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Xu, Dinghai

Personal Details

First Name:Dinghai
Middle Name:
Last Name:Xu
Suffix:
RePEc Short-ID:pxu46
[This author has chosen not to make the email address public]
http://arts.uwaterloo.ca/~dhxu/
Terminal Degree:2007 Department of Economics; University of Western Ontario (from RePEc Genealogy)

Affiliation

Department of Economics
University of Waterloo

Waterloo, Canada
http://economics.uwaterloo.ca/
RePEc:edi:dewatca (more details at EDIRC)

Research output

as
Jump to: Working papers Articles

Working papers

  1. Dinghai Xu, 2020. "Canadian Stock Market Volatility under COVID-19," Working Papers 2001, University of Waterloo, Department of Economics, revised May 2020.
  2. Dinghai Xu, 2019. "A Study on Volatility Spurious Almost Integration Effect: A Threshold Realized GARCH Approach," Working Papers 1903, University of Waterloo, Department of Economics, revised Dec 2019.
  3. Dinghai Xu & Jingru Ji & Donghua Wang, 2018. "Modelling the spreading process of extreme risks via a simple agent-based model: Evidence from the China stock market," Working Papers 1806, University of Waterloo, Department of Economics, revised 09 Jan 2018.
  4. Cathy Ning & Dinghai Xu & Tony Wirjanto, 2014. "Is Volatility Clustering of Asset Returns Asymmetric?," Working Papers 050, Toronto Metropolitan University, Department of Economics.
  5. Ajay Singh & Dinghai Xu, 2013. "Random Matrix Application to Correlations Among Volatility of Assets," Papers 1310.1601, arXiv.org.
  6. Dinghai Xu, 2012. "Continuous Empirical Characteristic Function Estimation of GARCH Models," Working Papers 1204, University of Waterloo, Department of Economics, revised May 2012.
  7. Pierre Chausse & Dinghai Xu, 2012. "GMM Estimation of a Stochastic Volatility Model with Realized Volatility: A Monte Carlo Study," Working Papers 1203, University of Waterloo, Department of Economics, revised May 2012.
  8. Dinghai Xu & Yuying Li, 2010. "Empirical Evidence of the Leverage Effect in a Stochastic Volatility Model: A Realized Volatility Approach," Working Papers 1002, University of Waterloo, Department of Economics, revised May 2010.
  9. Dinghai Xu, 2010. "A Threshold Stochastic Volatility Model with Realized Volatility," Working Papers 1003, University of Waterloo, Department of Economics, revised May 2010.
  10. Cathy Ning & Dinghai Xu & Tony Wirjanto, 2009. "Modeling Asymmetric Volatility Clusters Using Copulas and High Frequency Data," Working Papers 006, Toronto Metropolitan University, Department of Economics.
  11. Dinghai Xu, 2009. "The Applications of Mixtures of Normal Distributions in Empirical Finance: A Selected Survey," Working Papers 0904, University of Waterloo, Department of Economics, revised Sep 2009.
  12. Dinghai Xu, 2009. "An Efficient Estimation for Switching Regression Models: A Monte Carlo Study," Working Papers 0903, University of Waterloo, Department of Economics, revised Apr 2009.
  13. Dinghai Xu & Tony S. Wirjanto, 2008. "An Empirical Characteristic Function Approach to VaR under a Mixture of Normal Distribution with Time-Varying Volatility," Working Papers 08008, University of Waterloo, Department of Economics.
  14. Dinghai Xu & John Knight, 2008. "Continuous Empirical Characteristic Function Estimation of Mixtures of Normal Parameters," Working Papers 08006, University of Waterloo, Department of Economics.
  15. Dinghai Xu & John Knight & Tony S. Wirjanto, 2008. "Asymmetric Stochastic Conditional Duration Model --A Mixture of Normals Approach"," Working Papers 08007, University of Waterloo, Department of Economics.

