, May.
    4. Lu-Tao Zhao & Li-Na Liu & Zi-Jie Wang & Ling-Yun He, 2019. "Forecasting Oil Price Volatility in the Era of Big Data: A Text Mining for VaR Approach," Sustainability, MDPI, vol. 11(14), pages 1-20, July.
    5. Lin, Edward M.H. & Sun, Edward W. & Yu, Min-Teh, 2020. "Behavioral data-driven analysis with Bayesian method for risk management of financial services," International Journal of Production Economics, Elsevier, vol. 228(C).
    6. Laura Garcia-Jorcano & Alfonso Novales, 2019. "Volatility specifications versus probability distributions in VaR forecasting," Documentos de Trabajo del ICAE 2019-26, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    7. Kim, Minjo & Lee, Sangyeol, 2016. "Nonlinear expectile regression with application to Value-at-Risk and expected shortfall estimation," Computational Statistics & Data Analysis, Elsevier, vol. 94(C), pages 1-19.
    8. Marius Galabe Sampid & Haslifah M Hasim & Hongsheng Dai, 2018. "Refining value-at-risk estimates using a Bayesian Markov-switching GJR-GARCH copula-EVT model," PLOS ONE, Public Library of Science, vol. 13(6), pages 1-33, June.
    9. Cathy W. S. Chen & Edward M. H. Lin & Tara F. J. Huang, 2022. "Bayesian quantile forecasting via the realized hysteretic GARCH model," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(7), pages 1317-1337, November.
    10. Chui-Chun Tsai & Tsun-Siou Lee, 2017. "Liquidity-Adjusted Value-at-Risk for TWSE Leverage/ Inverse ETFs: A Hellinger Distance Measure Research," Journal of Economics and Management, College of Business, Feng Chia University, Taiwan, vol. 13(1), pages 53-81, February.
    11. Nieto, Maria Rosa & Ruiz, Esther, 2016. "Frontiers in VaR forecasting and backtesting," International Journal of Forecasting, Elsevier, vol. 32(2), pages 475-501.
    12. Cathy Chen & Feng-Chi Liu & Mike So, 2013. "Threshold variable selection of asymmetric stochastic volatility models," Computational Statistics, Springer, vol. 28(6), pages 2415-2447, December.
    13. Jean-Paul Laurent & Hassan Omidi Firouzi, 2022. "Market Risk and Volatility Weighted Historical Simulation After Basel III," Working Papers hal-03679434, HAL.
    14. Chang Liu & Raja Nassar & Min Guo, 2015. "A Method of Retail Mortgage Stress Testing: Based on Time‐Frame and Magnitude Analysis," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 34(4), pages 261-274, July.
    15. Cathy W.S. Chen & Toshiaki Watanabe, 2019. "Bayesian modeling and forecasting of Value‐at‐Risk via threshold realized volatility," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 35(3), pages 747-765, May.
    16. Chi Ming Wong & Lei Lam Olivia Ting, 2016. "A Quantile Regression Approach to the Multiple Period Value at Risk Estimation," Journal of Economics and Management, College of Business, Feng Chia University, Taiwan, vol. 12(1), pages 1-35, February.
    17. Oksana Hoshovska & Zhanna Poplavska & Jana Kajanova & Olena Trevoho, 2023. "Random Risk Factors Influencing Cash Flows: Modifying RADR," Mathematics, MDPI, vol. 11(2), pages 1-22, January.
    18. Wilson Ye Chen & Richard H. Gerlach, 2017. "Semiparametric GARCH via Bayesian model averaging," Papers 1708.07587, arXiv.org.
    19. Candia, Claudio & Herrera, Rodrigo, 2024. "An empirical review of dynamic extreme value models for forecasting value at risk, expected shortfall and expectile," Journal of Empirical Finance, Elsevier, vol. 77(C).
    20. Laura Garcia-Jorcano & Alfonso Novales, 2020. "A dominance approach for comparing the performance of VaR forecasting models," Computational Statistics, Springer, vol. 35(3), pages 1411-1448, September.
    21. Chen, Cathy W.S. & Watanabe, Toshiaki & Lin, Edward M.H., 2023. "Bayesian estimation of realized GARCH-type models with application to financial tail risk management," Econometrics and Statistics, Elsevier, vol. 28(C), pages 30-46.
    22. Fries, Christian P. & Nigbur, Tobias & Seeger, Norman, 2017. "Displaced relative changes in historical simulation: Application to risk measures of interest rates with phases of negative rates," Journal of Empirical Finance, Elsevier, vol. 42(C), pages 175-198.
    23. Maria-Teresa Bosch-Badia & Joan Montllor-Serrats & Maria-Antonia Tarrazon-Rodon, 2020. "Risk Analysis through the Half-Normal Distribution," Mathematics, MDPI, vol. 8(11), pages 1-27, November.
    24. Sonia Benito Muela & Carmen López-Martín & Mª Ángeles Navarro, 2017. "The Role of the Skewed Distributions in the Framework of Extreme Value Theory (EVT)," International Business Research, Canadian Center of Science and Education, vol. 10(11), pages 88-102, November.
    25. Mauro Bernardi & Leopoldo Catania & Lea Petrella, 2014. "Are news important to predict large losses?," Papers 1410.6898, arXiv.org, revised Oct 2014.
    26. Pilar Abad Romero & Sonia Benito Muela & Miguel Angel Sánchez Granero & Carmen López, 2013. "Evaluating the performance of the skewed distributions to forecast Value at Risk in the Global Financial Crisis," Documentos de Trabajo del ICAE 2013-40, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.

  5. Cathy W. S. Chen & Richard Gerlach & Bruce B. K. Hwang & Michael McAleer, 2011. "Forecasting Value-at-Risk Using Nonlinear Regression Quantiles and the Intra-day Range," Working Papers in Economics 11/22, University of Canterbury, Department of Economics and Finance.

    Cited by:

    1. Rita Pimentel & Morten Risstad & Sjur Westgaard, 2022. "Predicting interest rate distributions using PCA & quantile regression," Digital Finance, Springer, vol. 4(4), pages 291-311, December.
    2. Fuertes, Ana-Maria & Olmo, Jose, 2013. "Optimally harnessing inter-day and intra-day information for daily value-at-risk prediction," International Journal of Forecasting, Elsevier, vol. 29(1), pages 28-42.
    3. David Kohns & Arnab Bhattacharjee, 2020. "Nowcasting Growth using Google Trends Data: A Bayesian Structural Time Series Model," Papers 2011.00938, arXiv.org, revised May 2022.
    4. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    5. Bagher Adabi & Mohsen Mehrara & Shapour Mohammadi, 2015. "Evaluation Approaches of Value at Risk for Tehran Stock Exchange," Iranian Economic Review (IER), Faculty of Economics,University of Tehran.Tehran,Iran, vol. 19(1), pages 41-62, Winter.
    6. Peng, Wei & Hu, Shichao & Chen, Wang & Zeng, Yu-feng & Yang, Lu, 2019. "Modeling the joint dynamic value at risk of the volatility index, oil price, and exchange rate," International Review of Economics & Finance, Elsevier, vol. 59(C), pages 137-149.
    7. Velasco, Sofia, 2024. "Asymmetries in the transmission of monetary policy shocks over the business cycle: a Bayesian Quantile Factor Augmented VAR," Working Paper Series 2983, European Central Bank.
    8. Kim, Minjo & Lee, Sangyeol, 2016. "Nonlinear expectile regression with application to Value-at-Risk and expected shortfall estimation," Computational Statistics & Data Analysis, Elsevier, vol. 94(C), pages 1-19.
    9. Seyfi, Seyed Mohammad Sina & Sharifi, Azin & Arian, Hamidreza, 2021. "Portfolio Value-at-Risk and expected-shortfall using an efficient simulation approach based on Gaussian Mixture Model," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 190(C), pages 1056-1079.
    10. David Kohns & Tibor Szendrei, 2020. "Horseshoe Prior Bayesian Quantile Regression," Papers 2006.07655, arXiv.org, revised Mar 2021.
    11. 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.
    12. Nieto, Maria Rosa & Ruiz, Esther, 2016. "Frontiers in VaR forecasting and backtesting," International Journal of Forecasting, Elsevier, vol. 32(2), pages 475-501.
    13. Meng, Xiaochun & Taylor, James W., 2018. "An approximate long-memory range-based approach for value at risk estimation," International Journal of Forecasting, Elsevier, vol. 34(3), pages 377-388.
    14. Liu Xiaochun & Luger Richard, 2018. "Markov-switching quantile autoregression: a Gibbs sampling approach," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 22(2), pages 1, April.
    15. Yun Duan, 2022. "A Novel Interval Energy-Forecasting Method for Sustainable Building Management Based on Deep Learning," Sustainability, MDPI, vol. 14(14), pages 1-18, July.
    16. CHEN, Cathy W.S. & WENG, Monica M.C. & WATANABE, Toshiaki & 渡部, 渡部, 2015. "Employing Bayesian Forecasting of Value-at-Risk to Determine an Appropriate Model for Risk Management," Discussion paper series HIAS-E-16, Hitotsubashi Institute for Advanced Study, Hitotsubashi University.
    17. Kaihua Deng, 2015. "Predicting By Learning: An Adaptive Rationale," Annals of Financial Economics (AFE), World Scientific Publishing Co. Pte. Ltd., vol. 10(02), pages 1-14, December.
    18. Jordan, Steven J. & Vivian, Andrew & Wohar, Mark E., 2017. "Forecasting market returns: bagging or combining?," International Journal of Forecasting, Elsevier, vol. 33(1), pages 102-120.
    19. Chiranjit Dutta & Kara Karpman & Sumanta Basu & Nalini Ravishanker, 2023. "Review of Statistical Approaches for Modeling High-Frequency Trading Data," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 85(1), pages 1-48, May.
    20. Seyed Mohammad Sina Seyfi & Azin Sharifi & Hamidreza Arian, 2020. "Portfolio Risk Measurement Using a Mixture Simulation Approach," Papers 2011.07994, arXiv.org.
    21. Kohns, David & Bhattacharjee, Arnab, 2023. "Nowcasting growth using Google Trends data: A Bayesian Structural Time Series model," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1384-1412.
    22. Henning Fischer & Ángela Blanco‐FERNÁndez & Peter Winker, 2016. "Predicting Stock Return Volatility: Can We Benefit from Regression Models for Return Intervals?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 35(2), pages 113-146, March.
    23. Taylor, James W., 2020. "Forecast combinations for value at risk and expected shortfall," International Journal of Forecasting, Elsevier, vol. 36(2), pages 428-441.
    24. Arian, Hamid & Moghimi, Mehrdad & Tabatabaei, Ehsan & Zamani, Shiva, 2022. "Encoded Value-at-Risk: A machine learning approach for portfolio risk measurement," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 202(C), pages 500-525.

  6. Chan, Nancy Y. C. & Chen, Cathy W.S. & Gerlach, Richard, 2009. "Bayesian time-varying quantile forecasting for Value-at-Risk in financial markets," Working Papers 9 OMEWP, University of Sydney Business School, Discipline of Business Analytics.

    Cited by:

    1. Klochkov, Yegor & Härdle, Wolfgang Karl & Xu, Xiu, 2019. "Localizing Multivariate CAViaR," IRTG 1792 Discussion Papers 2019-007, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    2. Cathy W. S. Chen & Richard Gerlach & Bruce B. K. Hwang & Michael McAleer, 2011. "Forecasting Value-at-Risk Using Nonlinear Regression Quantiles and the Intra-day Range," KIER Working Papers 775, Kyoto University, Institute of Economic Research.
    3. Zhengkun Li & Minh-Ngoc Tran & Chao Wang & Richard Gerlach & Junbin Gao, 2020. "A Bayesian Long Short-Term Memory Model for Value at Risk and Expected Shortfall Joint Forecasting," Papers 2001.08374, arXiv.org, revised May 2021.
    4. Pfarrhofer, Michael, 2022. "Modeling tail risks of inflation using unobserved component quantile regressions," Journal of Economic Dynamics and Control, Elsevier, vol. 143(C).
    5. Alhamzawi, Rahim & Yu, Keming, 2013. "Conjugate priors and variable selection for Bayesian quantile regression," Computational Statistics & Data Analysis, Elsevier, vol. 64(C), pages 209-219.
    6. Ayoub Ammy-Driss & Matthieu Garcin, 2021. "Efficiency of the financial markets during the COVID-19 crisis: time-varying parameters of fractional stable dynamics," Working Papers hal-02903655, HAL.
    7. Ayoub Ammy-Driss & Matthieu Garcin, 2020. "Efficiency of the financial markets during the COVID-19 crisis: time-varying parameters of fractional stable dynamics," Papers 2007.10727, arXiv.org, revised Nov 2021.
    8. Bagher Adabi & Mohsen Mehrara & Shapour Mohammadi, 2015. "Evaluation Approaches of Value at Risk for Tehran Stock Exchange," Iranian Economic Review (IER), Faculty of Economics,University of Tehran.Tehran,Iran, vol. 19(1), pages 41-62, Winter.
    9. Zongwu Cai & Xiyuan Liu, 2020. "A Functional-Coefficient VAR Model for Dynamic Quantiles with Constructing Financial Network," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202017, University of Kansas, Department of Economics, revised Oct 2020.
    10. Gerlach, Richard & Wang, Chao, 2020. "Semi-parametric dynamic asymmetric Laplace models for tail risk forecasting, incorporating realized measures," International Journal of Forecasting, Elsevier, vol. 36(2), pages 489-506.
    11. Prodosh Simlai, 2021. "Accrual mispricing, value-at-risk, and expected stock returns," Review of Quantitative Finance and Accounting, Springer, vol. 57(4), pages 1487-1517, November.
    12. Korobilis, Dimitris & Landau, Bettina & Musso, Alberto & Phella, Anthoulla, 2021. "The time-varying evolution of inflation risks," Working Paper Series 2600, European Central Bank.
    13. Rangika Peiris & Minh-Ngoc Tran & Chao Wang & Richard Gerlach, 2024. "Loss-based Bayesian Sequential Prediction of Value at Risk with a Long-Memory and Non-linear Realized Volatility Model," Papers 2408.13588, arXiv.org.
    14. Hubner, Stefan, 2016. "Topics in nonparametric identification and estimation," Other publications TiSEM 08fce56b-3193-46e0-871b-0, Tilburg University, School of Economics and Management.
    15. Li, Dan & Clements, Adam & Drovandi, Christopher, 2023. "A Bayesian approach for more reliable tail risk forecasts," Journal of Financial Stability, Elsevier, vol. 64(C).
    16. Marco Bottone & Lea Petrella & Mauro Bernardi, 2021. "Unified Bayesian conditional autoregressive risk measures using the skew exponential power distribution," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 30(3), pages 1079-1107, September.
    17. Korobilis, Dimitris, 2015. "Quantile forecasts of inflation under model uncertainty," MPRA Paper 64341, University Library of Munich, Germany.
    18. 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.
    19. Nieto, Maria Rosa & Ruiz, Esther, 2016. "Frontiers in VaR forecasting and backtesting," International Journal of Forecasting, Elsevier, vol. 32(2), pages 475-501.
    20. Zijian Zeng & Meng Li, 2020. "Bayesian Median Autoregression for Robust Time Series Forecasting," Papers 2001.01116, arXiv.org, revised Dec 2020.
    21. Bhattacharya, Indrabati & Ghosal, Subhashis, 2021. "Bayesian multivariate quantile regression using Dependent Dirichlet Process prior," Journal of Multivariate Analysis, Elsevier, vol. 185(C).
    22. So, Mike K.P. & Chung, Ray S.W., 2015. "Statistical inference for conditional quantiles in nonlinear time series models," Journal of Econometrics, Elsevier, vol. 189(2), pages 457-472.
    23. Richard Gerlach & Chao Wang, 2016. "Forecasting risk via realized GARCH, incorporating the realized range," Quantitative Finance, Taylor & Francis Journals, vol. 16(4), pages 501-511, April.
    24. Griffin, Jim E. & Mitrodima, Gelly, 2020. "A Bayesian quantile time series model for asset returns," LSE Research Online Documents on Economics 105610, London School of Economics and Political Science, LSE Library.
    25. Cathy W. S. Chen & Takaaki Koike & Wei-Hsuan Shau, 2024. "Tail risk forecasting with semi-parametric regression models by incorporating overnight information," Papers 2402.07134, arXiv.org.
    26. Mehmet Pinar & Thanasis Stengos & M. Ege Yazgan, 2018. "Quantile forecast combination using stochastic dominance," Empirical Economics, Springer, vol. 55(4), pages 1717-1755, December.
    27. Liu Xiaochun & Luger Richard, 2018. "Markov-switching quantile autoregression: a Gibbs sampling approach," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 22(2), pages 1, April.
    28. Hagfors, Lars Ivar & Bunn, Derek & Kristoffersen, Eline & Staver, Tiril Toftdahl & Westgaard, Sjur, 2016. "Modeling the UK electricity price distributions using quantile regression," Energy, Elsevier, vol. 102(C), pages 231-243.
    29. Hayette Gatfaoui, 2017. "Equity market information and credit risk signaling: A quantile cointegrating regression approach," Post-Print hal-01745285, HAL.
    30. Mateusz Buczyński & Marcin Chlebus, 2019. "Old-fashioned parametric models are still the best. A comparison of Value-at-Risk approaches in several volatility states," Working Papers 2019-12, Faculty of Economic Sciences, University of Warsaw.
    31. Yuta Kurose & Yasuhiro Omori, 2012. "Bayesian Analysis of Time-Varying Quantiles Using a Smoothing Spline," CIRJE F-Series CIRJE-F-845, CIRJE, Faculty of Economics, University of Tokyo.
    32. CHEN, Cathy W.S. & WENG, Monica M.C. & WATANABE, Toshiaki & 渡部, 渡部, 2015. "Employing Bayesian Forecasting of Value-at-Risk to Determine an Appropriate Model for Risk Management," Discussion paper series HIAS-E-16, Hitotsubashi Institute for Advanced Study, Hitotsubashi University.
    33. Chi Ming Wong & Lei Lam Olivia Ting, 2016. "A Quantile Regression Approach to the Multiple Period Value at Risk Estimation," Journal of Economics and Management, College of Business, Feng Chia University, Taiwan, vol. 12(1), pages 1-35, February.
    34. Ando, Tomohiro & Bai, Jushan, 2018. "Quantile co-movement in financial markets: A panel quantile model with unobserved heterogeneity," MPRA Paper 88765, University Library of Munich, Germany.
    35. Cathy Chen & Richard Gerlach, 2013. "Semi-parametric quantile estimation for double threshold autoregressive models with heteroskedasticity," Computational Statistics, Springer, vol. 28(3), pages 1103-1131, June.
    36. Storti, Giuseppe & Wang, Chao, 2022. "Nonparametric expected shortfall forecasting incorporating weighted quantiles," International Journal of Forecasting, Elsevier, vol. 38(1), pages 224-239.
    37. Xiaochun Liu, 2016. "Markov switching quantile autoregression," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 70(4), pages 356-395, November.
    38. Mauro Bernardi & Ghislaine Gayraud & Lea Petrella, 2013. "Bayesian inference for CoVaR," Papers 1306.2834, arXiv.org, revised Nov 2013.
    39. Jabed H. Tomal & Hafizur Rahman, 2021. "A Bayesian piecewise linear model for the detection of breakpoints in housing prices," METRON, Springer;Sapienza Università di Roma, vol. 79(3), pages 361-381, December.
    40. Zeng, Zijian & Li, Meng, 2021. "Bayesian median autoregression for robust time series forecasting," International Journal of Forecasting, Elsevier, vol. 37(2), pages 1000-1010.
    41. Paraschiv, Florentina & Bunn, Derek & Westgaard, Sjur, 2016. "Estimation and Application of Fully Parametric Multifactor Quantile Regression with Dynamic Coefficients," Working Papers on Finance 1607, University of St. Gallen, School of Finance.
    42. Ammy-Driss, Ayoub & Garcin, Matthieu, 2023. "Efficiency of the financial markets during the COVID-19 crisis: Time-varying parameters of fractional stable dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 609(C).
    43. Sonia Benito Muela & Carmen López-Martín & Mª Ángeles Navarro, 2017. "The Role of the Skewed Distributions in the Framework of Extreme Value Theory (EVT)," International Business Research, Canadian Center of Science and Education, vol. 10(11), pages 88-102, November.
    44. Korobilis, Dimitris, 2017. "Quantile regression forecasts of inflation under model uncertainty," International Journal of Forecasting, Elsevier, vol. 33(1), pages 11-20.
    45. Jiawen Luo & Shengjie Fu & Oguzhan Cepni & Rangan Gupta, 2024. "Climate Risks and Forecastability of US Inflation: Evidence from Dynamic Quantile Model Averaging," Working Papers 202420, University of Pretoria, Department of Economics.
    46. Richard Gerlach & Zudi Lu & Hai Huang, 2013. "Exponentially Smoothing the Skewed Laplace Distribution for Value‐at‐Risk Forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 32(6), pages 534-550, September.
    47. Derek Bunn, Arne Andresen, Dipeng Chen, Sjur Westgaard, 2016. "Analysis and Forecasting of Electricty Price Risks with Quantile Factor Models," The Energy Journal, International Association for Energy Economics, vol. 0(Number 1).
    48. Mitrodima, Gelly & Oberoi, Jaideep, 2024. "CAViaR models for Value-at-Risk and Expected Shortfall with long range dependency features," LSE Research Online Documents on Economics 120880, London School of Economics and Political Science, LSE Library.
    49. Chao Wang & Richard Gerlach, 2019. "Semi-parametric Realized Nonlinear Conditional Autoregressive Expectile and Expected Shortfall," Papers 1906.09961, arXiv.org.
    50. Federico Gatta & Fabrizio Lillo & Piero Mazzarisi, 2024. "CAESar: Conditional Autoregressive Expected Shortfall," Papers 2407.06619, arXiv.org.
    51. Huarng, Kun-Huang & Yu, Tiffany Hui-Kuang, 2014. "A new quantile regression forecasting model," Journal of Business Research, Elsevier, vol. 67(5), pages 779-784.
    52. Vegard Høghaug Larsen & Nicolò Maffei-Faccioli & Laura Pagenhardt, 2023. "Where do they care? The ECB in the media and inflation expectations," Working Papers No 04/2023, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    53. Wilson Ye Chen & Gareth W. Peters & Richard H. Gerlach & Scott A. Sisson, 2017. "Dynamic Quantile Function Models," Papers 1707.02587, arXiv.org, revised May 2021.
    54. Komunjer, Ivana, 2013. "Quantile Prediction," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 961-994, Elsevier.
    55. Richard Gerlach & Chao Wang, 2018. "Semi-parametric Dynamic Asymmetric Laplace Models for Tail Risk Forecasting, Incorporating Realized Measures," Papers 1805.08653, arXiv.org.
    56. Liu, Xiaochun & Luger, Richard, 2015. "Unfolded GARCH models," Journal of Economic Dynamics and Control, Elsevier, vol. 58(C), pages 186-217.

