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Cathy Ning

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. 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. 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.
    2. 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.
    3. 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).
    4. 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.
    5. 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.
    6. 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.
    7. 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).
    8. 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.
    9. 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.
    10. 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.
    11. 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".
    12. 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.
    13. 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).
    14. 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.
    15. 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.
    16. 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.
    17. 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.
    18. Ba Chu & Stephen Satchell, 2016. "Recovering the Most Entropic Copulas from Preliminary Knowledge of Dependence," Econometrics, MDPI, vol. 4(2), pages 1-21, March.
    19. 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.
    20. 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.
    21. 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.
    22. 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.

  2. 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.

  3. Chollete, Loran & Ning, Cathy, 2009. "The Dependence Structure of Macroeconomic Variables in the US," UiS Working Papers in Economics and Finance 2009/31, University of Stavanger.

    Cited by:

    1. Jozef Barun'ik & Tobias Kley, 2015. "Quantile Coherency: A General Measure for Dependence between Cyclical Economic Variables," Papers 1510.06946, arXiv.org, revised Dec 2018.
    2. Salah Uddin, Gazi & Lucey, Brian & Rahman, Md Lutfur & Stenvall, David, 2024. "Quantile coherency across bonds, commodities, currencies, and equities," Journal of Commodity Markets, Elsevier, vol. 33(C).

  4. Cathy Ning, 2009. "Extreme Dependence in International Stock Markets," Working Papers 008, Toronto Metropolitan University, Department of Economics.

    Cited by:

    1. Chollete, Lorán & de la Peña, Victor & Lu, Ching-Chih, 2012. "International diversification: An extreme value approach," Journal of Banking & Finance, Elsevier, vol. 36(3), pages 871-885.
    2. Chollete, Loran & Ning, Cathy, 2009. "The Dependence Structure of Macroeconomic Variables in the US," UiS Working Papers in Economics and Finance 2009/31, University of Stavanger.
    3. Chollete, Lorán & de la Peña, Victor & Lu, Ching-Chih, 2011. "International diversification: A copula approach," Journal of Banking & Finance, Elsevier, vol. 35(2), pages 403-417, February.
    4. Warshaw, Evan, 2019. "Extreme dependence and risk spillovers across north american equity markets," The North American Journal of Economics and Finance, Elsevier, vol. 47(C), pages 237-251.
    5. Atskanov, Isuf, 2015. "Dynamic optimization of an investment portfolio on European stock markets using pair copulas," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 40(4), pages 84-105.
    6. Chollete, Loran & Pena, Victor de la & Lu, Ching-Chih, 2009. "International Diversification: A Copula Approach," UiS Working Papers in Economics and Finance 2009/27, University of Stavanger.
    7. Chollete, Loran & de la Pena , Victor & Lu, Ching-Chih, 2009. "International Diversification: An Extreme Value Approach," UiS Working Papers in Economics and Finance 2009/26, University of Stavanger.
    8. Muhammad Naeem & Hao Ji & Brunero Liseo, 2014. "Negative Return-Volume Relationship in Asian Stock Markets: Figarch-Copula Approach," Eurasian Journal of Economics and Finance, Eurasian Publications, vol. 2(2), pages 1-20.
    9. Henryk Gurgul & Artur Machno, 2014. "The optimal portfolio under VaR and ES," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 24(2), pages 59-79.
    10. Chollete, Loran & Ning, Cathy, 2010. "Asymmetric Dependence in US Financial Risk Factors?," UiS Working Papers in Economics and Finance 2011/2, University of Stavanger.
    11. Chollete, Loran & Ning, Cathy, 2012. "Asymmetric Dependence in the US Economy: Application to Money and the Phillips Curve," UiS Working Papers in Economics and Finance 2012/1, University of Stavanger.
    12. Tong, Bin & Wu, Chongfeng & Zhou, Chunyang, 2013. "Modeling the co-movements between crude oil and refined petroleum markets," Energy Economics, Elsevier, vol. 40(C), pages 882-897.

  5. Cathy Ning & Tony S. Wirjanto, 2008. "Extreme Return-Volume Dependence in East-Asian Stock Markets: A Copula Approach," Working Papers 08009, University of Waterloo, Department of Economics.