Articles

  1. Dinghai Xu, 2024. "“Good” and “bad” volatilities: a realized semivariance GARCH approach," Applied Economics, Taylor & Francis Journals, vol. 56(51), pages 6391-6411, November.
  2. Xu, Dinghai, 2022. "Canadian stock market volatility under COVID-19," International Review of Economics & Finance, Elsevier, vol. 77(C), pages 159-169.
  3. Donghua Wang & Jin Ding & Guoqing Chu & Dinghai Xu & Tony S. Wirjanto, 2021. "Modelling asset returns in the presence of price limits with Markov-switching mixture of truncated normal GARCH distribution: evidence from China," Applied Economics, Taylor & Francis Journals, vol. 53(7), pages 781-804, February.
  4. Dinghai Xu, 2021. "A study on volatility spurious almost integration effect: A threshold realized GARCH approach," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(3), pages 4104-4126, July.
  5. Ji, Jingru & Wang, Donghua & Xu, Dinghai & Xu, Chi, 2020. "Combining a self-exciting point process with the truncated generalized Pareto distribution: An extreme risk analysis under price limits," Journal of Empirical Finance, Elsevier, vol. 57(C), pages 52-70.
  6. Dinghai Xu, 2020. "Modelling asset returns under price limits with mixture of truncated Gaussian distribution," Applied Economics, Taylor & Francis Journals, vol. 52(52), pages 5706-5725, November.
  7. Ji, Jingru & Wang, Donghua & Xu, Dinghai, 2019. "Modelling the spreading process of extreme risks via a simple agent-based model: Evidence from the China stock market," Economic Modelling, Elsevier, vol. 80(C), pages 383-391.
  8. Pierre Chaussé & Dinghai Xu, 2018. "GMM estimation of a realized stochastic volatility model: A Monte Carlo study," Econometric Reviews, Taylor & Francis Journals, vol. 37(7), pages 719-743, August.
  9. Ajay Singh & Dinghai Xu, 2016. "Random matrix application to correlations amongst the volatility of assets," Quantitative Finance, Taylor & Francis Journals, vol. 16(1), pages 69-83, January.
  10. Ning, Cathy & Xu, Dinghai & Wirjanto, Tony S., 2015. "Is volatility clustering of asset returns asymmetric?," Journal of Banking & Finance, Elsevier, vol. 52(C), pages 62-76.
  11. Dinghai Xu & John Knight, 2013. "Stochastic volatility model under a discrete mixture-of-normal specification," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 37(2), pages 216-239, April.
  12. Dinghai Xu & Yuying Li, 2012. "Select Empirical Evidence of the Leverage Effect in a Stochastic Volatility Model: A Realized Volatility Approach," Frontiers of Economics in China-Selected Publications from Chinese Universities, Higher Education Press, vol. 7(1), pages 22-43, March.
  13. Dinghai Xu & John Knight, 2011. "Continuous Empirical Characteristic Function Estimation of Mixtures of Normal Parameters," Econometric Reviews, Taylor & Francis Journals, vol. 30(1), pages 25-50.
  14. Dinghai Xu & John Knight & Tony S. Wirjanto, 2011. "Asymmetric Stochastic Conditional Duration Model--A Mixture-of-Normal Approach," Journal of Financial Econometrics, Oxford University Press, vol. 9(3), pages 469-488, Summer.
  15. Ning, Cathy & Xu, Dinghai & Wirjanto, Tony S., 2008. "Modeling the leverage effect with copulas and realized volatility," Finance Research Letters, Elsevier, vol. 5(4), pages 221-227, December.

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. Dinghai Xu, 2020. "Canadian Stock Market Volatility under COVID-19," Working Papers 2001, University of Waterloo, Department of Economics, revised May 2020.