Articles

  1. Chen, Cathy W.S. & Watanabe, Toshiaki & Lin, Edward M.H., 2023. "Bayesian estimation of realized GARCH-type models with application to financial tail risk management," Econometrics and Statistics, Elsevier, vol. 28(C), pages 30-46.

    Cited by:

    1. Cathy W. S. Chen & Takaaki Koike & Wei‐Hsuan Shau, 2024. "Tail risk forecasting with semiparametric regression models by incorporating overnight information," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(5), pages 1492-1512, August.
    2. Cathy W. S. Chen & Takaaki Koike & Wei-Hsuan Shau, 2024. "Tail risk forecasting with semi-parametric regression models by incorporating overnight information," Papers 2402.07134, arXiv.org.

  2. Chen, Cathy W.S. & Liu, Feng-Chi & Pingal, Aljo Clair, 2023. "Integer-valued transfer function models for counts that show zero inflation," Statistics & Probability Letters, Elsevier, vol. 193(C).

    Cited by:

    1. Chen, Cathy W.S. & Chen, Chun-Shu & Hsiung, Mo-Hua, 2023. "Bayesian modeling of spatial integer-valued time series," Computational Statistics & Data Analysis, Elsevier, vol. 188(C).

  3. Chen, Cathy W.S. & Hsu, Hsiao-Yun & Watanabe, Toshiaki, 2023. "Tail risk forecasting of realized volatility CAViaR models," Finance Research Letters, Elsevier, vol. 51(C).

    Cited by:

    1. Zhu, Qinwen & Diao, Xundi & Wu, Chongfeng, 2023. "Volatility forecast with the regularity modifications," Finance Research Letters, Elsevier, vol. 58(PA).
    2. Cathy W. S. Chen & Takaaki Koike & Wei‐Hsuan Shau, 2024. "Tail risk forecasting with semiparametric regression models by incorporating overnight information," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(5), pages 1492-1512, August.
    3. Cathy W. S. Chen & Takaaki Koike & Wei-Hsuan Shau, 2024. "Tail risk forecasting with semi-parametric regression models by incorporating overnight information," Papers 2402.07134, arXiv.org.

  4. Cathy W. S. Chen & Edward M. H. Lin & Tara F. J. Huang, 2022. "Bayesian quantile forecasting via the realized hysteretic GARCH model," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(7), pages 1317-1337, November.

    Cited by:

    1. Cathy W. S. Chen & Takaaki Koike & Wei‐Hsuan Shau, 2024. "Tail risk forecasting with semiparametric regression models by incorporating overnight information," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(5), pages 1492-1512, August.
    2. Cathy W. S. Chen & Takaaki Koike & Wei-Hsuan Shau, 2024. "Tail risk forecasting with semi-parametric regression models by incorporating overnight information," Papers 2402.07134, arXiv.org.

  5. Cathy W. S. Chen & Bonny Lee, 2021. "Bayesian inference of multiple structural change models with asymmetric GARCH errors," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 30(3), pages 1053-1078, September.

    Cited by:

    1. Hsu, Shu-Han & Cheng, Po-Keng & Yang, Yiwen, 2024. "Diversification, hedging, and safe-haven characteristics of cryptocurrencies: A structural change approach," International Review of Financial Analysis, Elsevier, vol. 93(C).

  6. Cathy W. S. Chen & Sangyeol Lee & K. Khamthong, 2021. "Bayesian inference of nonlinear hysteretic integer-valued GARCH models for disease counts," Computational Statistics, Springer, vol. 36(1), pages 261-281, March.

    Cited by:

    1. Cathy W. S. Chen & Edward M. H. Lin & Tara F. J. Huang, 2022. "Bayesian quantile forecasting via the realized hysteretic GARCH model," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(7), pages 1317-1337, November.
    2. Chen, Cathy W.S. & Liu, Feng-Chi & Pingal, Aljo Clair, 2023. "Integer-valued transfer function models for counts that show zero inflation," Statistics & Probability Letters, Elsevier, vol. 193(C).
    3. Chen, Cathy W.S. & Chen, Chun-Shu & Hsiung, Mo-Hua, 2023. "Bayesian modeling of spatial integer-valued time series," Computational Statistics & Data Analysis, Elsevier, vol. 188(C).

  7. Cathy W. S. Chen & Hong Than-Thi & Manabu Asai, 2021. "On a Bivariate Hysteretic AR-GARCH Model with Conditional Asymmetry in Correlations," Computational Economics, Springer;Society for Computational Economics, vol. 58(2), pages 413-433, August.

    Cited by:

    1. Linyu Cao & Ruili Sun & Tiefeng Ma & Conan Liu, 2023. "On Asymmetric Correlations and Their Applications in Financial Markets," JRFM, MDPI, vol. 16(3), pages 1-18, March.

  8. Cathy W.S. Chen & Toshiaki Watanabe, 2019. "Bayesian modeling and forecasting of Value‐at‐Risk via threshold realized volatility," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 35(3), pages 747-765, May.

    Cited by:

    1. Chen, Cathy W.S. & Hsu, Hsiao-Yun & Watanabe, Toshiaki, 2023. "Tail risk forecasting of realized volatility CAViaR models," Finance Research Letters, Elsevier, vol. 51(C).
    2. Cathy W. S. Chen & Edward M. H. Lin & Tara F. J. Huang, 2022. "Bayesian quantile forecasting via the realized hysteretic GARCH model," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(7), pages 1317-1337, November.
    3. Cathy W. S. Chen & Takaaki Koike & Wei-Hsuan Shau, 2024. "Tail risk forecasting with semi-parametric regression models by incorporating overnight information," Papers 2402.07134, arXiv.org.
    4. Chen, Cathy W.S. & Watanabe, Toshiaki & Lin, Edward M.H., 2023. "Bayesian estimation of realized GARCH-type models with application to financial tail risk management," Econometrics and Statistics, Elsevier, vol. 28(C), pages 30-46.

  9. Manh Cuong Dong & Cathy W. S. Chen & Sangyoel Lee & Songsak Sriboonchitta, 2019. "How Strong is the Relationship Among Gold and USD Exchange Rates? Analytics Based on Structural Change Models," Computational Economics, Springer;Society for Computational Economics, vol. 53(1), pages 343-366, January.

    Cited by:

    1. Raza Syed Ali & Shah Nida & Ali Muhammad & Shahbaz Muhammad, 2021. "Do Exchange Rates Fluctuations Influence Gold Price in G7 Countries? New Insights from a Nonparametric Causality-in-Quantiles Test," Zagreb International Review of Economics and Business, Sciendo, vol. 24(2), pages 37-57.
    2. Hsu, Shu-Han & Cheng, Po-Keng & Yang, Yiwen, 2024. "Diversification, hedging, and safe-haven characteristics of cryptocurrencies: A structural change approach," International Review of Financial Analysis, Elsevier, vol. 93(C).
    3. Abid, Ilyes & Bouri, Elie & Galariotis, Emilios & Guesmi, Khaled & Mzoughi, Hela, 2023. "Bitcoin vs. fiat currencies: Insights from extreme dependence and risk spillover analysis with financial markets," International Review of Financial Analysis, Elsevier, vol. 90(C).
    4. Golitsis, Petros & Gkasis, Pavlos & Bellos, Sotirios K., 2022. "Dynamic spillovers and linkages between gold, crude oil, S&P 500, and other economic and financial variables. Evidence from the USA," The North American Journal of Economics and Finance, Elsevier, vol. 63(C).
    5. Cathy W. S. Chen & Bonny Lee, 2021. "Bayesian inference of multiple structural change models with asymmetric GARCH errors," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 30(3), pages 1053-1078, September.
    6. Awatef Ourir & Elie Bouri & Essahbi Essaadi, 2021. "Hedging the Risks of MENA Stock Markets with Gold: Evidence from the Spectral Approach," Working Papers 1511, Economic Research Forum, revised 20 Nov 2021.
    7. Tanin, Tauhidul Islam & Sarker, Ashutosh & Brooks, Robert, 2021. "Do currency exchange rates impact gold prices? New evidence from the ongoing COVID-19 period," International Review of Financial Analysis, Elsevier, vol. 77(C).
    8. Sahu, Pritish Kumar & Bal, Debi Prasad & Kundu, Pradip, 2022. "Gold price and exchange rate in pre and during Covid-19 period in India: Modelling dependence using copulas," Resources Policy, Elsevier, vol. 79(C).

  10. Cathy W. S. Chen & Khemmanant Khamthong & Sangyeol Lee, 2019. "Markov switching integer‐valued generalized auto‐regressive conditional heteroscedastic models for dengue counts," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 68(4), pages 963-983, August.

    Cited by:

    1. Huaping Chen & Qi Li & Fukang Zhu, 2023. "A covariate-driven beta-binomial integer-valued GARCH model for bounded counts with an application," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 86(7), pages 805-826, October.
    2. Matteo Iacopini & Carlo R. M. A. Santagiustina, 2020. "Filtering the intensity of public concern from social media count data with jumps," Papers 2012.13267, arXiv.org.
    3. Han Li & Zijian Liu & Kai Yang & Xiaogang Dong & Wenshan Wang, 2024. "A pth-order random coefficients mixed binomial autoregressive process with explanatory variables," Computational Statistics, Springer, vol. 39(5), pages 2581-2604, July.
    4. Lee, Sangyeol & Kim, Dongwon & Kim, Byungsoo, 2023. "Modeling and inference for multivariate time series of counts based on the INGARCH scheme," Computational Statistics & Data Analysis, Elsevier, vol. 177(C).
    5. Chen, Cathy W.S. & Liu, Feng-Chi & Pingal, Aljo Clair, 2023. "Integer-valued transfer function models for counts that show zero inflation," Statistics & Probability Letters, Elsevier, vol. 193(C).
    6. Bracher, Johannes & Held, Leonhard, 2022. "Endemic-epidemic models with discrete-time serial interval distributions for infectious disease prediction," International Journal of Forecasting, Elsevier, vol. 38(3), pages 1221-1233.

  11. Chen, Cathy W.S. & Dong, Manh Cuong & Liu, Nathan & Sriboonchitta, Songsak, 2019. "Inferences of default risk and borrower characteristics on P2P lending," The North American Journal of Economics and Finance, Elsevier, vol. 50(C).

    Cited by:

    1. Li, ZhouPing & Ge, RuYi & Guo, XiaoShuang & Cai, Lingfei, 2021. "Can individual investors learn from experience in online P2P lending? Evidence from China," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).
    2. Qian Wang & Jinbao Yang & Yung‐ho Chiu & Tai‐Yu Lin, 2020. "The impact of digital finance on financial efficiency," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 41(7), pages 1225-1236, October.
    3. Qian Wang & Jinbao Yang & Yung‐ho Chiu & Tai‐Yu Lin, 2023. "Cross‐regional comparative study on digital finance and finance efficiency in China: The eastern and non‐eastern areas," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 44(1), pages 68-83, January.
    4. Zhang, Xuan & Ouyang, Ruolan & Liu, Ding & Xu, Liao, 2020. "Determinants of corporate default risk in China: The role of financial constraints," Economic Modelling, Elsevier, vol. 92(C), pages 87-98.
    5. He, Yunwen, 2021. "Using your regular contacts as collateral: The information value of call logs," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).
    6. Wang, Qian & Su, Zhongnan & Chen, Xinyang, 2021. "Information disclosure and the default risk of online peer-to-peer lending platform," Finance Research Letters, Elsevier, vol. 38(C).
    7. Wang, Shaoda & Ye, Dezhu & Liao, Junyun, 2024. "Politeness matters: The role of polite languages in online peer-to-peer lending," Journal of Business Research, Elsevier, vol. 171(C).

  12. Cathy W.S. Chen & Hong Than‐Thi & Mike K.P. So & Songsak Sriboonchitta, 2019. "Quantile forecasting based on a bivariate hysteretic autoregressive model with GARCH errors and time ‐varying correlations," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 35(6), pages 1301-1321, November.

    Cited by:

    1. Cathy W. S. Chen & Hong Than-Thi & Manabu Asai, 2021. "On a Bivariate Hysteretic AR-GARCH Model with Conditional Asymmetry in Correlations," Computational Economics, Springer;Society for Computational Economics, vol. 58(2), pages 413-433, August.
    2. Cathy W. S. Chen & Edward M. H. Lin & Tara F. J. Huang, 2022. "Bayesian quantile forecasting via the realized hysteretic GARCH model," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(7), pages 1317-1337, November.
    3. Shoukun Jiao & Wuyi Ye, 2022. "Dependence and Systemic Risk Analysis Between S&P 500 Index and Sector Indexes: A Conditional Value-at-Risk Approach," Computational Economics, Springer;Society for Computational Economics, vol. 59(3), pages 1203-1229, March.

  13. Dong, Manh Cuong & Tian, Shaonan & Chen, Cathy W.S., 2018. "Predicting failure risk using financial ratios: Quantile hazard model approach," The North American Journal of Economics and Finance, Elsevier, vol. 44(C), pages 204-220.

    Cited by:

    1. Tomasz Korol, 2019. "Dynamic Bankruptcy Prediction Models for European Enterprises," JRFM, MDPI, vol. 12(4), pages 1-15, December.
    2. Chen, Cathy W.S. & Dong, Manh Cuong & Liu, Nathan & Sriboonchitta, Songsak, 2019. "Inferences of default risk and borrower characteristics on P2P lending," The North American Journal of Economics and Finance, Elsevier, vol. 50(C).
    3. Theodore Metaxas & Athanasios Romanopoulos, 2023. "A Literature Review on the Financial Determinants of Hotel Default," JRFM, MDPI, vol. 16(7), pages 1-19, July.
    4. Lawrence, Akvile & Karlsson, Magnus & Nehler, Therese & Thollander, Patrik, 2019. "Effects of monetary investment, payback time and firm characteristics on electricity saving in energy-intensive industry," Applied Energy, Elsevier, vol. 240(C), pages 499-512.

  14. Sangyeol Lee & Siyun Park & Cathy W. S. Chen, 2017. "On Fisher’s dispersion test for integer-valued autoregressive Poisson models with applications," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 46(20), pages 9985-9994, October.

    Cited by:

    1. Christian H. Weiß & Esmeralda Gonçalves & Nazaré Mendes Lopes, 2017. "Testing the compounding structure of the CP-INARCH model," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 80(5), pages 571-603, July.

  15. Chen, Cathy W.S. & Lin, Tsai-Yu, 2017. "Nonparametric tolerance limits for pair trading," Finance Research Letters, Elsevier, vol. 21(C), pages 1-9.

    Cited by:

    1. Law, K.F. & Li, W.K. & Yu, Philip L.H., 2018. "A single-stage approach for cointegration-based pairs trading," Finance Research Letters, Elsevier, vol. 26(C), pages 177-184.
    2. Lin, Tsai-Yu & Chen, Cathy W.S. & Syu, Fong-Yi, 2021. "Multi-asset pair-trading strategy: A statistical learning approach," The North American Journal of Economics and Finance, Elsevier, vol. 55(C).

  16. Cathy W. S. Chen & Sangyeol Lee, 2017. "Bayesian causality test for integer-valued time series models with applications to climate and crime data," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 66(4), pages 797-814, August.