    Cited by:

    1. Kuang-Liang Chang, 2021. "A New Dynamic Mixture Copula Mechanism to Examine the Nonlinear and Asymmetric Tail Dependence Between Stock and Exchange Rate Returns," Computational Economics, Springer;Society for Computational Economics, vol. 58(4), pages 965-999, December.
    2. Ye, Cheng & Qiu, Yanjun & Lu, Guohao & Hou, Yawen, 2018. "Quantitative strategy for the Chinese commodity futures market based on a dynamic weighted money flow model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 512(C), pages 1009-1018.
    3. Wei Lin & Gloria González‐Rivera, 2019. "Extreme returns and intensity of trading," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 34(7), pages 1121-1140, November.
    4. Rossi, Eduardo & Santucci de Magistris, Paolo, 2013. "Long memory and tail dependence in trading volume and volatility," Journal of Empirical Finance, Elsevier, vol. 22(C), pages 94-112.
    5. Chen, Shiu-Sheng, 2012. "Revisiting the empirical linkages between stock returns and trading volume," MPRA Paper 36897, University Library of Munich, Germany.
    6. Sun, Changyou, 2013. "Price variation and volume dynamics of securitized timberlands," Forest Policy and Economics, Elsevier, vol. 27(C), pages 44-53.
    7. Ivan Medovikov, 2014. "Can Analysts Predict Rallies Better Than Crashes?," Papers 1405.3225, arXiv.org.
    8. Medovikov, Ivan, 2016. "When does the stock market listen to economic news? New evidence from copulas and news wires," Journal of Banking & Finance, Elsevier, vol. 65(C), pages 27-40.
    9. Reboredo, Juan C. & Tiwari, Aviral Kumar & Albulescu, Claudiu Tiberiu, 2015. "An analysis of dependence between Central and Eastern European stock markets," Economic Systems, Elsevier, vol. 39(3), pages 474-490.
    10. Xingjian Zheng & Dehua Shen, 2020. "The High-Volume Return Premium: Does it Really Exist in the Chinese Stock Market?," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 27(2), pages 213-230, June.
    11. Wang, Yi-Chiuan & Wu, Jyh-Lin & Lai, Yi-Hao, 2018. "New evidence on asymmetric return–volume dependence and extreme movements," Journal of Empirical Finance, Elsevier, vol. 45(C), pages 212-227.
    12. Ivan Medovikov, 2014. "When does the stock market listen to economic news? New evidence from copulas and news wires," Papers 1410.8427, arXiv.org.
    13. Naeem, Muhammad & Bouri, Elie & Boako, Gideon & Roubaud, David, 2020. "Tail dependence in the return-volume of leading cryptocurrencies," Finance Research Letters, Elsevier, vol. 36(C).
    14. Hongjun Zeng & Abdullahi D. Ahmed, 2022. "Market integration and volatility spillover across major East Asian stock and Bitcoin markets: an empirical assessment," International Journal of Managerial Finance, Emerald Group Publishing Limited, vol. 19(4), pages 772-802, August.
    15. Tong, Bin & Diao, Xundi & Wu, Chongfeng, 2015. "Modeling asymmetric and dynamic dependence of overnight and daytime returns: An empirical evidence from China Banking Sector," Economic Modelling, Elsevier, vol. 51(C), pages 366-382.