    Cited by:

    1. Pham, Son Duy & Nguyen, Thao Thac Thanh & Do, Hung Xuan & Vo, Xuan Vinh, 2023. "Portfolio diversification during the COVID-19 pandemic: Do vaccinations matter?," Journal of Financial Stability, Elsevier, vol. 65(C).
    2. Gu, Tiantian & Venkateswaran, Anand & Erath, Marc, 2023. "Impact of fiscal stimulus on volatility: A cross-country analysis," Research in International Business and Finance, Elsevier, vol. 65(C).
    3. Si Mohammed, Kamel & Tedeschi, Marco & Mallek, Sabrine & Tarczyńska-Łuniewska, Małgorzata & Zhang, Anqi, 2023. "Realized semi variance quantile connectedness between oil prices and stock market: Spillover from Russian-Ukraine clash," Resources Policy, Elsevier, vol. 85(PA).
    4. Si Mohammed, K. & Mellit, A., 2023. "The relationship between oil prices and the indices of renewable energy and technology companies based on QQR and GCQ techniques," Renewable Energy, Elsevier, vol. 209(C), pages 97-105.
    5. Paresh Kumar Narayan & Syed Aun R. Rizvi & Ali Sakti, 2022. "Did green debt instruments aid diversification during the COVID-19 pandemic?," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-15, December.
    6. Seyed Reza Tabatabaei Poudeh & Sungchul Choi & Chengbo Fu, 2022. "The Effect of COVID-19 on the Relationship between Idiosyncratic Volatility and Expected Stock Returns," Risks, MDPI, vol. 10(3), pages 1-11, March.

  2. Dinghai Xu, 2019. "A Study on Volatility Spurious Almost Integration Effect: A Threshold Realized GARCH Approach," Working Papers 1903, University of Waterloo, Department of Economics, revised Dec 2019.

    Cited by:

    1. Dinghai Xu, 2020. "Canadian Stock Market Volatility under COVID-19," Working Papers 2001, University of Waterloo, Department of Economics, revised May 2020.

  3. Dinghai Xu & Jingru Ji & Donghua Wang, 2018. "Modelling the spreading process of extreme risks via a simple agent-based model: Evidence from the China stock market," Working Papers 1806, University of Waterloo, Department of Economics, revised 09 Jan 2018.

    Cited by:

    1. Zhang, Jinyu & Zhang, Qiaosen & Li, Yong & Wang, Qianchao, 2023. "Sequential Bayesian inference for agent-based models with application to the Chinese business cycle," Economic Modelling, Elsevier, vol. 126(C).
    2. Tubbenhauer, Tobias & Fieberg, Christian & Poddig, Thorsten, 2021. "Multi-agent-based VaR forecasting," Journal of Economic Dynamics and Control, Elsevier, vol. 131(C).

  4. Cathy Ning & Dinghai Xu & Tony Wirjanto, 2014. "Is Volatility Clustering of Asset Returns Asymmetric?," Working Papers 050, Toronto Metropolitan University, Department of Economics.

    Cited by:

    1. Fei Su & Lei Wang, 2020. "Conditional Volatility Persistence and Realized Volatility Asymmetry: Evidence from the Chinese Stock Markets," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 56(14), pages 3252-3269, November.
    2. Jang, Minchul & Yoon, Soeun & Jung, Seoyoung & Min, Baehyun, 2024. "Simulating and assessing carbon markets: Application to the Korean and the EU ETSs," Renewable and Sustainable Energy Reviews, Elsevier, vol. 195(C).
    3. Kim Karlsson, Hyunjoo & Li, Yushu, 2024. "Investigation of Swedish krona exchange rate volatility by APARCH-Support Vector Regression," Working Papers in Economics and Statistics 10/2024, Linnaeus University, School of Business and Economics, Department of Economics and Statistics.
    4. Aloui, Chaker & Hammoudeh, Shawkat & Hamida, Hela Ben, 2015. "Price discovery and regime shift behavior in the relationship between sharia stocks and sukuk: A two-state Markov switching analysis," Pacific-Basin Finance Journal, Elsevier, vol. 34(C), pages 121-135.
    5. Yang, Bingduo & Cai, Zongwu & Hafner, Christian M. & Liu, Guannan, 2018. "Trending Mixture Copula Models with Copula Selection," IRTG 1792 Discussion Papers 2018-057, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    6. Dinghai Xu, 2021. "A study on volatility spurious almost integration effect: A threshold realized GARCH approach," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(3), pages 4104-4126, July.
    7. Yarovaya, Larisa & Brzeszczyński, Janusz & Lau, Chi Keung Marco, 2017. "Asymmetry in spillover effects: Evidence for international stock index futures markets," International Review of Financial Analysis, Elsevier, vol. 53(C), pages 94-111.
    8. Zhao, Xiaojun & Zhang, Na & Zhang, Yali & Xu, Chao & Shang, Pengjian, 2024. "Equity markets volatility clustering: A multiscale analysis of intraday and overnight returns," Journal of Empirical Finance, Elsevier, vol. 77(C).
    9. Ana Carolina Costa Correa & Tabajara Pimenta Júnior & Luiz Eduardo Gaio, 2018. "Interdependence and asymmetries: Latin American ADRs and developed markets," Brazilian Business Review, Fucape Business School, vol. 15(4), pages 391-409, July.
    10. Phong Nguyen & Wei-han Liu, 2017. "Time-Varying Linkage of Possible Safe Haven Assets: A Cross-Market and Cross-asset Analysis," International Review of Finance, International Review of Finance Ltd., vol. 17(1), pages 43-76, March.
    11. Taylor, James W., 2022. "Forecasting Value at Risk and expected shortfall using a model with a dynamic omega ratio," Journal of Banking & Finance, Elsevier, vol. 140(C).
    12. Katarzyna Czech & Michał Wielechowski & Pavel Kotyza & Irena Benešová & Adriana Laputková, 2020. "Shaking Stability: COVID-19 Impact on the Visegrad Group Countries’ Financial Markets," Sustainability, MDPI, vol. 12(15), pages 1-19, August.
    13. Holger Fink & Yulia Klimova & Claudia Czado & Jakob Stober, 2016. "Regime switching vine copula models for global equity and volatility indices," Papers 1604.05598, arXiv.org.
    14. Ji‐Eun Choi & Dong Wan Shin, 2018. "Forecasts for leverage heterogeneous autoregressive models with jumps and other covariates," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 37(6), pages 691-704, September.
    15. Chyi Lin Lee, 2017. "An examination of the risk-return relation in the Australian housing market," International Journal of Housing Markets and Analysis, Emerald Group Publishing Limited, vol. 10(3), pages 431-449, June.
    16. Fei Su, 2018. "Essays on Price Discovery and Volatility Dynamics in the Foreign Exchange Market," PhD Thesis, Finance Discipline Group, UTS Business School, University of Technology, Sydney, number 2-2018, January-A.
    17. Holger Fink & Yulia Klimova & Claudia Czado & Jakob Stöber, 2017. "Regime Switching Vine Copula Models for Global Equity and Volatility Indices," Econometrics, MDPI, vol. 5(1), pages 1-38, January.
    18. 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.
    19. Ba Chu & Stephen Satchell, 2016. "Recovering the Most Entropic Copulas from Preliminary Knowledge of Dependence," Econometrics, MDPI, vol. 4(2), pages 1-21, March.
    20. Pablo Cansado-Bravo & Carlos Rodríguez-Monroy, 2018. "Persistence of Oil Prices in Gas Import Prices and the Resilience of the Oil-Indexation Mechanism. The Case of Spanish Gas Import Prices," Energies, MDPI, vol. 11(12), pages 1-17, December.
    21. Cao, Guangxi & Zhang, Minjia & Li, Qingchen, 2017. "Volatility-constrained multifractal detrended cross-correlation analysis: Cross-correlation among Mainland China, US, and Hong Kong stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 472(C), pages 67-76.
    22. Jan Jakub Szczygielski & Chimwemwe Chipeta, 2023. "Properties of returns and variance and the implications for time series modelling: Evidence from South Africa," Modern Finance, Modern Finance Institute, vol. 1(1), pages 35-55.