    Cited by:

    1. Cathy W. S. Chen & Sangyeol Lee & K. Khamthong, 2021. "Bayesian inference of nonlinear hysteretic integer-valued GARCH models for disease counts," Computational Statistics, Springer, vol. 36(1), pages 261-281, March.
    2. Kai Yang & Han Li & Dehui Wang & Chenhui Zhang, 2021. "Random coefficients integer-valued threshold autoregressive processes driven by logistic regression," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 105(4), pages 533-557, December.
    3. Berry, Lindsay R. & Helman, Paul & West, Mike, 2020. "Probabilistic forecasting of heterogeneous consumer transaction–sales time series," International Journal of Forecasting, Elsevier, vol. 36(2), pages 552-569.
    4. Luiza S. C. Piancastelli & Wagner Barreto‐Souza & Hernando Ombao, 2023. "Flexible bivariate INGARCH process with a broad range of contemporaneous correlation," Journal of Time Series Analysis, Wiley Blackwell, vol. 44(2), pages 206-222, March.
    5. Federico Bassetti & Giulia Carallo & Roberto Casarin, 2022. "First-order integer-valued autoregressive processes with Generalized Katz innovations," Papers 2202.02029, arXiv.org.
    6. Sefa Awaworyi Churchill & Russell Smyth & Trong‐Anh Trinh, 2023. "Crime, Weather and Climate Change in Australia," The Economic Record, The Economic Society of Australia, vol. 99(324), pages 84-107, March.
    7. Mike West, 2020. "Bayesian forecasting of multivariate time series: scalability, structure uncertainty and decisions," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 72(1), pages 1-31, February.
    8. Xinyang Wang & Dehui Wang & Kai Yang, 2021. "Integer-valued time series model order shrinkage and selection via penalized quasi-likelihood approach," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 84(5), pages 713-750, July.
    9. Kai Yang & Yao Kang & Dehui Wang & Han Li & Yajing Diao, 2019. "Modeling overdispersed or underdispersed count data with generalized Poisson integer-valued autoregressive processes," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 82(7), pages 863-889, October.
    10. Luis E. Nieto-Barajas, 2022. "Dependence on a collection of Poisson random variables," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 31(1), pages 21-39, March.
    11. Chen, Cathy W.S. & Liu, Feng-Chi & Pingal, Aljo Clair, 2023. "Integer-valued transfer function models for counts that show zero inflation," Statistics & Probability Letters, Elsevier, vol. 193(C).
    12. Chen, Cathy W.S. & Chen, Chun-Shu & Hsiung, Mo-Hua, 2023. "Bayesian modeling of spatial integer-valued time series," Computational Statistics & Data Analysis, Elsevier, vol. 188(C).

  17. Chen, Cathy W.S. & Wang, Zona & Sriboonchitta, Songsak & Lee, Sangyeol, 2017. "Pair trading based on quantile forecasting of smooth transition GARCH models," The North American Journal of Economics and Finance, Elsevier, vol. 39(C), pages 38-55.

    Cited by:

    1. Yi-Kai Su & Kae-Yih Tzeng & Chun-Jan Tseng & Cheng-Hsien Lin, 2024. "The Influence of Defense Industry Development Act on the Smooth Transition Dynamics of Stock Volatilities of Defense Industry," Advances in Management and Applied Economics, SCIENPRESS Ltd, vol. 14(3), pages 1-7.
    2. Jolanta Tamošaitienė & Vahidreza Yousefi & Hamed Tabasi, 2021. "Project Portfolio Construction Using Extreme Value Theory," Sustainability, MDPI, vol. 13(2), pages 1-13, January.
    3. Day Yang Liu & Ming Chen Chun & Yi Kai Su, 2021. "The impacts of Covid-19 pandemic on the smooth transition dynamics of stock market index volatilities for the Four Asian Tigers and Japan," International Journal of Research in Business and Social Science (2147-4478), Center for the Strategic Studies in Business and Finance, vol. 10(4), pages 183-194, June.
    4. Day-Yang Liu & Chun-Ming Chen & Yi-Kai Su, 2020. "The Impact of COVID-19 Pandemic on the Smooth Transition Dynamics of Broad-based Indices Volatilities in Taiwan," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 10(5), pages 1-14.
    5. Lin, Tsai-Yu & Chen, Cathy W.S. & Syu, Fong-Yi, 2021. "Multi-asset pair-trading strategy: A statistical learning approach," The North American Journal of Economics and Finance, Elsevier, vol. 55(C).

  18. 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.

    Cited by:

    1. Ando, Tomohiro & Bai, Jushan, 2018. "Quantile co-movement in financial markets: A panel quantile model with unobserved heterogeneity," MPRA Paper 88765, University Library of Munich, Germany.
    2. Wang, Kai Y.K. & Chen, Cathy W.S. & So, Mike K.P., 2023. "Quantile three-factor model with heteroskedasticity, skewness, and leptokurtosis," Computational Statistics & Data Analysis, Elsevier, vol. 182(C).

  19. Chen, Cathy W.S. & Lee, Sangyeol, 2016. "Generalized Poisson autoregressive models for time series of counts," Computational Statistics & Data Analysis, Elsevier, vol. 99(C), pages 51-67.

    Cited by:

    1. Yang, Kai & Yu, Xinyang & Zhang, Qingqing & Dong, Xiaogang, 2022. "On MCMC sampling in self-exciting integer-valued threshold time series models," Computational Statistics & Data Analysis, Elsevier, vol. 169(C).
    2. Cem Cakmakli & Yasin Simsek, 2023. "Bridging the Covid-19 Data and the Epidemiological Model using Time-Varying Parameter SIRD Model," Papers 2301.13692, arXiv.org.
    3. Cathy W. S. Chen & Sangyeol Lee & K. Khamthong, 2021. "Bayesian inference of nonlinear hysteretic integer-valued GARCH models for disease counts," Computational Statistics, Springer, vol. 36(1), pages 261-281, March.
    4. Cem Cakmaklı & Yasin Simsek, 2020. "Bridging the COVID-19 Data and the Epidemiological Model using Time Varying Parameter SIRD Model," Working Paper series 20-23, Rimini Centre for Economic Analysis, revised Feb 2021.
    5. Qi Li & Fukang Zhu, 2020. "Mean targeting estimator for the integer-valued GARCH(1, 1) model," Statistical Papers, Springer, vol. 61(2), pages 659-679, April.
    6. Marinho G. Andrade & Katiane S. Conceição & Nalini Ravishanker, 2024. "Zero-modified count time series modeling with an application to influenza cases," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 108(3), pages 611-637, September.
    7. Federico Bassetti & Giulia Carallo & Roberto Casarin, 2022. "First-order integer-valued autoregressive processes with Generalized Katz innovations," Papers 2202.02029, arXiv.org.
    8. Youngmi Lee & Sangyeol Lee, 2019. "CUSUM test for general nonlinear integer-valued GARCH models: comparison study," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 71(5), pages 1033-1057, October.
    9. Xinyang Wang & Dehui Wang & Kai Yang, 2021. "Integer-valued time series model order shrinkage and selection via penalized quasi-likelihood approach," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 84(5), pages 713-750, July.
    10. Luis E. Nieto-Barajas, 2022. "Dependence on a collection of Poisson random variables," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 31(1), pages 21-39, March.
    11. Chen, Cathy W.S. & Liu, Feng-Chi & Pingal, Aljo Clair, 2023. "Integer-valued transfer function models for counts that show zero inflation," Statistics & Probability Letters, Elsevier, vol. 193(C).
    12. Chen, Cathy W.S. & Chen, Chun-Shu & Hsiung, Mo-Hua, 2023. "Bayesian modeling of spatial integer-valued time series," Computational Statistics & Data Analysis, Elsevier, vol. 188(C).
    13. Kai Yang & Yiwei Zhao & Han Li & Dehui Wang, 2023. "On bivariate threshold Poisson integer-valued autoregressive processes," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 86(8), pages 931-963, November.
    14. Bu Hyoung Lee, 2022. "Bootstrap Prediction Intervals of Temporal Disaggregation," Stats, MDPI, vol. 5(1), pages 1-13, February.

  20. 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.

    Cited by:

    1. Jareño, Francisco & González, María de la O & Tolentino, Marta & Sierra, Karen, 2020. "Bitcoin and gold price returns: A quantile regression and NARDL analysis," Resources Policy, Elsevier, vol. 67(C).
    2. 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.
    3. 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.
    4. Manh Cuong Dong & Cathy W. S. Chen & Manabu Asai, 2023. "Bayesian non‐linear quantile effects on modelling realized kernels," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(1), pages 981-995, January.
    5. 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.
    6. Wright, Calvin & Swidler, Steve, 2023. "Abnormal trading volume, news and market efficiency: Evidence from the Jamaica Stock Exchange," Research in International Business and Finance, Elsevier, vol. 64(C).
    7. Mohamed S. Ahmed & John A. Doukas, 2021. "Revisiting disposition effect and momentum: a quantile regression perspective," Review of Quantitative Finance and Accounting, Springer, vol. 56(3), pages 1087-1128, April.

  21. Buu‐Chau Truong & Cathy W. S. Chen & Mike K. P. So, 2016. "Model selection of a switching mechanism for financial time series," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 32(6), pages 836-851, November.

    Cited by:

    1. Cathy W. S. Chen & Hong Than-Thi & Manabu Asai, 2021. "On a Bivariate Hysteretic AR-GARCH Model with Conditional Asymmetry in Correlations," Computational Economics, Springer;Society for Computational Economics, vol. 58(2), pages 413-433, August.

  22. Richard Gerlach & Cathy W. S. Chen & Edward M. H. Lin, 2016. "Bayesian Assessment of Dynamic Quantile Forecasts," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 35(8), pages 751-764, December.
    See citations under working paper version above.
  23. Richard Gerlach & Cathy W. S. Chen, 2016. "Bayesian Expected Shortfall Forecasting Incorporating the Intraday Range," Journal of Financial Econometrics, Oxford University Press, vol. 14(1), pages 128-158.

    Cited by:

    1. Gerlach, Richard & Wang, Chao, 2020. "Semi-parametric dynamic asymmetric Laplace models for tail risk forecasting, incorporating realized measures," International Journal of Forecasting, Elsevier, vol. 36(2), pages 489-506.
    2. Patton, Andrew J. & Ziegel, Johanna F. & Chen, Rui, 2019. "Dynamic semiparametric models for expected shortfall (and Value-at-Risk)," Journal of Econometrics, Elsevier, vol. 211(2), pages 388-413.
    3. Kim, Dongwhan & Kang, Kyu Ho, 2021. "Conditional value-at-risk forecasts of an optimal foreign currency portfolio," International Journal of Forecasting, Elsevier, vol. 37(2), pages 838-861.
    4. Cathy W. S. Chen & Edward M. H. Lin & Tara F. J. Huang, 2022. "Bayesian quantile forecasting via the realized hysteretic GARCH model," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(7), pages 1317-1337, November.
    5. Cathy W.S. Chen & Toshiaki Watanabe, 2019. "Bayesian modeling and forecasting of Value‐at‐Risk via threshold realized volatility," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 35(3), pages 747-765, May.
    6. Chao Wang & Richard Gerlach & Qian Chen, 2018. "A Semi-parametric Realized Joint Value-at-Risk and Expected Shortfall Regression Framework," Papers 1807.02422, arXiv.org, revised Jan 2021.
    7. Chao Wang & Richard Gerlach, 2019. "Semi-parametric Realized Nonlinear Conditional Autoregressive Expectile and Expected Shortfall," Papers 1906.09961, arXiv.org.
    8. Richard Gerlach & Chao Wang, 2016. "Bayesian Semi-parametric Realized-CARE Models for Tail Risk Forecasting Incorporating Realized Measures," Papers 1612.08488, arXiv.org.
    9. Richard Gerlach & Chao Wang, 2018. "Semi-parametric Dynamic Asymmetric Laplace Models for Tail Risk Forecasting, Incorporating Realized Measures," Papers 1805.08653, arXiv.org.

  24. Chen, Cathy W.S. & Gerlach, Richard & Lin, Edward M.H., 2014. "Bayesian estimation of smoothly mixing time-varying parameter GARCH models," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 194-209.

    Cited by:

    1. Niklas Ahlgren & Alexander Back & Timo Terasvirta, 2024. "A new GARCH model with a deterministic time-varying intercept," Papers 2410.03239, arXiv.org, revised Oct 2024.
    2. Chen, Cathy W.S. & Lee, Sangyeol, 2016. "Generalized Poisson autoregressive models for time series of counts," Computational Statistics & Data Analysis, Elsevier, vol. 99(C), pages 51-67.
    3. Cathy W.S. Chen & Toshiaki Watanabe, 2019. "Bayesian modeling and forecasting of Value‐at‐Risk via threshold realized volatility," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 35(3), pages 747-765, May.
    4. Manh Cuong Dong & Cathy W. S. Chen & Sangyoel Lee & Songsak Sriboonchitta, 2019. "How Strong is the Relationship Among Gold and USD Exchange Rates? Analytics Based on Structural Change Models," Computational Economics, Springer;Society for Computational Economics, vol. 53(1), pages 343-366, January.

  25. S.T. Boris Choy & Cathy W.S. Chen & Edward M.H. Lin, 2014. "Bivariate asymmetric GARCH models with heavy tails and dynamic conditional correlations," Quantitative Finance, Taylor & Francis Journals, vol. 14(7), pages 1297-1313, July.

    Cited by:

    1. Chang, Carolyn W. & Li, Xiaodan & Lin, Edward M.H. & Yu, Min-Teh, 2018. "Systemic risk, interconnectedness, and non-core activities in Taiwan insurance industry," International Review of Economics & Finance, Elsevier, vol. 55(C), pages 273-284.
    2. Cathy W. S. Chen & Hong Than-Thi & Manabu Asai, 2021. "On a Bivariate Hysteretic AR-GARCH Model with Conditional Asymmetry in Correlations," Computational Economics, Springer;Society for Computational Economics, vol. 58(2), pages 413-433, August.
    3. Thanakorn Nitithumbundit & Jennifer S. K. Chan, 2020. "ECM Algorithm for Auto-Regressive Multivariate Skewed Variance Gamma Model with Unbounded Density," Methodology and Computing in Applied Probability, Springer, vol. 22(3), pages 1169-1191, September.
    4. Nitithumbundit, Thanakorn & Chan, Jennifer S.K., 2022. "Covid-19 impact on Cryptocurrencies market using Multivariate Time Series Models," The Quarterly Review of Economics and Finance, Elsevier, vol. 86(C), pages 365-375.
    5. Do, A. & Powell, R. & Yong, J. & Singh, A., 2020. "Time-varying asymmetric volatility spillover between global markets and China’s A, B and H-shares using EGARCH and DCC-EGARCH models," The North American Journal of Economics and Finance, Elsevier, vol. 54(C).

  26. Cathy Chen & Richard Gerlach, 2013. "Semi-parametric quantile estimation for double threshold autoregressive models with heteroskedasticity," Computational Statistics, Springer, vol. 28(3), pages 1103-1131, June.

    Cited by:

    1. Pfarrhofer, Michael, 2022. "Modeling tail risks of inflation using unobserved component quantile regressions," Journal of Economic Dynamics and Control, Elsevier, vol. 143(C).
    2. 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.
    3. 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.
    4. Wang, Kai Y.K. & Chen, Cathy W.S. & So, Mike K.P., 2023. "Quantile three-factor model with heteroskedasticity, skewness, and leptokurtosis," Computational Statistics & Data Analysis, Elsevier, vol. 182(C).
    5. Vahid Nassiri & Ignace Loris, 2014. "An efficient algorithm for structured sparse quantile regression," Computational Statistics, Springer, vol. 29(5), pages 1321-1343, October.
    6. Cathy Chen & Simon Lin & Philip Yu, 2012. "Smooth Transition Quantile Capital Asset Pricing Models with Heteroscedasticity," Computational Economics, Springer;Society for Computational Economics, vol. 40(1), pages 19-48, June.

  27. Cathy Chen & Feng-Chi Liu & Mike So, 2013. "Threshold variable selection of asymmetric stochastic volatility models," Computational Statistics, Springer, vol. 28(6), pages 2415-2447, December.

    Cited by:

    1. Bermudez, P. de Zea & Marín, J. Miguel & Rue, Håvard & Veiga, Helena, 2024. "Integrated nested Laplace approximations for threshold stochastic volatility models," Econometrics and Statistics, Elsevier, vol. 30(C), pages 15-35.
    2. Zea Bermudez, Patrícia de & Rue, Havard, 2021. "Integrated nested Laplace approximations for threshold stochastic volatility models," DES - Working Papers. Statistics and Econometrics. WS 31804, Universidad Carlos III de Madrid. Departamento de Estadística.
    3. P. de Zea Bermudez & J. Miguel Marín & Helena Veiga, 2020. "Data cloning estimation for asymmetric stochastic volatility models," Econometric Reviews, Taylor & Francis Journals, vol. 39(10), pages 1057-1074, November.
    4. Mao, Xiuping & Ruiz, Esther & Veiga, Helena, 2017. "Threshold stochastic volatility: Properties and forecasting," International Journal of Forecasting, Elsevier, vol. 33(4), pages 1105-1123.

  28. Cathy Chen & Shu-Yu Chen & Sangyeol Lee, 2013. "Bayesian Unit Root Test in Double Threshold Heteroskedastic Models," Computational Economics, Springer;Society for Computational Economics, vol. 42(4), pages 471-490, December.

    Cited by:

    1. Magris Martin & Iosifidis Alexandros, 2021. "Approximate Bayes factors for unit root testing," Papers 2102.10048, arXiv.org, revised Feb 2021.
    2. Vosseler, Alexander, 2016. "Bayesian model selection for unit root testing with multiple structural breaks," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 616-630.
    3. Asif Ali & Habib Ur Rahman & Adam Arian & John Sands, 2023. "Flight-to-Liquidity and Excess Stock Return: Empirical Evidence from a Dynamic Panel Model," JRFM, MDPI, vol. 16(12), pages 1-16, December.
    4. Badri Narayan Rath & Vaseem Akram, 2021. "Popularity of Unit Root Tests - A Review," Asian Economics Letters, Asia-Pacific Applied Economics Association, vol. 2(4), pages 1-5.
    5. Shyh-Wei Chen & Chi-Sheng Hsu & Cyun-Jhen Pen, 2016. "Are Inflation Rates Mean-reverting Processes? Evidence from Six Asian Countries," Journal of Economics and Management, College of Business, Feng Chia University, Taiwan, vol. 12(1), pages 119-155, February.

  29. Cathy Chen & Simon Lin & Philip Yu, 2012. "Smooth Transition Quantile Capital Asset Pricing Models with Heteroscedasticity," Computational Economics, Springer;Society for Computational Economics, vol. 40(1), pages 19-48, June.

    Cited by:

    1. Mercik, Aleksander & Słoński, Tomasz & Karaś, Marta, 2024. "Understanding crypto-asset exposure: An investigation of its impact on performance and stock sensitivity among listed companies," International Review of Financial Analysis, Elsevier, vol. 92(C).
    2. Prince Hikouatcha & Arsène Aurelien Njamen Kengdo & Hans Patrick Bidias Menik & Pierre Ghislain Tchoffo Tioyem & Tii Njivukuh Nchofoung, 2023. "Microstructure and asset pricing: An insight on African frontier stock markets," Bulletin of Economic Research, Wiley Blackwell, vol. 75(4), pages 944-987, October.
    3. Marco Bottone & Lea Petrella & Mauro Bernardi, 2021. "Unified Bayesian conditional autoregressive risk measures using the skew exponential power distribution," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 30(3), pages 1079-1107, September.
    4. Manh Cuong Dong & Cathy W. S. Chen & Manabu Asai, 2023. "Bayesian non‐linear quantile effects on modelling realized kernels," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(1), pages 981-995, January.
    5. 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.
    6. 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.
    7. MeiChi Huang, 2022. "Time‐varying roles of housing risk factors in state‐level housing markets," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(4), pages 4660-4683, October.
    8. MeiChi Huang, 2021. "Regime switches and permanent changes in impacts of housing risk factors on MSA‐level housing returns," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(1), pages 310-342, January.
    9. Cathy Chen & Richard Gerlach, 2013. "Semi-parametric quantile estimation for double threshold autoregressive models with heteroskedasticity," Computational Statistics, Springer, vol. 28(3), pages 1103-1131, June.
    10. Wang, Kai Y.K. & Chen, Cathy W.S. & So, Mike K.P., 2023. "Quantile three-factor model with heteroskedasticity, skewness, and leptokurtosis," Computational Statistics & Data Analysis, Elsevier, vol. 182(C).
    11. Derek Bunn, Arne Andresen, Dipeng Chen, Sjur Westgaard, 2016. "Analysis and Forecasting of Electricty Price Risks with Quantile Factor Models," The Energy Journal, International Association for Energy Economics, vol. 0(Number 1).