    16. Chu, Jeffrey & Chan, Stephen & Zhang, Yuanyuan, 2023. "An analysis of the return–volume relationship in decentralised finance (DeFi)," International Review of Economics & Finance, Elsevier, vol. 85(C), pages 236-254.
    17. Atskanov, Isuf, 2015. "Dynamic optimization of an investment portfolio on European stock markets using pair copulas," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 40(4), pages 84-105.
    18. Aida Karmous & Heni Boubaker & Lotfi Belkacem, 2021. "Forecasting Volatility for an Optimal Portfolio with Stylized Facts Using Copulas," Computational Economics, Springer;Society for Computational Economics, vol. 58(2), pages 461-482, August.
    19. Albulescu, Claudiu Tiberiu & Aubin, Christian & Goyeau, Daniel & Tiwari, Aviral Kumar, 2018. "Extreme co-movements and dependencies among major international exchange rates: A copula approach," The Quarterly Review of Economics and Finance, Elsevier, vol. 69(C), pages 56-69.
    20. Koubaa, Yosra & Slim, Skander, 2019. "The relationship between trading activity and stock market volatility: Does the volume threshold matter?," Economic Modelling, Elsevier, vol. 82(C), pages 168-184.
    21. Parab Narayan & Y. V. Reddy, 2017. "Exploring the Causal Relationship Between Stock Returns, Volume, and Turnover across Sectoral Indices in Indian Stock Market," Metamorphosis: A Journal of Management Research, , vol. 16(2), pages 122-140, December.
    22. Yamani, Ehab, 2023. "Return–volume nexus in financial markets: A survey of research," Research in International Business and Finance, Elsevier, vol. 65(C).
    23. Chen, Wang & Wei, Yu & Lang, Qiaoqi & Lin, Yu & Liu, Maojuan, 2014. "Financial market volatility and contagion effect: A copula–multifractal volatility approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 398(C), pages 289-300.
    24. Ezzat, Hassan & Kirkulak, Berna, 2014. "Information Arrival and Volatility: Evidence from the Saudi Arabia Stock Exchange (Tadawul)," MPRA Paper 61160, University Library of Munich, Germany.
    25. Muhammad Naeem & Hao Ji & Brunero Liseo, 2014. "Negative Return-Volume Relationship in Asian Stock Markets: Figarch-Copula Approach," Eurasian Journal of Economics and Finance, Eurasian Publications, vol. 2(2), pages 1-20.
    26. Bouri, Elie & Lau, Chi Keung Marco & Lucey, Brian & Roubaud, David, 2019. "Trading volume and the predictability of return and volatility in the cryptocurrency market," Finance Research Letters, Elsevier, vol. 29(C), pages 340-346.
    27. Kao, Yu-Sheng & Zhao, Kai & Chuang, Hwei-Lin & Ku, Yu-Cheng, 2024. "The asymmetric relationships between the Bitcoin futures’ return, volatility, and trading volume," International Review of Economics & Finance, Elsevier, vol. 89(PA), pages 524-542.
    28. Tiwari, Aviral Kumar & Adewuyi, Adeolu O. & Albulescu, Claudiu T. & Wohar, Mark E., 2020. "Empirical evidence of extreme dependence and contagion risk between main cryptocurrencies," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
    29. Kao, Yu-Sheng & Chuang, Hwei-Lin & Ku, Yu-Cheng, 2020. "The empirical linkages among market returns, return volatility, and trading volume: Evidence from the S&P 500 VIX Futures," The North American Journal of Economics and Finance, Elsevier, vol. 54(C).