  5. Ajay Singh & Dinghai Xu, 2013. "Random Matrix Application to Correlations Among Volatility of Assets," Papers 1310.1601, arXiv.org.

    Cited by:

    1. Longfeng Zhao & Wei Li & Andrea Fenu & Boris Podobnik & Yougui Wang & H. Eugene Stanley, 2017. "The q-dependent detrended cross-correlation analysis of stock market," Papers 1705.01406, arXiv.org, revised Jun 2017.
    2. Sebastiano Michele Zema & Giorgio Fagiolo & Tiziano Squartini & Diego Garlaschelli, 2021. "Mesoscopic Structure of the Stock Market and Portfolio Optimization," LEM Papers Series 2021/45, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    3. Anshul Verma & Riccardo Junior Buonocore & Tiziana di Matteo, 2017. "A cluster driven log-volatility factor model: a deepening on the source of the volatility clustering," Papers 1712.02138, arXiv.org, revised May 2018.
    4. Nie, Chun-Xiao, 2021. "Analyzing financial correlation matrix based on the eigenvector–eigenvalue identity," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 567(C).

  6. Dinghai Xu & Yuying Li, 2010. "Empirical Evidence of the Leverage Effect in a Stochastic Volatility Model: A Realized Volatility Approach," Working Papers 1002, University of Waterloo, Department of Economics, revised May 2010.

    Cited by:

    1. Dinghai Xu, 2010. "A Threshold Stochastic Volatility Model with Realized Volatility," Working Papers 1003, University of Waterloo, Department of Economics, revised May 2010.
    2. Robert Stok & Paul Bilokon, 2023. "From Deep Filtering to Deep Econometrics," Papers 2311.06256, arXiv.org.

  7. Dinghai Xu, 2010. "A Threshold Stochastic Volatility Model with Realized Volatility," Working Papers 1003, University of Waterloo, Department of Economics, revised May 2010.

    Cited by:

    1. Heejoon Han & Eunhee Lee, 2020. "Triple Regime Stochastic Volatility Model with Threshold and Leverage Effects," Korean Economic Review, Korean Economic Association, vol. 36, pages 481-509.
    2. Mao, Xiuping & Ruiz, Esther & Veiga, Helena, 2017. "Threshold stochastic volatility: Properties and forecasting," International Journal of Forecasting, Elsevier, vol. 33(4), pages 1105-1123.

  8. Cathy Ning & Dinghai Xu & Tony Wirjanto, 2009. "Modeling Asymmetric Volatility Clusters Using Copulas and High Frequency Data," Working Papers 006, Toronto Metropolitan University, Department of Economics.

    Cited by:

    1. Oleg Sokolinskiy & Dick van Dijk, 2011. "Forecasting Volatility with Copula-Based Time Series Models," Tinbergen Institute Discussion Papers 11-125/4, Tinbergen Institute.
    2. Pedro Antonio Martín Cervantes & Salvador Cruz Rambaud & María del Carmen Valls Martínez, 2020. "An Application of the SRA Copulas Approach to Price-Volume Research," Mathematics, MDPI, vol. 8(11), pages 1-28, October.
    3. Sahil Aggarwal, 2013. "The Uncovered Interest Rate Parity Puzzle in the Foreign Exchange Market," Working Papers 13-07, New York University, Leonard N. Stern School of Business, Department of Economics.

  9. Dinghai Xu, 2009. "The Applications of Mixtures of Normal Distributions in Empirical Finance: A Selected Survey," Working Papers 0904, University of Waterloo, Department of Economics, revised Sep 2009.