  30. Chen, Cathy W.S. & Gerlach, Richard & Hwang, Bruce B.K. & McAleer, Michael, 2012. "Forecasting Value-at-Risk using nonlinear regression quantiles and the intra-day range," International Journal of Forecasting, Elsevier, vol. 28(3), pages 557-574.
    See citations under working paper version above.
  31. Cathy W.S. Chen & Richard Gerlach & Edward M. H. Lin & W. C. W. Lee, 2012. "Bayesian Forecasting for Financial Risk Management, Pre and Post the Global Financial Crisis," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 31(8), pages 661-687, December.
    See citations under working paper version above.
  32. Lin, Edward M.H. & Chen, Cathy W.S. & Gerlach, Richard, 2012. "Forecasting volatility with asymmetric smooth transition dynamic range models," International Journal of Forecasting, Elsevier, vol. 28(2), pages 384-399.

    Cited by:

    1. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    2. Lin, Edward M.H. & Sun, Edward W. & Yu, Min-Teh, 2020. "Behavioral data-driven analysis with Bayesian method for risk management of financial services," International Journal of Production Economics, Elsevier, vol. 228(C).
    3. Chao Wang & Richard Gerlach, 2021. "A Bayesian realized threshold measurement GARCH framework for financial tail risk forecasting," Papers 2106.00288, arXiv.org, revised Oct 2022.
    4. Wang, Lu & Ma, Feng & Liu, Jing & Yang, Lin, 2020. "Forecasting stock price volatility: New evidence from the GARCH-MIDAS model," International Journal of Forecasting, Elsevier, vol. 36(2), pages 684-694.
    5. Juan Benjamín Duarte Duarte & Juan Manuel Mascare?nas Pérez-Iñigo, 2014. "Comprobación de la eficiencia débil en los principales mercados financieros latinoamericanos," Estudios Gerenciales, Universidad Icesi, November.
    6. Markus Vogl, 2022. "Quantitative modelling frontiers: a literature review on the evolution in financial and risk modelling after the financial crisis (2008–2019)," SN Business & Economics, Springer, vol. 2(12), pages 1-69, December.
    7. Wu, Xinyu & Hou, Xinmeng, 2020. "Forecasting volatility with component conditional autoregressive range model," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
    8. Fiszeder, Piotr & Fałdziński, Marcin & Molnár, Peter, 2019. "Range-based DCC models for covariance and value-at-risk forecasting," Journal of Empirical Finance, Elsevier, vol. 54(C), pages 58-76.
    9. Leandro Maciel & Fernando Gomide & Rosangela Ballini, 2014. "An Evolving Fuzzy-Garch Approach Forfinancial Volatility Modeling And Forecasting," Anais do XL Encontro Nacional de Economia [Proceedings of the 40th Brazilian Economics Meeting] 138, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics].
    10. CHEN, Cathy W.S. & WENG, Monica M.C. & WATANABE, Toshiaki & 渡部, 渡部, 2015. "Employing Bayesian Forecasting of Value-at-Risk to Determine an Appropriate Model for Risk Management," Discussion paper series HIAS-E-16, Hitotsubashi Institute for Advanced Study, Hitotsubashi University.
    11. Qu, Hui & Zhang, Yi, 2022. "Asymmetric multivariate HAR models for realized covariance matrix: A study based on volatility timing strategies," Economic Modelling, Elsevier, vol. 106(C).
    12. Chen, Cathy W.S. & Gerlach, Richard & Lin, Edward M.H., 2014. "Bayesian estimation of smoothly mixing time-varying parameter GARCH models," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 194-209.
    13. Leandro Maciel, 2012. "A Hybrid Fuzzy GJR-GARCH Modeling Approach for Stock Market Volatility Forecasting," Brazilian Review of Finance, Brazilian Society of Finance, vol. 10(3), pages 337-367.
    14. Leandro Maciel & Fernando Gomide & Rosangela Ballini, 2016. "Evolving Fuzzy-GARCH Approach for Financial Volatility Modeling and Forecasting," Computational Economics, Springer;Society for Computational Economics, vol. 48(3), pages 379-398, October.
    15. Ng, Kok Haur & Peiris, Shelton & Chan, Jennifer So-kuen & Allen, David & Ng, Kooi Huat, 2017. "Efficient modelling and forecasting with range based volatility models and its application," The North American Journal of Economics and Finance, Elsevier, vol. 42(C), pages 448-460.
    16. Wu, Xinyu & Xie, Haibin & Zhang, Huanming, 2022. "Time-varying risk aversion and renminbi exchange rate volatility: Evidence from CARR-MIDAS model," The North American Journal of Economics and Finance, Elsevier, vol. 61(C).
    17. Danyan Wen & Mengxi He & Yaojie Zhang & Yudong Wang, 2022. "Forecasting realized volatility of Chinese stock market: A simple but efficient truncated approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(2), pages 230-251, March.

  33. Chan, J.S.K. & Lam, C.P.Y. & Yu, P.L.H. & Choy, S.T.B. & Chen, C.W.S., 2012. "A Bayesian conditional autoregressive geometric process model for range data," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3006-3019.

    Cited by:

    1. Shay Kee Tan & Kok Haur Ng & Jennifer So-Kuen Chan, 2022. "Predicting Returns, Volatilities and Correlations of Stock Indices Using Multivariate Conditional Autoregressive Range and Return Models," Mathematics, MDPI, vol. 11(1), pages 1-24, December.
    2. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    3. Arnold, Richard & Chukova, Stefanka & Hayakawa, Yu & Marshall, Sarah, 2020. "Geometric-Like Processes: An Overview and Some Reliability Applications," Reliability Engineering and System Safety, Elsevier, vol. 201(C).
    4. Chan, Jennifer So Kuen & Wan, Wai Yin, 2014. "Multivariate generalized Poisson geometric process model with scale mixtures of normal distributions," Journal of Multivariate Analysis, Elsevier, vol. 127(C), pages 72-87.
    5. Wu, Xinyu & Hou, Xinmeng, 2020. "Forecasting volatility with component conditional autoregressive range model," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
    6. Tan, Shay-Kee & Ng, Kok-Haur & Chan, Jennifer So-Kuen & Mohamed, Ibrahim, 2019. "Quantile range-based volatility measure for modelling and forecasting volatility using high frequency data," The North American Journal of Economics and Finance, Elsevier, vol. 47(C), pages 537-551.
    7. Chan Jennifer So Kuen & Ng Kok-Haur & Nitithumbundit Thanakorn & Peiris Shelton, 2019. "Efficient estimation of financial risk by regressing the quantiles of parametric distributions: An application to CARR models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 23(2), pages 1-22, April.
    8. Ng, Kok Haur & Peiris, Shelton & Chan, Jennifer So-kuen & Allen, David & Ng, Kooi Huat, 2017. "Efficient modelling and forecasting with range based volatility models and its application," The North American Journal of Economics and Finance, Elsevier, vol. 42(C), pages 448-460.

  34. Cathy W. S. Chen & Richard H. Gerlach & Ann M. H. Lin, 2011. "Multi-regime nonlinear capital asset pricing models," Quantitative Finance, Taylor & Francis Journals, vol. 11(9), pages 1421-1438, April.

    Cited by:

    1. Arısoy, Yakup Eser & Altay-Salih, Aslıhan & Akdeniz, Levent, 2015. "Aggregate volatility expectations and threshold CAPM," The North American Journal of Economics and Finance, Elsevier, vol. 34(C), pages 231-253.
    2. 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.
    3. 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.
    4. Wang, Kai Y.K. & Chen, Cathy W.S. & So, Mike K.P., 2023. "Quantile three-factor model with heteroskedasticity, skewness, and leptokurtosis," Computational Statistics & Data Analysis, Elsevier, vol. 182(C).
    5. Cathy Chen & Simon Lin & Philip Yu, 2012. "Smooth Transition Quantile Capital Asset Pricing Models with Heteroscedasticity," Computational Economics, Springer;Society for Computational Economics, vol. 40(1), pages 19-48, June.
    6. Hu, May & Muhammad, Abdul & Yang, Jingjing, 2022. "Ownership concentration, modified audit opinion, and auditor switch: New evidence and method," The North American Journal of Economics and Finance, Elsevier, vol. 61(C).

  35. Cathy Chen & Feng Liu & Richard Gerlach, 2011. "Bayesian subset selection for threshold autoregressive moving-average models," Computational Statistics, Springer, vol. 26(1), pages 1-30, March.

    Cited by:

    1. Ayman A. Amin & Walid Emam & Yusra Tashkandy & Christophe Chesneau, 2023. "Bayesian Subset Selection of Seasonal Autoregressive Models," Mathematics, MDPI, vol. 11(13), pages 1-13, June.
    2. Alexander Vosseler & Enzo Weber, 2018. "Forecasting seasonal time series data: a Bayesian model averaging approach," Computational Statistics, Springer, vol. 33(4), pages 1733-1765, December.
    3. Xiaobing Zheng & Kun Liang & Qiang Xia & Dabin Zhang, 2022. "Best Subset Selection for Double-Threshold-Variable Autoregressive Moving-Average Models: The Bayesian Approach," Computational Economics, Springer;Society for Computational Economics, vol. 59(3), pages 1175-1201, March.
    4. Philipp Piribauer, 2016. "Heterogeneity in spatial growth clusters," Empirical Economics, Springer, vol. 51(2), pages 659-680, September.
    5. Varun Agiwal & Jitendra Kumar, 2020. "Bayesian estimation for threshold autoregressive model with multiple structural breaks," METRON, Springer;Sapienza Università di Roma, vol. 78(3), pages 361-382, December.
    6. Jouchi Nakajima & Mike West, 2013. "Bayesian Analysis of Latent Threshold Dynamic Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 31(2), pages 151-164, April.

  36. Chen, Cathy W.S. & Chan, Jennifer S.K. & So, Mike K.P. & Lee, Kevin K.M., 2011. "Classification in segmented regression problems," Computational Statistics & Data Analysis, Elsevier, vol. 55(7), pages 2276-2287, July.

    Cited by:

    1. Shiow-Lan Gau & Jean Dieu Tapsoba & Shen-Ming Lee, 2014. "Bayesian approach for mixture models with grouped data," Computational Statistics, Springer, vol. 29(5), pages 1025-1043, October.

  37. Gerlach, Richard H. & Chen, Cathy W. S. & Chan, Nancy Y. C., 2011. "Bayesian Time-Varying Quantile Forecasting for Value-at-Risk in Financial Markets," Journal of Business & Economic Statistics, American Statistical Association, vol. 29(4), pages 481-492.
    See citations under working paper version above.
  38. Cathy W. S. Chen & Richard H. Gerlach & Ann M. H. Lin, 2010. "Falling and explosive, dormant, and rising markets via multiple‐regime financial time series models," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 26(1), pages 28-49, January.

    Cited by:

    1. Adewuyi, Adeolu O. & Wahab, Bashir A. & Adeboye, Olusegun S., 2020. "Stationarity of prices of precious and industrial metals using recent unit root methods: Implications for markets’ efficiency," Resources Policy, Elsevier, vol. 65(C).

  39. 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.

    Cited by:

    1. Yuzhi Cai & Julian Stander, 2018. "The threshold GARCH model: estimation and density forecasting for financial returns," Working Papers 2018-23, Swansea University, School of Management.
    2. Massimiliano Caporin & Rangan Gupta & Francesco Ravazzolo, 2019. "Contagion between Real Estate and Financial Markets: A Bayesian Quantile-on-Quantile Approach," Working Papers 201913, University of Pretoria, Department of Economics.
    3. Yves S. Schüler, 2014. "Asymmetric Effects of Uncertainty over the Business Cycle: A Quantile Structural Vector Autoregressive Approach," Working Paper Series of the Department of Economics, University of Konstanz 2014-02, Department of Economics, University of Konstanz.
    4. Liyuan Chen & Paola Zerilli & Christopher F Baum, 2018. "Leverage effects and stochastic volatility in spot oil returns: A Bayesian approach with VaR and CVaR applications," Boston College Working Papers in Economics 953, Boston College Department of Economics.
    5. Caporin, Massimiliano & Pelizzon, Loriana & Ravazzolo, Francesco & Rigobon, Roberto, 2015. "Measuring sovereign contagion in Europe," SAFE Working Paper Series 103, Leibniz Institute for Financial Research SAFE.
    6. Manh Cuong Dong & Cathy W. S. Chen & Manabu Asai, 2023. "Bayesian non‐linear quantile effects on modelling realized kernels," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(1), pages 981-995, January.
    7. 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.
    8. So, Mike K.P. & Chung, Ray S.W., 2015. "Statistical inference for conditional quantiles in nonlinear time series models," Journal of Econometrics, Elsevier, vol. 189(2), pages 457-472.
    9. 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.
    10. Wen Chang, Hao & Chang, Tsangyao, 2023. "How oil price and exchange rate affect stock price in China using Bayesian Quantile_on_Quantile with GARCH approach," The North American Journal of Economics and Finance, Elsevier, vol. 64(C).
    11. Cathy Chen & Richard Gerlach, 2013. "Semi-parametric quantile estimation for double threshold autoregressive models with heteroskedasticity," Computational Statistics, Springer, vol. 28(3), pages 1103-1131, June.
    12. Wang, Kai Y.K. & Chen, Cathy W.S. & So, Mike K.P., 2023. "Quantile three-factor model with heteroskedasticity, skewness, and leptokurtosis," Computational Statistics & Data Analysis, Elsevier, vol. 182(C).
    13. Dong, Manh Cuong & Tian, Shaonan & Chen, Cathy W.S., 2018. "Predicting failure risk using financial ratios: Quantile hazard model approach," The North American Journal of Economics and Finance, Elsevier, vol. 44(C), pages 204-220.
    14. Vahid Nassiri & Ignace Loris, 2014. "An efficient algorithm for structured sparse quantile regression," Computational Statistics, Springer, vol. 29(5), pages 1321-1343, October.
    15. Cathy Chen & Simon Lin & Philip Yu, 2012. "Smooth Transition Quantile Capital Asset Pricing Models with Heteroscedasticity," Computational Economics, Springer;Society for Computational Economics, vol. 40(1), pages 19-48, June.
    16. Schüler, Yves S., 2020. "The impact of uncertainty and certainty shocks," Discussion Papers 14/2020, Deutsche Bundesbank.

  40. Cathy W. S. Chen & Mike K. P. So & Edward M. H. Lin, 2009. "Volatility forecasting with double Markov switching GARCH models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 28(8), pages 681-697.

    Cited by:

    1. Kuang-Liang Chang & Charles Ka Yui Leung, 2021. "How did the asset markets change after the Global Financial Crisis?," GRU Working Paper Series GRU_2021_004, City University of Hong Kong, Department of Economics and Finance, Global Research Unit.
    2. David Ardia & Lennart F. Hoogerheide, 2010. "Efficient Bayesian Estimation and Combination of GARCH-Type Models," Tinbergen Institute Discussion Papers 10-046/4, Tinbergen Institute.
    3. Maciej Augustyniak & Mathieu Boudreault & Manuel Morales, 2018. "Maximum Likelihood Estimation of the Markov-Switching GARCH Model Based on a General Collapsing Procedure," Methodology and Computing in Applied Probability, Springer, vol. 20(1), pages 165-188, March.
    4. Bagher Adabi & Mohsen Mehrara & Shapour Mohammadi, 2015. "Evaluation Approaches of Value at Risk for Tehran Stock Exchange," Iranian Economic Review (IER), Faculty of Economics,University of Tehran.Tehran,Iran, vol. 19(1), pages 41-62, Winter.
    5. Halkos, George & Tzirivis, Apostolos, 2018. "Effective energy commodities’ risk management: Econometric modeling of price volatility," MPRA Paper 90781, University Library of Munich, Germany.
    6. Marco Bottone & Lea Petrella & Mauro Bernardi, 2021. "Unified Bayesian conditional autoregressive risk measures using the skew exponential power distribution," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 30(3), pages 1079-1107, September.
    7. Marius Galabe Sampid & Haslifah M Hasim & Hongsheng Dai, 2018. "Refining value-at-risk estimates using a Bayesian Markov-switching GJR-GARCH copula-EVT model," PLOS ONE, Public Library of Science, vol. 13(6), pages 1-33, June.
    8. Cifter, Atilla, 2012. "Volatility Forecasting with Asymmetric Normal Mixture Garch Model: Evidence from South Africa," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(2), pages 127-142, June.
    9. Haas Markus, 2010. "Skew-Normal Mixture and Markov-Switching GARCH Processes," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 14(4), pages 1-56, September.
    10. Funke, Michael & Shu, Chang & Cheng, Xiaoqiang & Eraslan, Sercan, 2015. "Assessing the CNH–CNY pricing differential: Role of fundamentals, contagion and policy," Journal of International Money and Finance, Elsevier, vol. 59(C), pages 245-262.
    11. Liu, Hsiang-Hsi & Chuang, Wen-I & Huang, Jih-Jeng & Chen, Yu-Hao, 2016. "The overconfident trading behavior of individual versus institutional investors," International Review of Economics & Finance, Elsevier, vol. 45(C), pages 518-539.
    12. S.T. Boris Choy & Cathy W.S. Chen & Edward M.H. Lin, 2014. "Bivariate asymmetric GARCH models with heavy tails and dynamic conditional correlations," Quantitative Finance, Taylor & Francis Journals, vol. 14(7), pages 1297-1313, July.
    13. Pierre-Julien Trombe & Pierre Pinson & Henrik Madsen, 2012. "A General Probabilistic Forecasting Framework for Offshore Wind Power Fluctuations," Energies, MDPI, vol. 5(3), pages 1-37, March.
    14. Liang, Chao & Li, Yan & Ma, Feng & Wei, Yu, 2021. "Global equity market volatilities forecasting: A comparison of leverage effects, jumps, and overnight information," International Review of Financial Analysis, Elsevier, vol. 75(C).
    15. Chang, Kuang-Liang, 2012. "Volatility regimes, asymmetric basis effects and forecasting performance: An empirical investigation of the WTI crude oil futures market," Energy Economics, Elsevier, vol. 34(1), pages 294-306.
    16. Liu, Qingfu & Wong, Ieokhou & An, Yunbi & Zhang, Jinqing, 2014. "Asymmetric Information and Volatility Forecasting in Commodity Futures Markets," Pacific-Basin Finance Journal, Elsevier, vol. 26(C), pages 79-97.
    17. Virbickaitė, Audronė & Ausín, M. Concepción & Galeano, Pedro, 2020. "Copula stochastic volatility in oil returns: Approximate Bayesian computation with volatility prediction," Energy Economics, Elsevier, vol. 92(C).

  41. Chen, Cathy W.S. & Gerlach, Richard & Cheng, Nick Y.P. & Yang, Y.L., 2009. "The impact of structural breaks on the integration of the ASEAN-5 stock markets," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 79(8), pages 2654-2664.