Articles

  1. 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.
  2. Ning, Cathy, 2010. "Dependence structure between the equity market and the foreign exchange market-A copula approach," Journal of International Money and Finance, Elsevier, vol. 29(5), pages 743-759, September.

    Cited by:

    1. Tian, Maoxi & El Khoury, Rim & Alshater, Muneer M., 2023. "The nonlinear and negative tail dependence and risk spillovers between foreign exchange and stock markets in emerging economies," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 82(C).
    2. Sehgal, Sanjay & Pandey, Piyush & Diesting, Florent, 2017. "Examining dynamic currency linkages amongst South Asian economies: An empirical study," Research in International Business and Finance, Elsevier, vol. 42(C), pages 173-190.
    3. Jinan Liu & Apostolos Serletis, 2023. "Volatility and dependence in energy markets," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 47(1), pages 15-37, March.
    4. Sun, Changyou, 2013. "On the market risk of securitized timberlands," Journal of Forest Economics, Elsevier, vol. 19(2), pages 110-127.
    5. Kuang-Liang Chang, 2021. "A New Dynamic Mixture Copula Mechanism to Examine the Nonlinear and Asymmetric Tail Dependence Between Stock and Exchange Rate Returns," Computational Economics, Springer;Society for Computational Economics, vol. 58(4), pages 965-999, December.
    6. I. Medovikov S. & И. Медовиков С., 2019. "Могут ли фондовые аналитики предсказать рыночный риск? Новые сведения из теории копулы // Can Stock Analysts Predict Market Risk? New Evidence from Copula Theory," Финансы: теория и практика/Finance: Theory and Practice // Finance: Theory and Practice, ФГОБУВО Финансовый университет при Правительстве Российской Федерации // Financial University under The Government of Russian Federation, vol. 23(1), pages 38-48.
    7. Syed Abul, Basher & Salem, Nechi & Hui, Zhu, 2014. "Dependence patterns across Gulf Arab stock markets: a copula approach," MPRA Paper 56566, University Library of Munich, Germany.
    8. Sun, Xiaolei & Liu, Chang & Wang, Jun & Li, Jianping, 2020. "Assessing the extreme risk spillovers of international commodities on maritime markets: A GARCH-Copula-CoVaR approach," International Review of Financial Analysis, Elsevier, vol. 68(C).
    9. Chen, Lin & Wen, Fenghua & Li, Wanyang & Yin, Hua & Zhao, Lili, 2022. "Extreme risk spillover of the oil, exchange rate to Chinese stock market: Evidence from implied volatility indexes," Energy Economics, Elsevier, vol. 107(C).
    10. Chollete, Lorán & de la Peña, Victor & Lu, Ching-Chih, 2012. "International diversification: An extreme value approach," Journal of Banking & Finance, Elsevier, vol. 36(3), pages 871-885.
    11. Bouri, Elie & Gupta, Rangan & Lau, Chi Keung Marco & Roubaud, David & Wang, Shixuan, 2018. "Bitcoin and global financial stress: A copula-based approach to dependence and causality in the quantiles," The Quarterly Review of Economics and Finance, Elsevier, vol. 69(C), pages 297-307.
    12. Çekin, Semih Emre & Pradhan, Ashis Kumar & Tiwari, Aviral Kumar & Gupta, Rangan, 2020. "Measuring co-dependencies of economic policy uncertainty in Latin American countries using vine copulas," The Quarterly Review of Economics and Finance, Elsevier, vol. 76(C), pages 207-217.
    13. Walid, Chkili & Chaker, Aloui & Masood, Omar & Fry, John, 2011. "Stock market volatility and exchange rates in emerging countries: A Markov-state switching approach," Emerging Markets Review, Elsevier, vol. 12(3), pages 272-292, September.
    14. Li, Wei-Zhen & Zhai, Jin-Rui & Jiang, Zhi-Qiang & Wang, Gang-Jin & Zhou, Wei-Xing, 2022. "Predicting tail events in a RIA-EVT-Copula framework," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 600(C).
    15. Guglielmo Maria Caporale & John Hunter & Faek Menla Ali, 2013. "On the Linkages between Stock Prices and Exchange Rates: Evidence from the Banking Crisis of 2007-2010," Discussion Papers of DIW Berlin 1289, DIW Berlin, German Institute for Economic Research.
    16. Garcia-Jorcano, Laura & Benito, Sonia, 2020. "Studying the properties of the Bitcoin as a diversifying and hedging asset through a copula analysis: Constant and time-varying," Research in International Business and Finance, Elsevier, vol. 54(C).