    Cited by:

    1. Jun Lu & Shao Yi, 2022. "Reducing Overestimating and Underestimating Volatility via the Augmented Blending-ARCH Model," Applied Economics and Finance, Redfame publishing, vol. 9(2), pages 48-59, May.
    2. Assoc. Prof. Leon Li, 2022. "The Pricing of Discretionary Accruals Revisited: The Application of Mixtures of Regressions Based on Asymmetric Investor Behavior," International Journal of Economics and Financial Research, Academic Research Publishing Group, vol. 8(3), pages 78-84, 09-2022.
    3. Pedro Correia S. Bezerra & Pedro Henrique M. Albuquerque, 2017. "Volatility forecasting via SVR–GARCH with mixture of Gaussian kernels," Computational Management Science, Springer, vol. 14(2), pages 179-196, April.
    4. Jun Lu & Shao Yi, 2022. "Reducing overestimating and underestimating volatility via the augmented blending-ARCH model," Papers 2203.12456, arXiv.org.
    5. Yu Mei & Zhiping Chen & Jia Liu & Bingbing Ji, 2022. "Multi-stage portfolio selection problem with dynamic stochastic dominance constraints," Journal of Global Optimization, Springer, vol. 83(3), pages 585-613, July.

  10. Dinghai Xu & Tony S. Wirjanto, 2008. "An Empirical Characteristic Function Approach to VaR under a Mixture of Normal Distribution with Time-Varying Volatility," Working Papers 08008, University of Waterloo, Department of Economics.

    Cited by:

    1. Dinghai Xu, 2009. "The Applications of Mixtures of Normal Distributions in Empirical Finance: A Selected Survey," Working Papers 0904, University of Waterloo, Department of Economics, revised Sep 2009.
    2. Jiro Hodoshima & Toshiyuki Yamawake, 2020. "The Aumann–Serrano Performance Index for Multi-Period Gambles in Stock Data," JRFM, MDPI, vol. 13(11), pages 1-18, November.
    3. Tony S. Wirjanto & Adam W. Kolkiewicz & Zhongxian Men, 2013. "Stochastic Conditional Duration Models with Mixture Processes," Working Paper series 29_13, Rimini Centre for Economic Analysis.

  11. Dinghai Xu & John Knight, 2008. "Continuous Empirical Characteristic Function Estimation of Mixtures of Normal Parameters," Working Papers 08006, University of Waterloo, Department of Economics.

    Cited by:

    1. Cornelis J. Potgieter & Marc G. Genton, 2013. "Characteristic Function-based Semiparametric Inference for Skew-symmetric Models," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 40(3), pages 471-490, September.
    2. Hodoshima, Jiro & Yamawake, Toshiyuki, 2019. "Comparison of utility indifference pricing and mean-variance approach under a normal mixture distribution with time-varying volatility," Finance Research Letters, Elsevier, vol. 28(C), pages 74-81.
    3. Dinghai Xu & John Knight, 2013. "Stochastic volatility model under a discrete mixture-of-normal specification," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 37(2), pages 216-239, April.
    4. Dinghai Xu, 2009. "An Efficient Estimation for Switching Regression Models: A Monte Carlo Study," Working Papers 0903, University of Waterloo, Department of Economics, revised Apr 2009.

  12. Dinghai Xu & John Knight & Tony S. Wirjanto, 2008. "Asymmetric Stochastic Conditional Duration Model --A Mixture of Normals Approach"," Working Papers 08007, University of Waterloo, Department of Economics.

    Cited by:

    1. Zhongxian Men & Tony S. Wirjanto & Adam W. Kolkiewicz, 2013. "Bayesian Inference of Multiscale Stochastic Conditional Duration Models," Working Paper series 63_13, Rimini Centre for Economic Analysis.
    2. Dinghai Xu, 2009. "The Applications of Mixtures of Normal Distributions in Empirical Finance: A Selected Survey," Working Papers 0904, University of Waterloo, Department of Economics, revised Sep 2009.
    3. Zhongxian Men & Tony S. Wirjanto & Adam W. Kolkiewicz, 2016. "A Multiscale Stochastic Conditional Duration Model," Annals of Financial Economics (AFE), World Scientific Publishing Co. Pte. Ltd., vol. 11(04), pages 1-28, December.
    4. Zhongxian Men & Adam W. Kolkiewicz & Tony S. Wirjanto, 2019. "Threshold Stochastic Conditional Duration Model for Financial Transaction Data," JRFM, MDPI, vol. 12(2), pages 1-21, May.
    5. Tony S. Wirjanto & Adam W. Kolkiewicz & Zhongxian Men, 2013. "Stochastic Conditional Duration Models with Mixture Processes," Working Paper series 29_13, Rimini Centre for Economic Analysis.
    6. Dingan Feng & Peter X.-K. Song & Tony S. Wirjanto, 2015. "Time-Deformation Modeling of Stock Returns Directed by Duration Processes," Econometric Reviews, Taylor & Francis Journals, vol. 34(4), pages 480-511, April.
    7. Zhongxian Men & Adam W. Kolkiewicz & Tony S. Wirjanto, 2013. "Bayesian Inference of Asymmetric Stochastic Conditional Duration Models," Working Paper series 28_13, Rimini Centre for Economic Analysis.

Articles

  1. Xu, Dinghai, 2022. "Canadian stock market volatility under COVID-19," International Review of Economics & Finance, Elsevier, vol. 77(C), pages 159-169.
    See citations under working paper version above.
  2. Donghua Wang & Jin Ding & Guoqing Chu & Dinghai Xu & Tony S. Wirjanto, 2021. "Modelling asset returns in the presence of price limits with Markov-switching mixture of truncated normal GARCH distribution: evidence from China," Applied Economics, Taylor & Francis Journals, vol. 53(7), pages 781-804, February.

    Cited by:

    1. Amaro, Raphael & Pinho, Carlos & Madaleno, Mara, 2022. "Forecasting the Value-at-Risk of energy commodities: A comparison of models and alternative distribution functions," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 65, pages 77-101.
    2. Kai Zheng & Weidong Xu & Xili Zhang, 2023. "Multivariate Regime Switching Model Estimation and Asset Allocation," Computational Economics, Springer;Society for Computational Economics, vol. 61(1), pages 165-196, January.
    3. Amaro, Raphael & Pinho, Carlos, 2022. "Energy commodities: A study on model selection for estimating Value-at-Risk," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 68, pages 5-27.

  3. Dinghai Xu, 2021. "A study on volatility spurious almost integration effect: A threshold realized GARCH approach," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(3), pages 4104-4126, July.
    See citations under working paper version above.
  4. Ji, Jingru & Wang, Donghua & Xu, Dinghai & Xu, Chi, 2020. "Combining a self-exciting point process with the truncated generalized Pareto distribution: An extreme risk analysis under price limits," Journal of Empirical Finance, Elsevier, vol. 57(C), pages 52-70.

    Cited by:

    1. 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).

  5. Ji, Jingru & Wang, Donghua & Xu, Dinghai, 2019. "Modelling the spreading process of extreme risks via a simple agent-based model: Evidence from the China stock market," Economic Modelling, Elsevier, vol. 80(C), pages 383-391.
    See citations under working paper version above.
  6. Ajay Singh & Dinghai Xu, 2016. "Random matrix application to correlations amongst the volatility of assets," Quantitative Finance, Taylor & Francis Journals, vol. 16(1), pages 69-83, January.
    See citations under working paper version above.
  7. Ning, Cathy & Xu, Dinghai & Wirjanto, Tony S., 2015. "Is volatility clustering of asset returns asymmetric?," Journal of Banking & Finance, Elsevier, vol. 52(C), pages 62-76.
    See citations under working paper version above.
  8. Dinghai Xu & John Knight, 2011. "Continuous Empirical Characteristic Function Estimation of Mixtures of Normal Parameters," Econometric Reviews, Taylor & Francis Journals, vol. 30(1), pages 25-50.
    See citations under working paper version above.
  9. Dinghai Xu & John Knight & Tony S. Wirjanto, 2011. "Asymmetric Stochastic Conditional Duration Model--A Mixture-of-Normal Approach," Journal of Financial Econometrics, Oxford University Press, vol. 9(3), pages 469-488, Summer.
    See citations under working paper version above.
  10. Ning, Cathy & Xu, Dinghai & Wirjanto, Tony S., 2008. "Modeling the leverage effect with copulas and realized volatility," Finance Research Letters, Elsevier, vol. 5(4), pages 221-227, December.