    Cited by:

    1. Kose, Nezir & Emirmahmutoglu, Furkan & Aksoy, Sezgin, 2012. "The interest rate–inflation relationship under an inflation targeting regime: The case of Turkey," Journal of Asian Economics, Elsevier, vol. 23(4), pages 476-485.
    2. Qin, Ruibing & Tian, Zheng & Jin, Hao & Zhang, Xiaowei, 2010. "Strong convergence rate of robust estimator of change point," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 80(10), pages 2026-2032.
    3. Chien, Mei-Se & Lee, Chien-Chiang & Hu, Te-Chung & Hu, Hui-Ting, 2015. "Dynamic Asian stock market convergence: Evidence from dynamic cointegration analysis among China and ASEAN-5," Economic Modelling, Elsevier, vol. 51(C), pages 84-98.
    4. Prukumpai, Suthawan & Sethapramote, Yuthana, 2018. "Stock Market Integration in the ASEAN-5," Asian Journal of Applied Economics/ Applied Economics Journal, Kasetsart University, Faculty of Economics, Center for Applied Economic Research, vol. 25(1), pages 15-34, June.
    5. Rahman, Md. Saifur & Shahari, Farihana, 2017. "The nexus between financial integration and real economy: Solow-growth model concept," Research in International Business and Finance, Elsevier, vol. 42(C), pages 1244-1253.
    6. Dinh, Dung V. & Powell, Robert J. & Vo, Duc H., 2021. "Forecasting corporate financial distress in the Southeast Asian countries: A market-based approach," Journal of Asian Economics, Elsevier, vol. 74(C).
    7. Allen, David E. & Gao, Jiti & McAleer, Michael, 2009. "Modelling and managing financial risk: An overview," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 79(8), pages 2521-2524.
    8. Kang, Sang Hoon & Uddin, Gazi Salah & Troster, Victor & Yoon, Seong-Min, 2019. "Directional spillover effects between ASEAN and world stock markets," Journal of Multinational Financial Management, Elsevier, vol. 52.

  42. Lai, YiHao & Chen, Cathy W.S. & Gerlach, Richard, 2009. "Optimal dynamic hedging via copula-threshold-GARCH models," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 79(8), pages 2609-2624.

    Cited by:

    1. Chang, Kuang-Liang, 2012. "The time-varying and asymmetric dependence between crude oil spot and futures markets: Evidence from the Mixture copula-based ARJI–GARCH model," Economic Modelling, Elsevier, vol. 29(6), pages 2298-2309.
    2. Jin Zhang & Dietmar Maringer, 2010. "Asset Pair-Copula Selection with Downside Risk Minimization," Working Papers 037, COMISEF.
    3. Wei, Yu & Wang, Yudong & Huang, Dengshi, 2011. "A copula–multifractal volatility hedging model for CSI 300 index futures," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(23), pages 4260-4272.
    4. Janani Sri S. & Parthajit Kayal & G. Balasubramanian, 2022. "Can Equity be Safe-haven for Investment?," Journal of Emerging Market Finance, Institute for Financial Management and Research, vol. 21(1), pages 32-63, March.
    5. Qu, Hui & Wang, Tianyang & Zhang, Yi & Sun, Pengfei, 2019. "Dynamic hedging using the realized minimum-variance hedge ratio approach – Examination of the CSI 300 index futures," Pacific-Basin Finance Journal, Elsevier, vol. 57(C).
    6. Ahmed Ghorbel & Abdelwahed Trabelsi, 2012. "Optimal dynamic hedging strategy with futures oil markets via FIEGARCH-EVT copula models," International Journal of Managerial and Financial Accounting, Inderscience Enterprises Ltd, vol. 4(1), pages 1-28.
    7. Chia-Hsun Hsieh & Shian-Chang Huang, 2012. "Time-Varying Dependency and Structural Changes in Currency Markets," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 48(2), pages 94-127, March.
    8. Teresa Serra & José M. Gil, 2013. "Price volatility in food markets: can stock building mitigate price fluctuations?," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 40(3), pages 507-528, July.
    9. Wenming Shi & Kevin X. Li & Zhongzhi Yang & Ganggang Wang, 2017. "Time-varying copula models in the shipping derivatives market," Empirical Economics, Springer, vol. 53(3), pages 1039-1058, November.
    10. Serra, Teresa & Gil, José M., 2012. "Biodiesel as a motor fuel price stabilization mechanism," Energy Policy, Elsevier, vol. 50(C), pages 689-698.
    11. Lai, YiHao & Tseng, Jen-Ching, 2010. "The role of Chinese stock market in global stock markets: A safe haven or a hedge?," International Review of Economics & Finance, Elsevier, vol. 19(2), pages 211-218, April.
    12. Serra, Teresa, 2011. "Volatility spillovers between food and energy markets: A semiparametric approach," Energy Economics, Elsevier, vol. 33(6), pages 1155-1164.
    13. Jin Seo Cho & Peter C. B. Phillips & Juwon Seo, 2019. "Parametric Inference on the Mean of Functional Data Applied to Lifetime Income Curves," Working papers 2019rwp-153, Yonsei University, Yonsei Economics Research Institute.
    14. Bai, Xiwen & Kavussanos, Manolis G., 2022. "Hedging IMO2020 compliant fuel price exposure using futures contracts," Energy Economics, Elsevier, vol. 110(C).
    15. Zhiyuan Pan & Xianchao Sun, 2014. "Hedging Strategy Using Copula and Nonparametric Methods: Evidence from China Securities Index Futures," International Journal of Economics and Financial Issues, Econjournals, vol. 4(1), pages 107-121.
    16. Tehrani , Reza & Veisizadeh , Vahid, 2021. "Dynamic Cross Hedging Effectiveness between Gold and Stock Market Based on Downside Risk Measures: Evidence from Iran Emerging Capital Market," Journal of Money and Economy, Monetary and Banking Research Institute, Central Bank of the Islamic Republic of Iran, vol. 16(1), pages 43-70, March.
    17. Kunlapath Sukcharoen & Hankyeung Choi & David J. Leatham, 2015. "Optimal gasoline hedging strategies using futures contracts and exchange-traded funds," Applied Economics, Taylor & Francis Journals, vol. 47(32), pages 3482-3498, July.
    18. Jin Seo Cho & Peter C. B. Phillips & Juwon Seo, 2022. "Parametric Conditional Mean Inference With Functional Data Applied To Lifetime Income Curves," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 63(1), pages 391-456, February.
    19. Zied Ftiti & Kais Tissaoui & Sahbi Boubaker, 2022. "On the relationship between oil and gas markets: a new forecasting framework based on a machine learning approach," Annals of Operations Research, Springer, vol. 313(2), pages 915-943, June.
    20. Gang-Jin Wang & Chi Xie & Peng Zhang & Feng Han & Shou Chen, 2014. "Dynamics of Foreign Exchange Networks: A Time-Varying Copula Approach," Discrete Dynamics in Nature and Society, Hindawi, vol. 2014, pages 1-11, May.
    21. Gong, Yuting & Li, Kevin X. & Chen, Shu-Ling & Shi, Wenming, 2020. "Contagion risk between the shipping freight and stock markets: Evidence from the recent US-China trade war," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 136(C).
    22. YiHao Lai, 2008. "Does Asymmetric Dependence Structure Matter? A Value-at-Risk View," International Journal of Business and Economics, School of Management Development, Feng Chia University, Taichung, Taiwan, vol. 7(3), pages 249-268, December.
    23. Chen, Yi-Hsuan & Tu, Anthony H., 2013. "Estimating hedged portfolio value-at-risk using the conditional copula: An illustration of model risk," International Review of Economics & Finance, Elsevier, vol. 27(C), pages 514-528.
    24. Allen, David E. & Gao, Jiti & McAleer, Michael, 2009. "Modelling and managing financial risk: An overview," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 79(8), pages 2521-2524.
    25. Penikas, Henry, 2011. "Copula-Based Price Risk Hedging Models," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 22(2), pages 3-21.
    26. Parthajit Kayal & Janani Sri SG, 2020. "Going Beyond Gold: Can Equities be Safe-Haven?," Working Papers 2020-203, Madras School of Economics,Chennai,India.
    27. Penikas, H., 2010. "Financial Applications of Copula-Models," Journal of the New Economic Association, New Economic Association, issue 7, pages 24-44.
    28. Chang, Kuang-Liang, 2014. "The symmetrical and positive relationship between crude oil and nominal exchange rate returns," The North American Journal of Economics and Finance, Elsevier, vol. 29(C), pages 266-284.

  43. So, Mike K.P. & Chen, Cathy W.S. & Lee, Jen-Yu & Chang, Yi-Ping, 2008. "An empirical evaluation of fat-tailed distributions in modeling financial time series," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 77(1), pages 96-108.

    Cited by:

    1. Jiang, Chun-Fu & Peng, Hong-Yi & Yang, Yu-Kuan, 2016. "Tail variance of portfolio under generalized Laplace distribution," Applied Mathematics and Computation, Elsevier, vol. 282(C), pages 187-203.
    2. Huang, Alex YiHou, 2010. "An optimization process in Value-at-Risk estimation," Review of Financial Economics, Elsevier, vol. 19(3), pages 109-116, August.
    3. Kostas Andriosopoulos & Nikos Nomikos, 2012. "Risk management in the energy markets and Value-at-Risk modelling: a Hybrid approach," RSCAS Working Papers 2012/47, European University Institute.
    4. Cerqueti, Roy & Giacalone, Massimiliano & Panarello, Demetrio, 2019. "A Generalized Error Distribution Copula-based method for portfolios risk assessment," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 524(C), pages 687-695.

  44. Chen, Cathy W.S. & Gerlach, Richard & Lin, Edward M.H., 2008. "Volatility forecasting using threshold heteroskedastic models of the intra-day range," Computational Statistics & Data Analysis, Elsevier, vol. 52(6), pages 2990-3010, February.

    Cited by:

    1. S. Bordignon & D. Raggi, 2010. "Long memory and nonlinearities in realized volatility: a Markov switching approach," Working Papers 694, Dipartimento Scienze Economiche, Universita' di Bologna.
    2. Yuta Kurose, 2021. "Stochastic volatility model with range-based correction and leverage," Papers 2110.00039, arXiv.org, revised Oct 2021.
    3. Cathy W. S. Chen & Richard Gerlach & Bruce B. K. Hwang & Michael McAleer, 2011. "Forecasting Value-at-Risk Using Nonlinear Regression Quantiles and the Intra-day Range," KIER Working Papers 775, Kyoto University, Institute of Economic Research.
    4. Liang-Ching Lin & Li-Hsien Sun, 2019. "Modeling financial interval time series," PLOS ONE, Public Library of Science, vol. 14(2), pages 1-20, February.
    5. Godfrey Marozva & Margaret Rutendo Magwedere, 2017. "Macroeconomic Variables, Leverage, Stock Returns and Stock Return Volatility," Acta Universitatis Danubius. OEconomica, Danubius University of Galati, issue 13(4), pages 264-288, AUGUST.
    6. Shay Kee Tan & Kok Haur Ng & Jennifer So-Kuen Chan, 2022. "Predicting Returns, Volatilities and Correlations of Stock Indices Using Multivariate Conditional Autoregressive Range and Return Models," Mathematics, MDPI, vol. 11(1), pages 1-24, December.
    7. Tsiotas, Georgios, 2012. "On generalised asymmetric stochastic volatility models," Computational Statistics & Data Analysis, Elsevier, vol. 56(1), pages 151-172, January.
    8. Charles, Amélie, 2010. "The day-of-the-week effects on the volatility: The role of the asymmetry," European Journal of Operational Research, Elsevier, vol. 202(1), pages 143-152, April.
    9. Chen, Qian & Gerlach, Richard H., 2013. "The two-sided Weibull distribution and forecasting financial tail risk," International Journal of Forecasting, Elsevier, vol. 29(4), pages 527-540.
    10. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    11. Piotr Fiszeder & Marta Ma³ecka, 2022. "Forecasting volatility during the outbreak of Russian invasion of Ukraine: application to commodities, stock indices, currencies, and cryptocurrencies," Equilibrium. Quarterly Journal of Economics and Economic Policy, Institute of Economic Research, vol. 17(4), pages 939-967, December.
    12. Chao Wang & Richard Gerlach, 2021. "A Bayesian realized threshold measurement GARCH framework for financial tail risk forecasting," Papers 2106.00288, arXiv.org, revised Oct 2022.
    13. Bagher Adabi & Mohsen Mehrara & Shapour Mohammadi, 2015. "Evaluation Approaches of Value at Risk for Tehran Stock Exchange," Iranian Economic Review (IER), Faculty of Economics,University of Tehran.Tehran,Iran, vol. 19(1), pages 41-62, Winter.
    14. Fiszeder, Piotr & Fałdziński, Marcin & Molnár, Peter, 2023. "Modeling and forecasting dynamic conditional correlations with opening, high, low, and closing prices," Journal of Empirical Finance, Elsevier, vol. 70(C), pages 308-321.
    15. Richard Gerlach & Chao Wang, 2016. "Forecasting risk via realized GARCH, incorporating the realized range," Quantitative Finance, Taylor & Francis Journals, vol. 16(4), pages 501-511, April.
    16. Isuru Ratnayake & V. A. Samaranayake, 2022. "Threshold Asymmetric Conditional Autoregressive Range (TACARR) Model," Papers 2202.03351, arXiv.org, revised Mar 2022.
    17. Yuta Kurose, 2022. "Bayesian GARCH modeling for return and range," Economics Bulletin, AccessEcon, vol. 42(3), pages 1717-1727.
    18. Tan, Shay-Kee & Ng, Kok-Haur & Chan, Jennifer So-Kuen & Mohamed, Ibrahim, 2019. "Quantile range-based volatility measure for modelling and forecasting volatility using high frequency data," The North American Journal of Economics and Finance, Elsevier, vol. 47(C), pages 537-551.
    19. Haase, Marco & Huss, Matthias, 2018. "Guilty speculators? Range-based conditional volatility in a cross-section of wheat futures," Journal of Commodity Markets, Elsevier, vol. 10(C), pages 29-46.
    20. Borovkova, Svetlana & Permana, Ferry J., 2009. "Implied volatility in oil markets," Computational Statistics & Data Analysis, Elsevier, vol. 53(6), pages 2022-2039, April.
    21. Ng, Kok Haur & Peiris, Shelton & Chan, Jennifer So-kuen & Allen, David & Ng, Kooi Huat, 2017. "Efficient modelling and forecasting with range based volatility models and its application," The North American Journal of Economics and Finance, Elsevier, vol. 42(C), pages 448-460.
    22. Chan, J.S.K. & Lam, C.P.Y. & Yu, P.L.H. & Choy, S.T.B. & Chen, C.W.S., 2012. "A Bayesian conditional autoregressive geometric process model for range data," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3006-3019.
    23. Wu, Xinyu & Xie, Haibin & Zhang, Huanming, 2022. "Time-varying risk aversion and renminbi exchange rate volatility: Evidence from CARR-MIDAS model," The North American Journal of Economics and Finance, Elsevier, vol. 61(C).
    24. Richard Gerlach & Declan Walpole & Chao Wang, 2017. "Semi-parametric Bayesian tail risk forecasting incorporating realized measures of volatility," Quantitative Finance, Taylor & Francis Journals, vol. 17(2), pages 199-215, February.

  45. Chen, Cathy W.S. & Gerlach, Richard H. & Tai, Amanda P.J., 2008. "Testing for nonlinearity in mean and volatility for heteroskedastic models," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 79(3), pages 489-499.

    Cited by:

    1. Ledermann, Daniel & Alexander, Carol, 2012. "Further properties of random orthogonal matrix simulation," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 83(C), pages 56-79.

  46. Mike K. P. So & Cathy W. S. Chen & Thomas C. Chiang & Doris S. Y. Lin, 2007. "Modelling financial time series with threshold nonlinearity in returns and trading volume," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 23(4), pages 319-338, July.

    Cited by:

    1. Mike K. P. So & C. Y. Choi, 2009. "A threshold factor multivariate stochastic volatility model," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 28(8), pages 712-735.

  47. Thomas C. Chiang & Cathy W.S. Chen & Mike K.P. So, 2007. "Asymmetric Return and Volatility Responses to Composite News from Stock Markets," Multinational Finance Journal, Multinational Finance Journal, vol. 11(3-4), pages 179-210, September.

    Cited by:

    1. Xiangnan Meng & Xin Deng, 2013. "Interest Rate and Foreign Exchange Sensitivity of Bank Stock Returns: Evidence from China," Multinational Finance Journal, Multinational Finance Journal, vol. 17(1-2), pages 77-106, March - J.
    2. Cathy W. S. Chen & Bonny Lee, 2021. "Bayesian inference of multiple structural change models with asymmetric GARCH errors," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 30(3), pages 1053-1078, September.
    3. Aityan, Sergey K. & Ivanov-Schitz, Alexey K. & Izotov, Sergey S., 2010. "Time-shift asymmetric correlation analysis of global stock markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 20(5), pages 590-605, December.
    4. Thomas Chiang & Lin Tan & Jiandong Li & Edward Nelling, 2013. "Dynamic Herding Behavior in Pacific-Basin Markets: Evidence and Implications," Multinational Finance Journal, Multinational Finance Journal, vol. 17(3-4), pages 165-200, September.

  48. Mike K. P. So & Cathy W. S. Chen & Feng‐Chi Liu, 2006. "Best subset selection of autoregressive models with exogenous variables and generalized autoregressive conditional heteroscedasticity errors," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 55(2), pages 201-224, April.

    Cited by:

    1. Søren Johansen & Marco Riani & Anthony C. Atkinson, 2012. "The Selection of ARIMA Models with or without Regressors," CREATES Research Papers 2012-46, Department of Economics and Business Economics, Aarhus University.
    2. Ayman A. Amin & Walid Emam & Yusra Tashkandy & Christophe Chesneau, 2023. "Bayesian Subset Selection of Seasonal Autoregressive Models," Mathematics, MDPI, vol. 11(13), pages 1-13, June.
    3. Alexander Vosseler & Enzo Weber, 2018. "Forecasting seasonal time series data: a Bayesian model averaging approach," Computational Statistics, Springer, vol. 33(4), pages 1733-1765, December.
    4. Yip, Iris W.H. & So, Mike K.P., 2009. "Simplified specifications of a multivariate generalized autoregressive conditional heteroscedasticity model," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 80(2), pages 327-340.
    5. Rodolfo Angelo Magtanggol Iii De Guzman & Mike K. P. So, 2018. "Empirical Analysis Of Bitcoin Prices Using Threshold Time Series Models," Annals of Financial Economics (AFE), World Scientific Publishing Co. Pte. Ltd., vol. 13(04), pages 1-24, December.

  49. Chen, Cathy W.S. & Yang, Ming Jing & Gerlach, Richard & Jim Lo, H., 2006. "The asymmetric reactions of mean and volatility of stock returns to domestic and international information based on a four-regime double-threshold GARCH model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 366(C), pages 401-418.

    Cited by:

    1. Yang, Yung-Lieh & Chang, Chia-Lin, 2008. "A double-threshold GARCH model of stock market and currency shocks on stock returns," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 79(3), pages 458-474.
    2. Kang, Sang Hoon & Cheong, Chongcheul & Yoon, Seong-Min, 2011. "Structural changes and volatility transmission in crude oil markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(23), pages 4317-4324.
    3. Kushal Banik Chowdhury & Nityananda Sarkar, 2015. "The Effect of Inflation on Inflation Uncertainty in the G7 Countries: A Double Threshold GARCH Model," International Econometric Review (IER), Econometric Research Association, vol. 7(1), pages 34-50, April.
    4. Piotr Wdowinski & Marta Malecka, 2010. "Asymmetry in Volatility: A Comparison of Developed and Transition Stock Markets," CESifo Working Paper Series 2974, CESifo.
    5. Liu, Hsiang-Hsi & Chuang, Wen-I & Huang, Jih-Jeng & Chen, Yu-Hao, 2016. "The overconfident trading behavior of individual versus institutional investors," International Review of Economics & Finance, Elsevier, vol. 45(C), pages 518-539.
    6. Lahmiri, Salim, 2017. "Asymmetric and persistent responses in price volatility of fertilizers through stable and unstable periods," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 466(C), pages 405-414.
    7. Wei, Yu, 2012. "Forecasting volatility of fuel oil futures in China: GARCH-type, SV or realized volatility models?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(22), pages 5546-5556.