    17. Laih, Yih-Wenn, 2014. "Measuring rank correlation coefficients between financial time series: A GARCH-copula based sequence alignment algorithm," European Journal of Operational Research, Elsevier, vol. 232(2), pages 375-382.
    18. Ülkü, Numan & Demirci, Ebru, 2012. "Joint dynamics of foreign exchange and stock markets in emerging Europe," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 22(1), pages 55-86.
    19. Stanislav Anatolyev & Vladimir Pyrlik, 2021. "Shrinkage for Gaussian and t Copulas in Ultra-High Dimensions," CERGE-EI Working Papers wp699, The Center for Economic Research and Graduate Education - Economics Institute, Prague.
    20. Ivan Medovikov, 2014. "Can Analysts Predict Rallies Better Than Crashes?," Papers 1405.3225, arXiv.org.
    21. Bai, Xiwen, 2021. "Tanker freight rates and economic policy uncertainty: A wavelet-based copula approach," Energy, Elsevier, vol. 235(C).
    22. Aloui, Riadh & Aïssa, Mohamed Safouane Ben & Hammoudeh, Shawkat & Nguyen, Duc Khuong, 2014. "Dependence and extreme dependence of crude oil and natural gas prices with applications to risk management," Energy Economics, Elsevier, vol. 42(C), pages 332-342.
    23. Chao Xu & Jinchuan Ke & Xiaojun Zhao & Xiaofang Zhao, 2020. "Multiscale Quantile Correlation Coefficient: Measuring Tail Dependence of Financial Time Series," Sustainability, MDPI, vol. 12(12), pages 1-24, June.
    24. Kumar, Satish & Tiwari, Aviral Kumar & Raheem, Ibrahim Dolapo & Hille, Erik, 2021. "Time-varying dependence structure between oil and agricultural commodity markets: A dependence-switching CoVaR copula approach," Resources Policy, Elsevier, vol. 72(C).
    25. Suleyman Hilmi Kal & Ferhat Arslaner & Nuran Arslaner, 2015. "The Dynamic Relationship Between Stock, Bond and Foreign Exchange Markets," Working Papers 1512, Research and Monetary Policy Department, Central Bank of the Republic of Turkey.
    26. Tachibana, Minoru, 2018. "Safe-haven and hedge currencies for the US, UK, and Euro area stock markets: A copula-based approach," Global Finance Journal, Elsevier, vol. 35(C), pages 82-96.
    27. Medovikov, Ivan, 2016. "When does the stock market listen to economic news? New evidence from copulas and news wires," Journal of Banking & Finance, Elsevier, vol. 65(C), pages 27-40.
    28. Irena Vodenska & Alexander P. Becker & Di Zhou & Dror Y. Kenett & H. Eugene Stanley & Shlomo Havlin, 2016. "Community Analysis of Global Financial Markets," Risks, MDPI, vol. 4(2), pages 1-15, May.
    29. Reboredo, Juan C. & Rivera-Castro, Miguel A. & Ugolini, Andrea, 2016. "Downside and upside risk spillovers between exchange rates and stock prices," Journal of Banking & Finance, Elsevier, vol. 62(C), pages 76-96.
    30. Reboredo, Juan C., 2012. "Modelling oil price and exchange rate co-movements," Journal of Policy Modeling, Elsevier, vol. 34(3), pages 419-440.
    31. Yutaka Kurihara & Akio Fukushima & Shinichiro Maeda, 2020. "Can Bitcoin’S Price Be A Predictor Of Stock Prices?," Noble International Journal of Economics and Financial Research, Noble Academic Publsiher, vol. 5(4), pages 50-55, April.
    32. Christos Agiakloglou & Anil Bera & Emmanouil Deligiannakis, 2022. "Evaluating measures of dependence for linearly generated nonlinear time series along with spurious correlation," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 46(3), pages 535-552, July.
    33. Ivan Medovikov, 2014. "When does the stock market listen to economic news? New evidence from copulas and news wires," Papers 1410.8427, arXiv.org.
    34. Tiwari, Aviral Kumar & Nasreen, Samia & Hammoudeh, Shawkat & Selmi, Refk, 2021. "Dynamic dependence of oil, clean energy and the role of technology companies: New evidence from copulas with regime switching," Energy, Elsevier, vol. 220(C).
    35. Wan, Li & Han, Liyan & Xu, Yang & Matousek, Roman, 2021. "Dynamic linkage between the Chinese and global stock markets: A normal mixture approach," Emerging Markets Review, Elsevier, vol. 49(C).
    36. Reboredo, Juan C., 2011. "How do crude oil prices co-move?: A copula approach," Energy Economics, Elsevier, vol. 33(5), pages 948-955, September.