    Cited by:

    1. Shi Yafeng & Tao Xiangxing & Shi Yanlong & Zhu Nenghui & Ying Tingting & Peng Xun, 2020. "Can Technical Indicators Provide Information for Future Volatility: International Evidence," Journal of Systems Science and Information, De Gruyter, vol. 8(1), pages 53-66, February.
    2. Marcel Wollschlager & Rudi Schafer, 2015. "Impact of non-stationarity on estimating and modeling empirical copulas of daily stock returns," Papers 1506.08054, arXiv.org.
    3. Shi Yafeng & Yanlong Shi & Ying Tingting, 2024. "Can technical indicators based on underlying assets help to predict implied volatility index," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 44(1), pages 57-74, January.
    4. Jorge V. Pérez-Rodríguez, 2020. "Another look at the implied and realised volatility relation: a copula-based approach," Risk Management, Palgrave Macmillan, vol. 22(1), pages 38-64, March.
    5. Serra, Teresa & Gil, José M., 2012. "Biodiesel as a motor fuel price stabilization mechanism," Energy Policy, Elsevier, vol. 50(C), pages 689-698.
    6. Wu, Xinyu & Wang, Xiaona, 2020. "Forecasting volatility using realized stochastic volatility model with time-varying leverage effect," Finance Research Letters, Elsevier, vol. 34(C).
    7. Tan, Zhengxun & Xiao, Binuo & Huang, Yilong & Zhou, Li, 2021. "Value at risk and return in Chinese and the US stock markets: Double long memory and fractional cointegration," The North American Journal of Economics and Finance, Elsevier, vol. 56(C).
    8. Yang, Kun & Wei, Yu & Li, Shouwei & He, Jianmin, 2020. "Asymmetric risk spillovers between Shanghai and Hong Kong stock markets under China’s capital account liberalization," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).

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NEP Fields

NEP is an announcement service for new working papers, with a weekly report in each of many fields. This author has had 16 papers announced in NEP. These are the fields, ordered by number of announcements, along with their dates. If the author is listed in the directory of specialists for this field, a link is also provided.
  1. NEP-ECM: Econometrics (12) 2009-01-03 2009-01-03 2009-01-03 2009-05-23 2009-10-10 2009-11-14 2010-05-15 2010-05-15 2012-09-03 2012-09-03 2013-10-11 2019-12-23. Author is listed
  2. NEP-ETS: Econometric Time Series (8) 2009-11-14 2010-05-15 2010-05-15 2010-05-15 2012-09-03 2012-09-03 2013-10-11 2019-12-23. Author is listed
  3. NEP-ORE: Operations Research (8) 2009-01-03 2009-05-23 2009-10-10 2010-05-15 2012-09-03 2018-10-01 2019-12-23 2020-05-11. Author is listed
  4. NEP-MST: Market Microstructure (5) 2009-11-14 2010-05-15 2010-05-15 2010-05-15 2015-10-04. Author is listed
  5. NEP-RMG: Risk Management (4) 2009-01-03 2013-10-11 2018-10-01 2020-05-11
  6. NEP-CFN: Corporate Finance (2) 2009-10-10 2015-10-04
  7. NEP-CNA: China (1) 2018-10-01
  8. NEP-FMK: Financial Markets (1) 2020-05-11
  9. NEP-FOR: Forecasting (1) 2019-12-23
  10. NEP-GEN: Gender (1) 2020-05-11
  11. NEP-TRA: Transition Economics (1) 2018-10-01

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