  50. Chen, Cathy W.S. & Gerlach, Richard & So, Mike K.P., 2006. "Comparison of nonnested asymmetric heteroskedastic models," Computational Statistics & Data Analysis, Elsevier, vol. 51(4), pages 2164-2178, December.

    Cited by:

    1. Chen, Cathy W.S. & Gerlach, Richard H. & Tai, Amanda P.J., 2008. "Testing for nonlinearity in mean and volatility for heteroskedastic models," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 79(3), pages 489-499.
    2. David Ardia & Lennart F. Hoogerheide, 2010. "Efficient Bayesian Estimation and Combination of GARCH-Type Models," Tinbergen Institute Discussion Papers 10-046/4, Tinbergen Institute.
    3. Charles, Amélie, 2010. "The day-of-the-week effects on the volatility: The role of the asymmetry," European Journal of Operational Research, Elsevier, vol. 202(1), pages 143-152, April.
    4. Mike K. P. So & C. Y. Choi, 2009. "A threshold factor multivariate stochastic volatility model," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 28(8), pages 712-735.
    5. Cathy W. S. Chen & Richard H. Gerlach & Ann M. H. Lin, 2011. "Multi-regime nonlinear capital asset pricing models," Quantitative Finance, Taylor & Francis Journals, vol. 11(9), pages 1421-1438, April.
    6. Chen, Cathy W.S. & Gerlach, Richard & Lin, Edward M.H., 2008. "Volatility forecasting using threshold heteroskedastic models of the intra-day range," Computational Statistics & Data Analysis, Elsevier, vol. 52(6), pages 2990-3010, February.
    7. Amendola, Alessandra & Storti, Giuseppe, 2008. "A GMM procedure for combining volatility forecasts," Computational Statistics & Data Analysis, Elsevier, vol. 52(6), pages 3047-3060, February.
    8. Cathy Chen & Feng-Chi Liu & Mike So, 2013. "Threshold variable selection of asymmetric stochastic volatility models," Computational Statistics, Springer, vol. 28(6), pages 2415-2447, December.
    9. Cathy W. S. Chen & Richard H. Gerlach & Ann M. H. Lin, 2010. "Falling and explosive, dormant, and rising markets via multiple‐regime financial time series models," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 26(1), pages 28-49, January.
    10. María José Rodríguez & Esther Ruiz, 2012. "Revisiting Several Popular GARCH Models with Leverage Effect: Differences and Similarities," Journal of Financial Econometrics, Oxford University Press, vol. 10(4), pages 637-668, September.
    11. Richard Gerlach & Chao Wang, 2016. "Forecasting risk via realized GARCH, incorporating the realized range," Quantitative Finance, Taylor & Francis Journals, vol. 16(4), pages 501-511, April.
    12. Alicia Pérez Alonso, 2006. "A Bootstrap Approach To Test The Conditional Symmetry In Time Series Models," Working Papers. Serie AD 2006-18, Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie).
    13. Cathy Chen & Richard Gerlach, 2013. "Semi-parametric quantile estimation for double threshold autoregressive models with heteroskedasticity," Computational Statistics, Springer, vol. 28(3), pages 1103-1131, June.
    14. Chen, Cathy W.S. & Watanabe, Toshiaki & Lin, Edward M.H., 2023. "Bayesian estimation of realized GARCH-type models with application to financial tail risk management," Econometrics and Statistics, Elsevier, vol. 28(C), pages 30-46.
    15. Chao Wang & Qian Chen & Richard Gerlach, 2017. "Bayesian Realized-GARCH Models for Financial Tail Risk Forecasting Incorporating Two-sided Weibull Distribution," Papers 1707.03715, arXiv.org.
    16. Vica Tendenan & Richard Gerlach & Chao Wang, 2020. "Tail risk forecasting using Bayesian realized EGARCH models," Papers 2008.05147, arXiv.org, revised Aug 2020.
    17. Hsu-Ling Chang & Chi-Wei Su, 2010. "The relationship between the Vietnam stock market and its major trading partners - TECM with bivariate asymmetric GARCH model," Applied Economics Letters, Taylor & Francis Journals, vol. 17(13), pages 1279-1283.
    18. Lin, Edward M.H. & Chen, Cathy W.S. & Gerlach, Richard, 2012. "Forecasting volatility with asymmetric smooth transition dynamic range models," International Journal of Forecasting, Elsevier, vol. 28(2), pages 384-399.
    19. Cathy Chen & Simon Lin & Philip Yu, 2012. "Smooth Transition Quantile Capital Asset Pricing Models with Heteroscedasticity," Computational Economics, Springer;Society for Computational Economics, vol. 40(1), pages 19-48, June.
    20. Broda, Simon & Paolella, Marc S., 2007. "Saddlepoint approximations for the doubly noncentral t distribution," Computational Statistics & Data Analysis, Elsevier, vol. 51(6), pages 2907-2918, March.
    21. Gerlach, Richard & Abeywardana, Sachin, 2016. "Variational Bayes for assessment of dynamic quantile forecasts," International Journal of Forecasting, Elsevier, vol. 32(4), pages 1385-1402.
    22. Liu, Xiaochun & Luger, Richard, 2015. "Unfolded GARCH models," Journal of Economic Dynamics and Control, Elsevier, vol. 58(C), pages 186-217.

  51. Gerlach, Richard & Chen, Cathy W.S. & Lin, Doris S.Y. & Huang, Ming-Hsiang, 2006. "Asymmetric responses of international stock markets to trading volume," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 360(2), pages 422-444.

    Cited by:

    1. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    2. Ralf Brüggemann & Markus Glaser & Stefan Schaarschmidt & Sandra Stankiewicz, 2014. "The Stock Return - Trading Volume Relationship in European Countries: Evidence from Asymmetric Impulse Responses," Working Paper Series of the Department of Economics, University of Konstanz 2014-24, Department of Economics, University of Konstanz.
    3. Chuang, Wen-I & Liu, Hsiang-Hsi & Susmel, Rauli, 2012. "The bivariate GARCH approach to investigating the relation between stock returns, trading volume, and return volatility," Global Finance Journal, Elsevier, vol. 23(1), pages 1-15.
    4. Rau, Tomás & Sarzosa, Miguel & Urzúa, Sergio, 2021. "The children of the missed pill," Journal of Health Economics, Elsevier, vol. 79(C).
    5. Bartosz Gębka, 2012. "The Dynamic Relation Between Returns, Trading Volume, And Volatility: Lessons From Spillovers Between Asia And The United States," Bulletin of Economic Research, Wiley Blackwell, vol. 64(1), pages 65-90, January.
    6. Zolotoy, L., 2008. "Empirical essays on the information transfer between and the informational efficiency of stock markets," Other publications TiSEM 2a2652c6-1060-4622-8721-8, Tilburg University, School of Economics and Management.
    7. Neaime, Simon, 2016. "Financial crises and contagion vulnerability of MENA stock markets," Emerging Markets Review, Elsevier, vol. 27(C), pages 14-35.
    8. Kai-Chao Yao & Hsiu-Wen Hsueh & Ming-Hsiang Huang & Tsung-Che Wu, 2022. "The Role of GARCH Effect on the Prediction of Air Pollution," Sustainability, MDPI, vol. 14(8), pages 1-20, April.
    9. Cheng, Xixin & Li, W.K. & Yu, Philip L.H. & Zhou, Xuan & Wang, Chao & Lo, P.H., 2011. "Modeling threshold conditional heteroscedasticity with regime-dependent skewness and kurtosis," Computational Statistics & Data Analysis, Elsevier, vol. 55(9), pages 2590-2604, September.
    10. Xiaqing Su & Zhe Liu, 2021. "Sector Volatility Spillover and Economic Policy Uncertainty: Evidence from China’s Stock Market," Mathematics, MDPI, vol. 9(12), pages 1-22, June.
    11. Vespignani, Joaquin L., 2012. "Modelling asymmetric consumer demand response: Evidence from scanner data," MPRA Paper 55601, University Library of Munich, Germany.

  52. Chen, Cathy W.S. & So, Mike K.P., 2006. "On a threshold heteroscedastic model," International Journal of Forecasting, Elsevier, vol. 22(1), pages 73-89.

    Cited by:

    1. Cathy W. S. Chen & Richard Gerlach & Bruce B. K. Hwang & Michael McAleer, 2011. "Forecasting Value-at-Risk Using Nonlinear Regression Quantiles and the Intra-day Range," KIER Working Papers 775, Kyoto University, Institute of Economic Research.
    2. Chen, Cathy W.S. & Hsu, Hsiao-Yun & Watanabe, Toshiaki, 2023. "Tail risk forecasting of realized volatility CAViaR models," Finance Research Letters, Elsevier, vol. 51(C).
    3. Chen, Cathy W.S. & Gerlach, Richard H. & Tai, Amanda P.J., 2008. "Testing for nonlinearity in mean and volatility for heteroskedastic models," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 79(3), pages 489-499.
    4. Chen, Cathy W.S. & Chan, Jennifer S.K. & So, Mike K.P. & Lee, Kevin K.M., 2011. "Classification in segmented regression problems," Computational Statistics & Data Analysis, Elsevier, vol. 55(7), pages 2276-2287, July.
    5. Beg, A.B.M. Rabiul Alam & Anwar, Sajid, 2012. "Sources of volatility persistence: A case study of the U.K. pound/U.S. dollar exchange rate returns," The North American Journal of Economics and Finance, Elsevier, vol. 23(2), pages 165-184.
    6. Yang, Yung-Lieh & Chang, Chia-Lin, 2008. "A double-threshold GARCH model of stock market and currency shocks on stock returns," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 79(3), pages 458-474.
    7. So, Mike K.P. & Chan, Raymond K.S., 2014. "Bayesian analysis of tail asymmetry based on a threshold extreme value model," Computational Statistics & Data Analysis, Elsevier, vol. 71(C), pages 568-587.
    8. Chen, Cathy W.S. & Lee, Sangyeol, 2016. "Generalized Poisson autoregressive models for time series of counts," Computational Statistics & Data Analysis, Elsevier, vol. 99(C), pages 51-67.
    9. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    10. Lin, Edward M.H. & Sun, Edward W. & Yu, Min-Teh, 2020. "Behavioral data-driven analysis with Bayesian method for risk management of financial services," International Journal of Production Economics, Elsevier, vol. 228(C).
    11. Chen, Cathy W.S. & Yang, Ming Jing & Gerlach, Richard & Jim Lo, H., 2006. "The asymmetric reactions of mean and volatility of stock returns to domestic and international information based on a four-regime double-threshold GARCH model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 366(C), pages 401-418.
    12. So, Mike K.P. & Chen, Cathy W.S. & Lee, Jen-Yu & Chang, Yi-Ping, 2008. "An empirical evaluation of fat-tailed distributions in modeling financial time series," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 77(1), pages 96-108.
    13. Vosseler, Alexander, 2016. "Bayesian model selection for unit root testing with multiple structural breaks," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 616-630.
    14. Chen, Cathy W.S. & Gerlach, Richard & Lin, Edward M.H., 2008. "Volatility forecasting using threshold heteroskedastic models of the intra-day range," Computational Statistics & Data Analysis, Elsevier, vol. 52(6), pages 2990-3010, February.
    15. Liu, Xialu & Chen, Rong, 2020. "Threshold factor models for high-dimensional time series," Journal of Econometrics, Elsevier, vol. 216(1), pages 53-70.
    16. Guo, Jinggang & Johnston, Craig M.T., 2021. "Do protectionist trade policies integrate domestic markets? Evidence from the Canada-U.S. softwood lumber dispute," Forest Policy and Economics, Elsevier, vol. 130(C).
    17. Chen, Cathy W.S. & Wang, Zona & Sriboonchitta, Songsak & Lee, Sangyeol, 2017. "Pair trading based on quantile forecasting of smooth transition GARCH models," The North American Journal of Economics and Finance, Elsevier, vol. 39(C), pages 38-55.
    18. Thomas C. Chiang & Cathy W.S. Chen & Mike K.P. So, 2007. "Asymmetric Return and Volatility Responses to Composite News from Stock Markets," Multinational Finance Journal, Multinational Finance Journal, vol. 11(3-4), pages 179-210, September.
    19. So, Mike K.P. & Chan, Thomas W.C. & Chu, Amanda M.Y., 2022. "Efficient estimation of high-dimensional dynamic covariance by risk factor mapping: Applications for financial risk management," Journal of Econometrics, Elsevier, vol. 227(1), pages 151-167.
    20. Chen, Cathy W. S. & Chiang, Thomas C. & So, Mike K. P., 2003. "Asymmetrical reaction to US stock-return news: evidence from major stock markets based on a double-threshold model," Journal of Economics and Business, Elsevier, vol. 55(5-6), pages 487-502.
    21. Funke, Michael & Shu, Chang & Cheng, Xiaoqiang & Eraslan, Sercan, 2015. "Assessing the CNH–CNY pricing differential: Role of fundamentals, contagion and policy," Journal of International Money and Finance, Elsevier, vol. 59(C), pages 245-262.
    22. Yip, Iris W.H. & So, Mike K.P., 2009. "Simplified specifications of a multivariate generalized autoregressive conditional heteroscedasticity model," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 80(2), pages 327-340.
    23. Cathy W.S. Chen & Toshiaki Watanabe, 2019. "Bayesian modeling and forecasting of Value‐at‐Risk via threshold realized volatility," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 35(3), pages 747-765, May.
    24. Liu, Hsiang-Hsi & Chuang, Wen-I & Huang, Jih-Jeng & Chen, Yu-Hao, 2016. "The overconfident trading behavior of individual versus institutional investors," International Review of Economics & Finance, Elsevier, vol. 45(C), pages 518-539.
    25. Audrino, Francesco, 2014. "Forecasting correlations during the late-2000s financial crisis: The short-run component, the long-run component, and structural breaks," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 43-60.
    26. Gerlach, Richard & Tuyl, Frank, 2006. "MCMC methods for comparing stochastic volatility and GARCH models," International Journal of Forecasting, Elsevier, vol. 22(1), pages 91-107.
    27. Chen, Qian & Gerlach, Richard & Lu, Zudi, 2012. "Bayesian Value-at-Risk and expected shortfall forecasting via the asymmetric Laplace distribution," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3498-3516.
    28. Wang, Kai Y.K. & Chen, Cathy W.S. & So, Mike K.P., 2023. "Quantile three-factor model with heteroskedasticity, skewness, and leptokurtosis," Computational Statistics & Data Analysis, Elsevier, vol. 182(C).
    29. Chen, Cathy W.S. & Gerlach, Richard & Lin, Edward M.H., 2014. "Bayesian estimation of smoothly mixing time-varying parameter GARCH models," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 194-209.
    30. Zeng, Zijian & Li, Meng, 2021. "Bayesian median autoregression for robust time series forecasting," International Journal of Forecasting, Elsevier, vol. 37(2), pages 1000-1010.
    31. Lin, Edward M.H. & Chen, Cathy W.S. & Gerlach, Richard, 2012. "Forecasting volatility with asymmetric smooth transition dynamic range models," International Journal of Forecasting, Elsevier, vol. 28(2), pages 384-399.
    32. So, Mike K.P. & Choi, C.Y., 2008. "A multivariate threshold stochastic volatility model," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 79(3), pages 306-317.
    33. Yang, Yaxing & Ling, Shiqing, 2017. "Self-weighted LAD-based inference for heavy-tailed threshold autoregressive models," Journal of Econometrics, Elsevier, vol. 197(2), pages 368-381.
    34. Chen, Cathy W.S. & Liu, Feng-Chi & Pingal, Aljo Clair, 2023. "Integer-valued transfer function models for counts that show zero inflation," Statistics & Probability Letters, Elsevier, vol. 193(C).

  53. Chen, Cathy W.S. & Yu, Tiffany H.K., 2005. "Long-term dependence with asymmetric conditional heteroscedasticity in stock returns," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 353(C), pages 413-424.

    Cited by:

    1. S. Bordignon & D. Raggi, 2010. "Long memory and nonlinearities in realized volatility: a Markov switching approach," Working Papers 694, Dipartimento Scienze Economiche, Universita' di Bologna.
    2. Gomes, Luís M. P. & Soares, Vasco J. S. & Gama, Sílvio M. A. & Matos, José A. O., 2018. "Long-term memory in Euronext stock indexes returns: an econophysics approach," Business and Economic Horizons (BEH), Prague Development Center, vol. 14(4), pages 862-881, August.

  54. Cathy W. S. Chen & Mike K. P. So & Richard H. Gerlach, 2005. "Asymmetric response and interaction of U.S. and local news in financial markets," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 21(3), pages 273-288, May.

    Cited by:

    1. Cathy W. S. Chen & Sangyeol Lee & K. Khamthong, 2021. "Bayesian inference of nonlinear hysteretic integer-valued GARCH models for disease counts," Computational Statistics, Springer, vol. 36(1), pages 261-281, March.
    2. Stephen Kawas & Everton Dockery, 2023. "What do we know about the stock markets’ reaction to regulatory announcements regarding financial institutions? Evidence from UK financial institutions," Review of Quantitative Finance and Accounting, Springer, vol. 60(1), pages 31-67, January.
    3. Sun, Yuying & Han, Ai & Hong, Yongmiao & Wang, Shouyang, 2018. "Threshold autoregressive models for interval-valued time series data," Journal of Econometrics, Elsevier, vol. 206(2), pages 414-446.

  55. Cathy W. S. Chen & Mike K. P. So & Ming-Tien Chen, 2005. "A Bayesian threshold nonlinearity test for financial time series," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 24(1), pages 61-75.

    Cited by:

    1. Chen, Cathy W.S. & Gerlach, Richard H. & Tai, Amanda P.J., 2008. "Testing for nonlinearity in mean and volatility for heteroskedastic models," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 79(3), pages 489-499.
    2. Chen, Cathy W.S. & Chan, Jennifer S.K. & So, Mike K.P. & Lee, Kevin K.M., 2011. "Classification in segmented regression problems," Computational Statistics & Data Analysis, Elsevier, vol. 55(7), pages 2276-2287, July.
    3. Massimiliano Caporin & Rangan Gupta & Francesco Ravazzolo, 2019. "Contagion between Real Estate and Financial Markets: A Bayesian Quantile-on-Quantile Approach," Working Papers 201913, University of Pretoria, Department of Economics.
    4. Lai, YiHao & Chen, Cathy W.S. & Gerlach, Richard, 2009. "Optimal dynamic hedging via copula-threshold-GARCH models," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 79(8), pages 2609-2624.
    5. Caporin, Massimiliano & Pelizzon, Loriana & Ravazzolo, Francesco & Rigobon, Roberto, 2015. "Measuring sovereign contagion in Europe," SAFE Working Paper Series 103, Leibniz Institute for Financial Research SAFE.
    6. So, Mike K.P. & Chen, Cathy W.S. & Lee, Jen-Yu & Chang, Yi-Ping, 2008. "An empirical evaluation of fat-tailed distributions in modeling financial time series," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 77(1), pages 96-108.
    7. Varun Agiwal & Jitendra Kumar, 2020. "Bayesian estimation for threshold autoregressive model with multiple structural breaks," METRON, Springer;Sapienza Università di Roma, vol. 78(3), pages 361-382, December.
    8. Nonejad, Nima, 2014. "Particle Markov Chain Monte Carlo Techniques of Unobserved Component Time Series Models Using Ox," MPRA Paper 55662, University Library of Munich, Germany.
    9. Monica Billio & Roberto Casarin & Francesco Ravazzolo & Herman K. van Dijk, 2011. "Bayesian Combinations of Stock Price Predictions with an Application to the Amsterdam Exchange Index," Tinbergen Institute Discussion Papers 11-082/4, Tinbergen Institute.
    10. 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.
    11. Todd E. Clark & Francesco Ravazzolo, 2012. "The macroeconomic forecasting performance of autoregressive models with alternative specifications of time-varying volatility," Working Paper 2012/09, Norges Bank.
    12. Chen, Cathy W. S. & Chiang, Thomas C. & So, Mike K. P., 2003. "Asymmetrical reaction to US stock-return news: evidence from major stock markets based on a double-threshold model," Journal of Economics and Business, Elsevier, vol. 55(5-6), pages 487-502.
    13. Chen, Cathy W.S. & Gerlach, Richard & So, Mike K.P., 2006. "Comparison of nonnested asymmetric heteroskedastic models," Computational Statistics & Data Analysis, Elsevier, vol. 51(4), pages 2164-2178, December.
    14. Cathy Chen & Feng Liu & Richard Gerlach, 2011. "Bayesian subset selection for threshold autoregressive moving-average models," Computational Statistics, Springer, vol. 26(1), pages 1-30, March.
    15. Jiazhu Pan & Qiang Xia & Jinshan Liu, 2017. "Bayesian analysis of multiple thresholds autoregressive model," Computational Statistics, Springer, vol. 32(1), pages 219-237, March.
    16. Cathy Chen & Simon Lin & Philip Yu, 2012. "Smooth Transition Quantile Capital Asset Pricing Models with Heteroscedasticity," Computational Economics, Springer;Society for Computational Economics, vol. 40(1), pages 19-48, June.
    17. Nonejad Nima, 2016. "Particle Markov Chain Monte Carlo Techniques of Unobserved Component Time Series Models Using Ox," Journal of Time Series Econometrics, De Gruyter, vol. 8(1), pages 55-90, January.
    18. Nonejad, Nima, 2017. "Parameter instability, stochastic volatility and estimation based on simulated likelihood: Evidence from the crude oil market," Economic Modelling, Elsevier, vol. 61(C), pages 388-408.
    19. Liu, Xiaochun & Luger, Richard, 2015. "Unfolded GARCH models," Journal of Economic Dynamics and Control, Elsevier, vol. 58(C), pages 186-217.