    37. Aviral Kumar Tiwari & Sangram Keshari Jena & Satish Kumar & Erik Hille, 2022. "Is oil price risk systemic to sectoral equity markets of an oil importing country? Evidence from a dependence-switching copula delta CoVaR approach," Annals of Operations Research, Springer, vol. 315(1), pages 429-461, August.
    38. Ying-Ying Shen & Zhi-Qiang Jiang & Jun-Chao Ma & Gang-Jin Wang & Wei-Xing Zhou, 2022. "Sector connectedness in the Chinese stock markets," Empirical Economics, Springer, vol. 62(2), pages 825-852, February.
    39. Reboredo, Juan C., 2012. "Do food and oil prices co-move?," Energy Policy, Elsevier, vol. 49(C), pages 456-467.
    40. Aloui, Riadh & Gupta, Rangan & Miller, Stephen M., 2016. "Uncertainty and crude oil returns," Energy Economics, Elsevier, vol. 55(C), pages 92-100.
    41. Tong, Bin & Diao, Xundi & Wu, Chongfeng, 2015. "Modeling asymmetric and dynamic dependence of overnight and daytime returns: An empirical evidence from China Banking Sector," Economic Modelling, Elsevier, vol. 51(C), pages 366-382.
    42. Chung-Shin Liu & Meng-Shiuh Chang & Ximing Wu & Chin Man Chui, 2016. "Hedges or safe havens—revisit the role of gold and USD against stock: a multivariate extended skew- copula approach," Quantitative Finance, Taylor & Francis Journals, vol. 16(11), pages 1763-1789, November.
    43. David E. Allen, 2022. "Cryptocurrencies, Diversification and the COVID-19 Pandemic," JRFM, MDPI, vol. 15(3), pages 1-25, February.
    44. Murad A. BEIN & Gulcay TUNA, 2016. "Comparing Spillover Effects Among Emerging Markets With A Higher (Lower) Share Of Commodity Exports: Evidence From The Two Major Crises," ECONOMIC COMPUTATION AND ECONOMIC CYBERNETICS STUDIES AND RESEARCH, Faculty of Economic Cybernetics, Statistics and Informatics, vol. 50(3), pages 265-284.
    45. Wu, Chih-Chiang & Wu, Chang-Che, 2017. "The asymmetry in carry trade and the U.S. dollar," The Quarterly Review of Economics and Finance, Elsevier, vol. 65(C), pages 304-313.
    46. Chollete, Loran & Ning, Cathy, 2009. "The Dependence Structure of Macroeconomic Variables in the US," UiS Working Papers in Economics and Finance 2009/31, University of Stavanger.
    47. Jia, Fei & Shen, Yao & Ren, Junfan & Xu, Xiangyun, 2021. "The impact of offshore exchange rate expectations on onshore exchange rates: The case of Chinese RMB," The North American Journal of Economics and Finance, Elsevier, vol. 56(C).
    48. Zhu, Hui-Ming & Li, Rong & Li, Sufang, 2014. "Modelling dynamic dependence between crude oil prices and Asia-Pacific stock market returns," International Review of Economics & Finance, Elsevier, vol. 29(C), pages 208-223.
    49. Ojea-Ferreiro, Javier & Reboredo, Juan C., 2022. "Exchange rates and the global transmission of equity market shocks," Economic Modelling, Elsevier, vol. 114(C).
    50. Muteba Mwamba, John & Mokwena, Paula, 2013. "International diversification and dependence structure of equity portfolios during market crashes: the Archimedean copula approach," MPRA Paper 64384, University Library of Munich, Germany.
    51. Mei Qiu & Pinfold & Rose, 2015. "A currency preferential approach to international equity investment," Applied Economics, Taylor & Francis Journals, vol. 47(49), pages 5247-5261, October.
    52. Cumperayot, Phornchanok & Kouwenberg, Roy, 2013. "Early warning systems for currency crises: A multivariate extreme value approach," Journal of International Money and Finance, Elsevier, vol. 36(C), pages 151-171.
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    101. Dirk G Baur & Isaac Miyakawa, 2013. "International Investors, Exchange Rates and Equity Prices," Working Paper Series 178, Finance Discipline Group, UTS Business School, University of Technology, Sydney.
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    103. Tiwari, Aviral Kumar & Adewuyi, Adeolu O. & Albulescu, Claudiu T. & Wohar, Mark E., 2020. "Empirical evidence of extreme dependence and contagion risk between main cryptocurrencies," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
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  3. Leo Michelis & Cathy Ning, 2010. "The dependence structure between the Canadian stock market and the USD/CAD exchange rate: a copula approach," Canadian Journal of Economics, Canadian Economics Association, vol. 43(3), pages 1016-1039, August.