  56. Cathy W. S. Chen & Mike K. P. So, 2003. "Subset threshold autoregression," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 22(1), pages 49-66.

    Cited by:

    1. Laurent Ferrara & Dominique Guégan, 2006. "Detection of the Industrial Business Cycle using SETAR Models," Journal of Business Cycle Measurement and Analysis, OECD Publishing, Centre for International Research on Economic Tendency Surveys, vol. 2005(3), pages 353-371.
    2. Gilles Dufrenot & Dominique Guegan & Anne Peguin-Feissolle, 2008. "Changing-regime volatility: A fractionally integrated SETAR model," Post-Print halshs-00185369, HAL.
    3. Florian Huber, 2014. "Forecasting Exchange Rates using Bayesian Threshold Vector Autoregressions," Economics Bulletin, AccessEcon, vol. 34(3), pages 1687-1695.
    4. Xiaobing Zheng & Kun Liang & Qiang Xia & Dabin Zhang, 2022. "Best Subset Selection for Double-Threshold-Variable Autoregressive Moving-Average Models: The Bayesian Approach," Computational Economics, Springer;Society for Computational Economics, vol. 59(3), pages 1175-1201, March.
    5. Philipp Piribauer, 2016. "Heterogeneity in spatial growth clusters," Empirical Economics, Springer, vol. 51(2), pages 659-680, September.
    6. Roberto Baragona & Francesco Battaglia & Domenico Cucina, 2004. "Estimating threshold subset autoregressive moving-average models by genetic algorithms," Metron - International Journal of Statistics, Dipartimento di Statistica, Probabilità e Statistiche Applicate - University of Rome, vol. 0(1), pages 39-61.
    7. Liu, Hsiang-Hsi & Chuang, Wen-I & Huang, Jih-Jeng & Chen, Yu-Hao, 2016. "The overconfident trading behavior of individual versus institutional investors," International Review of Economics & Finance, Elsevier, vol. 45(C), pages 518-539.
    8. Dufrenot, Gilles & Guegan, Dominique & Peguin-Feissolle, Anne, 2005. "Long-memory dynamics in a SETAR model - applications to stock markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 15(5), pages 391-406, December.
    9. Cathy Chen & Feng Liu & Richard Gerlach, 2011. "Bayesian subset selection for threshold autoregressive moving-average models," Computational Statistics, Springer, vol. 26(1), pages 1-30, March.
    10. Giannikis, D. & Vrontos, I.D. & Dellaportas, P., 2008. "Modelling nonlinearities and heavy tails via threshold normal mixture GARCH models," Computational Statistics & Data Analysis, Elsevier, vol. 52(3), pages 1549-1571, January.

  57. Chen, Cathy W. S. & Chiang, Thomas C. & So, Mike K. P., 2003. "Asymmetrical reaction to US stock-return news: evidence from major stock markets based on a double-threshold model," Journal of Economics and Business, Elsevier, vol. 55(5-6), pages 487-502.

    Cited by:

    1. Ross C Phillips & Denise Gorse, 2018. "Cryptocurrency price drivers: Wavelet coherence analysis revisited," PLOS ONE, Public Library of Science, vol. 13(4), pages 1-21, April.
    2. Norbert Funke & Akimi Matsuda, 2006. "Macroeconomic News and Stock Returns in the United States and Germany," German Economic Review, Verein für Socialpolitik, vol. 7(2), pages 189-210, May.
    3. XiaoHua Chen & Edna Solomon & Thanos Verousis, 2016. "Asymmetric Post-Announcement Drift to Good and Bad News: Evidence from Voluntary Trading Disclosures in the Chinese Stock Market," International Journal of the Economics of Business, Taylor & Francis Journals, vol. 23(2), pages 183-198, July.
    4. Cathy W. S. Chen & Richard Gerlach & Bruce B. K. Hwang & Michael McAleer, 2011. "Forecasting Value-at-Risk Using Nonlinear Regression Quantiles and the Intra-day Range," KIER Working Papers 775, Kyoto University, Institute of Economic Research.
    5. Chiang, Thomas C., 2019. "Empirical analysis of intertemporal relations between downside risks and expected returns—Evidence from Asian markets," Research in International Business and Finance, Elsevier, vol. 47(C), pages 264-278.
    6. Hela Namouri & Fredj Jawadi & Zied Ftiti & Néjib Hachicha, 2018. "Threshold effect in the relationship between investor sentiment and stock market returns: a PSTR specification," Applied Economics, Taylor & Francis Journals, vol. 50(5), pages 559-573, January.
    7. Dendramis, Yiannis & Kapetanios, George & Tzavalis, Elias, 2014. "Level shifts in stock returns driven by large shocks," Journal of Empirical Finance, Elsevier, vol. 29(C), pages 41-51.
    8. Yuan-Ming Lee & Kuan-Min Wang, 2012. "Searching for a better proxy for business cycles: with supports using US data," Applied Economics, Taylor & Francis Journals, vol. 44(11), pages 1433-1442, April.
    9. Chen, Cathy W.S. & Gerlach, Richard H. & Tai, Amanda P.J., 2008. "Testing for nonlinearity in mean and volatility for heteroskedastic models," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 79(3), pages 489-499.
    10. Lee, Hwang Hee & Hyun, Jung-Soon, 2019. "The asymmetric effect of equity volatility on credit default swap spreads," Journal of Banking & Finance, Elsevier, vol. 98(C), pages 125-136.
    11. Gebka, Bartosz & Serwa, Dobromil, 2006. "Are financial spillovers stable across regimes?: Evidence from the 1997 Asian crisis," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 16(4), pages 301-317, October.
    12. Yang, Yung-Lieh & Chang, Chia-Lin, 2008. "A double-threshold GARCH model of stock market and currency shocks on stock returns," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 79(3), pages 458-474.
    13. Fabio Trojani & Francesco Audrino, 2006. "Estimating and predicting multivariate volatility thresholds in global stock markets," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(3), pages 345-369.
    14. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    15. Chen, Cathy W.S. & Yang, Ming Jing & Gerlach, Richard & Jim Lo, H., 2006. "The asymmetric reactions of mean and volatility of stock returns to domestic and international information based on a four-regime double-threshold GARCH model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 366(C), pages 401-418.
    16. Cathy W. S. Chen & Mike K. P. So & Edward M. H. Lin, 2009. "Volatility forecasting with double Markov switching GARCH models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 28(8), pages 681-697.
    17. So, Mike K.P. & Chen, Cathy W.S. & Lee, Jen-Yu & Chang, Yi-Ping, 2008. "An empirical evaluation of fat-tailed distributions in modeling financial time series," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 77(1), pages 96-108.
    18. Gerlach, Richard & Chen, Cathy W.S. & Lin, Doris S.Y. & Huang, Ming-Hsiang, 2006. "Asymmetric responses of international stock markets to trading volume," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 360(2), pages 422-444.
    19. Jing Shi & Marcel Ausloos & Tingting Zhu, 2020. "If Global or Local Investor Sentiments are Prone to Developing an Impact on Stock Returns, is there an Industry Effect?," Papers 2012.12951, arXiv.org.
    20. Bartosz Gębka, 2012. "The Dynamic Relation Between Returns, Trading Volume, And Volatility: Lessons From Spillovers Between Asia And The United States," Bulletin of Economic Research, Wiley Blackwell, vol. 64(1), pages 65-90, January.
    21. Cathy W. S. Chen & Bonny Lee, 2021. "Bayesian inference of multiple structural change models with asymmetric GARCH errors," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 30(3), pages 1053-1078, September.
    22. Chen, Cathy W.S. & Gerlach, Richard & Lin, Edward M.H., 2008. "Volatility forecasting using threshold heteroskedastic models of the intra-day range," Computational Statistics & Data Analysis, Elsevier, vol. 52(6), pages 2990-3010, February.
    23. 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.
    24. Zhu, Junjun & Xie, Shiyu, 2010. "Bayesian Analysis of a Triple-Threshold GARCH Model with Application in Chinese Stock Market," MPRA Paper 28235, University Library of Munich, Germany.
    25. Li, Huimin & Jeon, Bang Nam & Cho, Seong-Yeon & Chiang, Thomas C., 2008. "The impact of sovereign rating changes and financial contagion on stock market returns: Evidence from five Asian countries," Global Finance Journal, Elsevier, vol. 19(1), pages 46-55.
    26. Roni Bhowmik & Abbas Ghulam & Wang Shouyang, 2018. "Return and Volatility Spillovers Effects: Study of Asian Emerging Stock Markets," Journal of Systems Science and Information, De Gruyter, vol. 6(2), pages 97-119, April.
    27. Cathy Chen & Shu-Yu Chen & Sangyeol Lee, 2013. "Bayesian Unit Root Test in Double Threshold Heteroskedastic Models," Computational Economics, Springer;Society for Computational Economics, vol. 42(4), pages 471-490, December.
    28. Cathy W. S. Chen & Richard H. Gerlach & Ann M. H. Lin, 2010. "Falling and explosive, dormant, and rising markets via multiple‐regime financial time series models," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 26(1), pages 28-49, January.
    29. Thomas C. Chiang & Cathy W.S. Chen & Mike K.P. So, 2007. "Asymmetric Return and Volatility Responses to Composite News from Stock Markets," Multinational Finance Journal, Multinational Finance Journal, vol. 11(3-4), pages 179-210, September.
    30. Kushal Banik Chowdhury & Nityananda Sarkar, 2015. "The Effect of Inflation on Inflation Uncertainty in the G7 Countries: A Double Threshold GARCH Model," International Econometric Review (IER), Econometric Research Association, vol. 7(1), pages 34-50, April.
    31. Faten Ben Slimane & Mohamed Mehanaoui & Irfan Akbar Kazi, 2013. "How Does the Financial Crisis Affect Volatility Behavior and Transmission Among European Stock Markets?," IJFS, MDPI, vol. 1(3), pages 1-21, August.
    32. Asgharian, Hossein & Liu, Lu, 2022. "Product market competition and stock return dependence," Finance Research Letters, Elsevier, vol. 50(C).
    33. Yingli Wang & Xiaoguang Yang, 2018. "Asymmetric response to PMI announcements in China's stock returns," Papers 1806.04347, arXiv.org.
    34. Klaus Grobys, 2015. "Size distortions of the wild bootstrapped HCCME-based LM test for serial correlation in the presence of asymmetric conditional heteroskedasticity," Empirical Economics, Springer, vol. 48(3), pages 1189-1202, May.
    35. Chen, Cathy W.S. & Gerlach, Richard & So, Mike K.P., 2006. "Comparison of nonnested asymmetric heteroskedastic models," Computational Statistics & Data Analysis, Elsevier, vol. 51(4), pages 2164-2178, December.
    36. Faten Ben Slimane & Mohamed Mehanaoui & Irfan A. Kazi, 2014. "Interdependency and Spillover during the Financial Crisis of 2007 to 2009 – Evidence from High Frequency Intraday Data," Working Papers 2014-126, Department of Research, Ipag Business School.
    37. Smales, Lee A., 2014. "Non-scheduled news arrival and high-frequency stock market dynamics," Research in International Business and Finance, Elsevier, vol. 32(C), pages 122-138.
    38. Dendramis, Yiannis & Kapetanios, George & Tzavalis, Elias, 2015. "Shifts in volatility driven by large stock market shocks," Journal of Economic Dynamics and Control, Elsevier, vol. 55(C), pages 130-147.
    39. Marcelo Cunha Medeiros & Alvaro Veiga, 2004. "Modelling multiple regimes in financial volatility with a flexible coefficient GARCH model," Textos para discussão 486, Department of Economics PUC-Rio (Brazil).
    40. Liu, Hsiang-Hsi & Chuang, Wen-I & Huang, Jih-Jeng & Chen, Yu-Hao, 2016. "The overconfident trading behavior of individual versus institutional investors," International Review of Economics & Finance, Elsevier, vol. 45(C), pages 518-539.
    41. CHEN, Cathy W.S. & WENG, Monica M.C. & WATANABE, Toshiaki & 渡部, 渡部, 2015. "Employing Bayesian Forecasting of Value-at-Risk to Determine an Appropriate Model for Risk Management," Discussion paper series HIAS-E-16, Hitotsubashi Institute for Advanced Study, Hitotsubashi University.
    42. Shumi Akhtar & Robert Faff & Barry Oliver, 2011. "The asymmetric impact of consumer sentiment announcements on Australian foreign exchange rates," Australian Journal of Management, Australian School of Business, vol. 36(3), pages 387-403, December.
    43. Cheng, Xixin & Li, W.K. & Yu, Philip L.H. & Zhou, Xuan & Wang, Chao & Lo, P.H., 2011. "Modeling threshold conditional heteroscedasticity with regime-dependent skewness and kurtosis," Computational Statistics & Data Analysis, Elsevier, vol. 55(9), pages 2590-2604, September.
    44. Dimitrios Vortelinos & Konstantinos Gkillas (Gillas) & Costas Syriopoulos & Argyro Svingou, 2017. "Asymmetric and nonlinear inter-relations of US stock indices," International Journal of Managerial Finance, Emerald Group Publishing Limited, vol. 14(1), pages 78-129, December.
    45. Sun, Yuying & Han, Ai & Hong, Yongmiao & Wang, Shouyang, 2018. "Threshold autoregressive models for interval-valued time series data," Journal of Econometrics, Elsevier, vol. 206(2), pages 414-446.
    46. Akhtar, Shumi & Faff, Robert & Oliver, Barry & Subrahmanyam, Avanidhar, 2011. "The power of bad: The negativity bias in Australian consumer sentiment announcements on stock returns," Journal of Banking & Finance, Elsevier, vol. 35(5), pages 1239-1249, May.
    47. Gao, Jiti & Gijbels, Irene & Van Bellegem, Sebastien, 2008. "Nonparametric simultaneous testing for structural breaks," Journal of Econometrics, Elsevier, vol. 143(1), pages 123-142, March.
    48. Knight John & Satchell Stephen, 2011. "Some New Results for Threshold AR(1) Models," Journal of Time Series Econometrics, De Gruyter, vol. 3(2), pages 1-42, April.
    49. Bialkowski, Jedrzej & Bohl, Martin T. & Serwa, Dobromil, 2006. "Testing for financial spillovers in calm and turbulent periods," The Quarterly Review of Economics and Finance, Elsevier, vol. 46(3), pages 397-412, July.
    50. Zhu, Hui-Ming & Li, ZhaoLai & You, WanHai & Zeng, Zhaofa, 2015. "Revisiting the asymmetric dynamic dependence of stock returns: Evidence from a quantile autoregression model," International Review of Financial Analysis, Elsevier, vol. 40(C), pages 142-153.
    51. Gebka, Bartosz, 2006. "Leaders and Laggards: International Evidence on Spillovers in Returns, Variance, and Trading Volume," Working Paper Series 2006,1, European University Viadrina Frankfurt (Oder), The Postgraduate Research Programme Capital Markets and Finance in the Enlarged Europe.
    52. Kung, Ling-Ming & Yu, Shang-Wu, 2008. "Prediction of index futures returns and the analysis of financial spillovers--A comparison between GARCH and the grey theorem," European Journal of Operational Research, Elsevier, vol. 186(3), pages 1184-1200, May.
    53. Yuan-Ming Lee & Kuan-Min Wang & T. Thanh-Binh Nguyen, 2008. "A Common-Use Proxy for Economic Performance: Application to Asymmetric Causality between the Stock Returns and Growth," International Journal of Business and Economics, School of Management Development, Feng Chia University, Taichung, Taiwan, vol. 7(2), pages 101-124, August.

  58. Cathy W. S. Chen & Tsai-Hung Cherng & Berlin Wu, 2001. "On the Selection of Subset Bilinear Time Series Models: a Genetic Algorithm Approach," Computational Statistics, Springer, vol. 16(4), pages 505-517, December.

    Cited by:

    1. Francesco Battaglia & Mattheos K. Protopapas, 2011. "Time‐varying multi‐regime models fitting by genetic algorithms," Journal of Time Series Analysis, Wiley Blackwell, vol. 32(3), pages 237-252, May.
    2. Roberto Baragona & Francesco Battaglia & Domenico Cucina, 2004. "Estimating threshold subset autoregressive moving-average models by genetic algorithms," Metron - International Journal of Statistics, Dipartimento di Statistica, Probabilità e Statistiche Applicate - University of Rome, vol. 0(1), pages 39-61.

  59. Chen, Cathy W. S. & Lee, Shen-Ming & Hsieh, Ying-Hen & Ungchusak, Kumnuan, 1999. "A unified approach to estimating population size for a births only model," Computational Statistics & Data Analysis, Elsevier, vol. 32(1), pages 29-46, November.

    Cited by:

    1. Hsieh, Ying-Hen & Chen, Cathy W.S. & Lee, Shen-Ming & Chen, Yi-Ming A. & Wu, Shiow-Ing & Lai, Shu-Fen & Chang, An-Lung, 2006. "Estimating the Number of HIV-infected gay sauna patrons in Taipei area," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 362(2), pages 495-503.

  60. Chen, Cathy W. S., 1998. "A Bayesian analysis of generalized threshold autoregressive models," Statistics & Probability Letters, Elsevier, vol. 40(1), pages 15-22, September.

    Cited by:

    1. Candelon, Bertrand & Lieb, Lenard, 2013. "Fiscal policy in good and bad times," Journal of Economic Dynamics and Control, Elsevier, vol. 37(12), pages 2679-2694.
    2. Carlo Pizzinelli & Konstantinos Theodoridis & Francesco Zanetti, 2018. "State Dependence in Labor Market Fluctuations: Evidence,Theory, and Policy Implications," BCAM Working Papers 1801, Birkbeck Centre for Applied Macroeconomics.
    3. Vugar Ahmadov & Salman Huseynov & Shaig Adigozalov & Fuad Mammadov & Vugar Rahimov, 2018. "Forecasting inflation in post-oil boom years: A case for regime switches?," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 42(2), pages 369-385, April.
    4. Andrea Carolina Vargas-Páez & Carlos David Ardila-Dueñas, 2021. "Efecto del riesgo de tipo de cambio en la rentabilidad de los bonos soberanos en Colombia," Borradores de Economia 1165, Banco de la Republica de Colombia.
    5. Vugar Ahmadov & Shaig Adigozalov & Salman Huseynov & Fuad Mammadov & Vugar Rahimov, 2016. "Forecasting inflation in post-oil boom years: A case for non-linear models?," Working Papers 1601, Central Bank of Azerbaijan Republic.
    6. Barnett, Alina & Mumtaz, Haroon & Theodoridis, Konstantinos, 2012. "Forecasting UK GDP growth, inflation and interest rates under structural change: a comparison of models with time-varying parameters," Bank of England working papers 450, Bank of England.
    7. Gerlach, Richard & Chen, Cathy W.S. & Lin, Doris S.Y. & Huang, Ming-Hsiang, 2006. "Asymmetric responses of international stock markets to trading volume," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 360(2), pages 422-444.
    8. Philipp Piribauer, 2016. "Heterogeneity in spatial growth clusters," Empirical Economics, Springer, vol. 51(2), pages 659-680, September.
    9. Varun Agiwal & Jitendra Kumar, 2020. "Bayesian estimation for threshold autoregressive model with multiple structural breaks," METRON, Springer;Sapienza Università di Roma, vol. 78(3), pages 361-382, December.
    10. Pizzinelli, Carlo & Theodoridis, Konstantinos & Zanetti, Francesco, 2020. "State Dependence in Labor Market Fluctuations," Cardiff Economics Working Papers E2020/2, Cardiff University, Cardiff Business School, Economics Section.
    11. Kling, Gerhard & Gao, Lei, 2008. "Chinese institutional investors' sentiment," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 18(4), pages 374-387, October.
    12. Manh Cuong Dong & Cathy W. S. Chen & Manabu Asai, 2023. "Bayesian non‐linear quantile effects on modelling realized kernels," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(1), pages 981-995, January.
    13. Edward P. Campbell, 2004. "Bayesian selection of threshold autoregressive models," Journal of Time Series Analysis, Wiley Blackwell, vol. 25(4), pages 467-482, July.
    14. Thomas C. Chiang & Cathy W.S. Chen & Mike K.P. So, 2007. "Asymmetric Return and Volatility Responses to Composite News from Stock Markets," Multinational Finance Journal, Multinational Finance Journal, vol. 11(3-4), pages 179-210, September.
    15. Kushal Banik Chowdhury & Nityananda Sarkar, 2015. "The Effect of Inflation on Inflation Uncertainty in the G7 Countries: A Double Threshold GARCH Model," International Econometric Review (IER), Econometric Research Association, vol. 7(1), pages 34-50, April.
    16. Chen, Cathy W. S. & Chiang, Thomas C. & So, Mike K. P., 2003. "Asymmetrical reaction to US stock-return news: evidence from major stock markets based on a double-threshold model," Journal of Economics and Business, Elsevier, vol. 55(5-6), pages 487-502.
    17. Zhepeng Hu & B. Wade Brorsen, 2017. "Spatial Price Transmission and Efficiency in the Urea Market," Agribusiness, John Wiley & Sons, Ltd., vol. 33(1), pages 98-115, January.
    18. Liu, Hsiang-Hsi & Chuang, Wen-I & Huang, Jih-Jeng & Chen, Yu-Hao, 2016. "The overconfident trading behavior of individual versus institutional investors," International Review of Economics & Finance, Elsevier, vol. 45(C), pages 518-539.
    19. Jiazhu Pan & Qiang Xia & Jinshan Liu, 2017. "Bayesian analysis of multiple thresholds autoregressive model," Computational Statistics, Springer, vol. 32(1), pages 219-237, March.
    20. Silvia Haan-Rietdijk & John Gottman & Cindy Bergeman & Ellen Hamaker, 2016. "Get Over It! A Multilevel Threshold Autoregressive Model for State-Dependent Affect Regulation," Psychometrika, Springer;The Psychometric Society, vol. 81(1), pages 217-241, March.
    21. Mohamed A. Ismail & Husni A. Charif, 2003. "Bayesian inference for threshold moving average models," Metron - International Journal of Statistics, Dipartimento di Statistica, Probabilità e Statistiche Applicate - University of Rome, vol. 0(1), pages 119-132.

  61. Chen, Cathy W. S., 1997. "Detection of additive outliers in bilinear time series," Computational Statistics & Data Analysis, Elsevier, vol. 24(3), pages 283-294, May.

    Cited by:

    1. Chen, Cathy W.S. & Lee, Sangyeol, 2016. "Generalized Poisson autoregressive models for time series of counts," Computational Statistics & Data Analysis, Elsevier, vol. 99(C), pages 51-67.
    2. King Chi Hung & Siu Hung Cheung & Wai-Sum Chan & Li-Xin Zhang, 2009. "On a robust test for SETAR-type nonlinearity in time series analysis," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 28(5), pages 445-464.
    3. Jussi Tolvi, 2001. "Outliers in eleven Finnish macroeconomic time series," Finnish Economic Papers, Finnish Economic Association, vol. 14(1), pages 14-32, Spring.
    4. Francesco Battaglia & Lia Orfei, 2005. "Outlier Detection And Estimation In NonLinear Time Series," Journal of Time Series Analysis, Wiley Blackwell, vol. 26(1), pages 107-121, January.
    5. Ping Chen & Jing Yang & Linyuan Li, 2015. "Synthetic detection of change point and outliers in bilinear time series models," International Journal of Systems Science, Taylor & Francis Journals, vol. 46(2), pages 284-293, January.
    6. Battaglia, Francesco, 2005. "Outliers in functional autoregressive time series," Statistics & Probability Letters, Elsevier, vol. 72(4), pages 323-332, May.

  62. Cathy W. S. Chen & Jack C. Lee, 1995. "Bayesian Inference Of Threshold Autoregressive Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 16(5), pages 483-492, September.

    Cited by:

    1. Tomas Konecny & Oxana Babecka-Kucharcukova, 2016. "Credit Spreads and the Links between the Financial and Real Sectors in a Small Open Economy: The Case of the Czech Republic," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 66(4), pages 302-321, August.
    2. Mehmet Caner & Bruce E. Hansen, 1998. "Threshold Autoregressions with a Near Unit Root," Working Papers 9821, Department of Economics, Bilkent University.
    3. Xianbo Zhou & Zhuoran Chen, 2023. "The Impact of Uncertainty Shocks to Consumption under Different Confidence Regimes Based on a Stochastic Uncertainty-in-Mean TVAR Model," Sustainability, MDPI, vol. 15(4), pages 1-20, February.
    4. De Santis, Roberto A. & Tornese, Tommaso, 2023. "Energy supply shocks’ nonlinearities on output and prices," Working Paper Series 2834, European Central Bank.
    5. Candelon, Bertrand & Lieb, Lenard, 2013. "Fiscal policy in good and bad times," Journal of Economic Dynamics and Control, Elsevier, vol. 37(12), pages 2679-2694.
    6. Carlo Pizzinelli & Konstantinos Theodoridis & Francesco Zanetti, 2018. "State Dependence in Labor Market Fluctuations: Evidence,Theory, and Policy Implications," BCAM Working Papers 1801, Birkbeck Centre for Applied Macroeconomics.
    7. Miranda-Agrippino, Silvia & Ricco, Giovanni, 2018. "Bayesian vector autoregressions," LSE Research Online Documents on Economics 87393, London School of Economics and Political Science, LSE Library.
    8. Piergiorgio Alessandri & Haroon Mumtaz, 2014. "Financial regimes and uncertainty shocks," BCAM Working Papers 1404, Birkbeck Centre for Applied Macroeconomics.
    9. Franta, Michal, 2021. "The Likelihood Of Effective Lower Bound Events," Macroeconomic Dynamics, Cambridge University Press, vol. 25(8), pages 2058-2079, December.
    10. KANAZAWA, Nobuyuki & 金澤, 伸幸, 2018. "Radial Basis Functions Neural Networks for Nonlinear Time Series Analysis and Time-Varying Effects of Supply Shocks," Discussion paper series HIAS-E-64, Hitotsubashi Institute for Advanced Study, Hitotsubashi University.
    11. Loschi, R.H. & Iglesias, P.L. & Arellano-Valle, R.B. & Cruz, F.R.B., 2007. "Full predictivistic modeling of stock market data: Application to change point problems," European Journal of Operational Research, Elsevier, vol. 180(1), pages 282-291, July.
    12. Henry, O.T. & Summers, P.M., 2000. "Australian Economic Growth: Non-Linearities and Internaitonal Influences," Department of Economics - Working Papers Series 738, The University of Melbourne.
    13. Ip, Wai-Cheung & Wong, Heung & Li, Yuan & Xie, Zhongjie, 1999. "Threshold variable selection by wavelets in open-loop threshold autoregressive models," Statistics & Probability Letters, Elsevier, vol. 42(4), pages 375-392, May.
    14. Xiwen Bai & Jesús Fernández-Villaverde & Yiliang Li & Francesco Zanetti, 2024. "The Causal Effects of Global Supply Chain Disruptions on Macroeconomic Outcomes: Evidence and Theory," CESifo Working Paper Series 10930, CESifo.
    15. Vugar Ahmadov & Salman Huseynov & Shaig Adigozalov & Fuad Mammadov & Vugar Rahimov, 2018. "Forecasting inflation in post-oil boom years: A case for regime switches?," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 42(2), pages 369-385, April.
    16. Florian Huber, 2014. "Forecasting Exchange Rates using Bayesian Threshold Vector Autoregressions," Economics Bulletin, AccessEcon, vol. 34(3), pages 1687-1695.
    17. Abidoye, Babatunde O. & Mabaya, Edward, 2013. "Adoption of Genetically Modified Crops in South Africa: Effects on wholesale maize prices," 2013 Fourth International Conference, September 22-25, 2013, Hammamet, Tunisia 160579, African Association of Agricultural Economists (AAAE).
    18. Chiu, Ching-Wai (Jeremy) & Hacioglu Hoke, Sinem, 2016. "Macroeconomic tail events with non-linear Bayesian VARs," Bank of England working papers 611, Bank of England.
    19. Andrea Carolina Vargas-Páez & Carlos David Ardila-Dueñas, 2021. "Efecto del riesgo de tipo de cambio en la rentabilidad de los bonos soberanos en Colombia," Borradores de Economia 1165, Banco de la Republica de Colombia.
    20. Chen, Cathy W.S. & So, Mike K.P., 2006. "On a threshold heteroscedastic model," International Journal of Forecasting, Elsevier, vol. 22(1), pages 73-89.
    21. Chan, Wai-Sum, 2022. "On temporal aggregation of some nonlinear time-series models," Econometrics and Statistics, Elsevier, vol. 21(C), pages 38-49.
    22. Magnus Reif, 2020. "Macroeconomics, Nonlinearities, and the Business Cycle," ifo Beiträge zur Wirtschaftsforschung, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 87.
    23. Vugar Ahmadov & Shaig Adigozalov & Salman Huseynov & Fuad Mammadov & Vugar Rahimov, 2016. "Forecasting inflation in post-oil boom years: A case for non-linear models?," Working Papers 1601, Central Bank of Azerbaijan Republic.
    24. Piergiorgio Alessandri & Haroon Mumtaz, 2014. "Financial indicators and density forecasts for US output and inflation," Temi di discussione (Economic working papers) 977, Bank of Italy, Economic Research and International Relations Area.
    25. Terence D.Agbeyegbe & Elena Goldman, 2005. "Estimation of threshold time series models using efficient jump MCMC," Economics Working Paper Archive at Hunter College 406, Hunter College Department of Economics, revised 2005.
    26. Hahn, Elke, 2020. "The wage-price pass-through in the euro area: does the growth regime matter?," Working Paper Series 2485, European Central Bank.
    27. Haroon Mumtaz & Laura Sunder-Plassmann, 2017. "Non-linear effects of government spending shocks in the US. Evidence from state-level data," Working Papers 841, Queen Mary University of London, School of Economics and Finance.
    28. De Santis, Roberto A. & Tornese, Tommaso, 2024. "US monetary policy is more powerful in low economic growth regimes," Working Paper Series 2919, European Central Bank.
    29. Barnett, Alina & Mumtaz, Haroon & Theodoridis, Konstantinos, 2012. "Forecasting UK GDP growth, inflation and interest rates under structural change: a comparison of models with time-varying parameters," Bank of England working papers 450, Bank of England.
    30. Nobuhiko Terui & Wirawan Dony Dahana, 2006. "Research Note—Estimating Heterogeneous Price Thresholds," Marketing Science, INFORMS, vol. 25(4), pages 384-391, 07-08.
    31. Piergiorgio Alessandri & Haroon Mumtaz, 2014. "Financial Conditions and Density Forecasts for US Output and Inflation," Working Papers 715, Queen Mary University of London, School of Economics and Finance.
    32. Xiaobing Zheng & Kun Liang & Qiang Xia & Dabin Zhang, 2022. "Best Subset Selection for Double-Threshold-Variable Autoregressive Moving-Average Models: The Bayesian Approach," Computational Economics, Springer;Society for Computational Economics, vol. 59(3), pages 1175-1201, March.
    33. Knotek, Edward S. & Zaman, Saeed, 2021. "Asymmetric responses of consumer spending to energy prices: A threshold VAR approach," Energy Economics, Elsevier, vol. 95(C).
    34. Cathy W. S. Chen & Mike K. P. So & Ming-Tien Chen, 2005. "A Bayesian threshold nonlinearity test for financial time series," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 24(1), pages 61-75.
    35. Varun Agiwal & Jitendra Kumar, 2020. "Bayesian estimation for threshold autoregressive model with multiple structural breaks," METRON, Springer;Sapienza Università di Roma, vol. 78(3), pages 361-382, December.
    36. Pizzinelli, Carlo & Theodoridis, Konstantinos & Zanetti, Francesco, 2020. "State Dependence in Labor Market Fluctuations," Cardiff Economics Working Papers E2020/2, Cardiff University, Cardiff Business School, Economics Section.
    37. Chen, Cathy W.S. & Gerlach, Richard & Lin, Edward M.H., 2008. "Volatility forecasting using threshold heteroskedastic models of the intra-day range," Computational Statistics & Data Analysis, Elsevier, vol. 52(6), pages 2990-3010, February.
    38. Zhu, Junjun & Xie, Shiyu, 2010. "Bayesian Analysis of a Triple-Threshold GARCH Model with Application in Chinese Stock Market," MPRA Paper 28235, University Library of Munich, Germany.
    39. De Luigi, Clara & Huber, Florian, 2018. "Debt regimes and the effectiveness of monetary policy," Journal of Economic Dynamics and Control, Elsevier, vol. 93(C), pages 218-238.
    40. Huber, Florian & Zörner, Thomas O., 2019. "Threshold cointegration in international exchange rates:A Bayesian approach," International Journal of Forecasting, Elsevier, vol. 35(2), pages 458-473.
    41. Bruce E. Hansen & Mehmet Caner, 1997. "Threshold Autoregressions with a Unit Root," Boston College Working Papers in Economics 381, Boston College Department of Economics.
    42. Reif Magnus, 2021. "Macroeconomic uncertainty and forecasting macroeconomic aggregates," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 25(2), pages 1-20, April.
    43. Gian Paulo Soave, 2023. "A panel threshold VAR with stochastic volatility-in-mean model: an application to the effects of financial and uncertainty shocks in emerging economies," Applied Economics, Taylor & Francis Journals, vol. 55(4), pages 397-431, January.
    44. MeiChi Huang, 2022. "Time‐varying impacts of expectations on housing markets across hot and cold phases," International Finance, Wiley Blackwell, vol. 25(2), pages 249-265, August.
    45. Balcilar, Mehmet & Ozdemir, Zeynel Abidin & Ozdemir, Huseyin & Aygun, Gurcan & Wohar, Mark E., 2022. "The macroeconomic impact of economic uncertainty and financial shocks under low and high financial stress," The North American Journal of Economics and Finance, Elsevier, vol. 63(C).
    46. Mansur, Alfan, 2023. "Capital flow volatility regimes and monetary policy dilemma: Evidence from New Zealand," The Journal of Economic Asymmetries, Elsevier, vol. 28(C).
    47. Balcilar, Mehmet & Ozdemir, Zeynel Abidin & Ozdemir, Huseyin & Aygun, Gurcan & Wohar, Mark E., 2022. "How Does the Economic Uncertainty Affect Asset Prices under Normal and Financial Distress Times?," IZA Discussion Papers 15296, Institute of Labor Economics (IZA).
    48. Nalban, Valeriu & Smădu, Andra, 2021. "Asymmetric effects of uncertainty shocks: Normal times and financial disruptions are different," Journal of Macroeconomics, Elsevier, vol. 69(C).
    49. Heinrich, Markus, 2020. "Does the Current State of the Business Cycle matter for Real-Time Forecasting? A Mixed-Frequency Threshold VAR approach," EconStor Preprints 219312, ZBW - Leibniz Information Centre for Economics.
    50. Ivan Mendieta‐Muñoz & Doğuhan Sündal, 2022. "Business cycles, financial conditions, and nonlinearities," Metroeconomica, Wiley Blackwell, vol. 73(2), pages 343-383, May.
    51. Piergiorgio Alessandri & Haroon Mumtaz, 2017. "Online Appendix to "Financial conditions and density forecasts for US output and inflation"," Online Appendices 14-103, Review of Economic Dynamics.
    52. Jiazhu Pan & Qiang Xia & Jinshan Liu, 2017. "Bayesian analysis of multiple thresholds autoregressive model," Computational Statistics, Springer, vol. 32(1), pages 219-237, March.
    53. Valeriu Nalban, 2016. "Sentiment-Driven Asymmetries in Romanian Monetary Policy Transmission," Eastern European Economics, Taylor & Francis Journals, vol. 54(3), pages 251-270, May.
    54. Silgado-Gómez, Edgar, 2022. "Sovereign Uncertainty," Research Technical Papers 10/RT/22, Central Bank of Ireland.
    55. Chen, Cathy W. S., 1998. "A Bayesian analysis of generalized threshold autoregressive models," Statistics & Probability Letters, Elsevier, vol. 40(1), pages 15-22, September.
    56. Ahmed Ghezal & Maddalena Cavicchioli & Imane Zemmouri, 2024. "On the existence of stationary threshold bilinear processes," Statistical Papers, Springer, vol. 65(6), pages 3739-3767, August.
    57. Cathy W. S. Chen & Mike K. P. So, 2003. "Subset threshold autoregression," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 22(1), pages 49-66.
    58. Chan, J.S.K. & Lam, C.P.Y. & Yu, P.L.H. & Choy, S.T.B. & Chen, C.W.S., 2012. "A Bayesian conditional autoregressive geometric process model for range data," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3006-3019.
    59. Miescu, Mirela & Mumtaz, Haroon & Theodoridis, Konstantinos, 2024. "Non-linear Dynamics of Oil Supply News Shocks," Cardiff Economics Working Papers E2024/18, Cardiff University, Cardiff Business School, Economics Section.
    60. Mohamed A. Ismail & Husni A. Charif, 2003. "Bayesian inference for threshold moving average models," Metron - International Journal of Statistics, Dipartimento di Statistica, Probabilità e Statistiche Applicate - University of Rome, vol. 0(1), pages 119-132.

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