    Cited by:

    1. Tian, Maoxi & El Khoury, Rim & Alshater, Muneer M., 2023. "The nonlinear and negative tail dependence and risk spillovers between foreign exchange and stock markets in emerging economies," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 82(C).
    2. Sehgal, Sanjay & Pandey, Piyush & Diesting, Florent, 2017. "Examining dynamic currency linkages amongst South Asian economies: An empirical study," Research in International Business and Finance, Elsevier, vol. 42(C), pages 173-190.
    3. Sun, Changyou, 2013. "On the market risk of securitized timberlands," Journal of Forest Economics, Elsevier, vol. 19(2), pages 110-127.
    4. Kuang-Liang Chang, 2021. "A New Dynamic Mixture Copula Mechanism to Examine the Nonlinear and Asymmetric Tail Dependence Between Stock and Exchange Rate Returns," Computational Economics, Springer;Society for Computational Economics, vol. 58(4), pages 965-999, December.
    5. Chen, Lin & Wen, Fenghua & Li, Wanyang & Yin, Hua & Zhao, Lili, 2022. "Extreme risk spillover of the oil, exchange rate to Chinese stock market: Evidence from implied volatility indexes," Energy Economics, Elsevier, vol. 107(C).
    6. Çekin, Semih Emre & Pradhan, Ashis Kumar & Tiwari, Aviral Kumar & Gupta, Rangan, 2020. "Measuring co-dependencies of economic policy uncertainty in Latin American countries using vine copulas," The Quarterly Review of Economics and Finance, Elsevier, vol. 76(C), pages 207-217.
    7. Ivan Medovikov, 2014. "Can Analysts Predict Rallies Better Than Crashes?," Papers 1405.3225, arXiv.org.
    8. Bai, Xiwen, 2021. "Tanker freight rates and economic policy uncertainty: A wavelet-based copula approach," Energy, Elsevier, vol. 235(C).
    9. Suleyman Hilmi Kal & Ferhat Arslaner & Nuran Arslaner, 2015. "The Dynamic Relationship Between Stock, Bond and Foreign Exchange Markets," Working Papers 1512, Research and Monetary Policy Department, Central Bank of the Republic of Turkey.
    10. Medovikov, Ivan, 2016. "When does the stock market listen to economic news? New evidence from copulas and news wires," Journal of Banking & Finance, Elsevier, vol. 65(C), pages 27-40.
    11. Irena Vodenska & Alexander P. Becker & Di Zhou & Dror Y. Kenett & H. Eugene Stanley & Shlomo Havlin, 2016. "Community Analysis of Global Financial Markets," Risks, MDPI, vol. 4(2), pages 1-15, May.
    12. Reboredo, Juan C. & Rivera-Castro, Miguel A. & Ugolini, Andrea, 2016. "Downside and upside risk spillovers between exchange rates and stock prices," Journal of Banking & Finance, Elsevier, vol. 62(C), pages 76-96.
    13. Yutaka Kurihara & Akio Fukushima & Shinichiro Maeda, 2020. "Can Bitcoin’S Price Be A Predictor Of Stock Prices?," Noble International Journal of Economics and Financial Research, Noble Academic Publsiher, vol. 5(4), pages 50-55, April.
    14. Ivan Medovikov, 2014. "When does the stock market listen to economic news? New evidence from copulas and news wires," Papers 1410.8427, arXiv.org.
    15. Wan, Li & Han, Liyan & Xu, Yang & Matousek, Roman, 2021. "Dynamic linkage between the Chinese and global stock markets: A normal mixture approach," Emerging Markets Review, Elsevier, vol. 49(C).
    16. David E. Allen, 2022. "Cryptocurrencies, Diversification and the COVID-19 Pandemic," JRFM, MDPI, vol. 15(3), pages 1-25, February.
    17. Lee, Chien-Chiang & Chang, Chi-Hung & Chen, Mei-Ping, 2015. "Industry co-movements of American depository receipts: Evidences from the copula approaches," Economic Modelling, Elsevier, vol. 46(C), pages 301-314.
    18. Wu, Chih-Chiang & Chiu, Junmao, 2017. "Economic evaluation of asymmetric and price range information in gold and general financial markets," Journal of International Money and Finance, Elsevier, vol. 74(C), pages 53-68.
    19. Adlane Haffar & Éric Le Fur, 2022. "Dependence structure of CAT bonds and portfolio diversification: a copula-GARCH approach," Journal of Asset Management, Palgrave Macmillan, vol. 23(4), pages 297-309, July.
    20. Tachibana, Minoru, 2018. "Relationship between stock and currency markets conditional on the US stock returns: A vine copula approach," Journal of Multinational Financial Management, Elsevier, vol. 46(C), pages 75-106.
    21. Rehman, Mobeen Ur & Katsiampa, Paraskevi & Zeitun, Rami & Vo, Xuan Vinh, 2023. "Conditional dependence structure and risk spillovers between Bitcoin and fiat currencies," Emerging Markets Review, Elsevier, vol. 55(C).
    22. Hammami, Algia & Ghenimi, Ameni & Bouri, Abdelfatteh, 2019. "Oil prices, US exchange rates, and stock market: evidence from Jordan as a net oil importer," MPRA Paper 94570, University Library of Munich, Germany.
    23. BenSaïda, Ahmed, 2018. "The contagion effect in European sovereign debt markets: A regime-switching vine copula approach," International Review of Financial Analysis, Elsevier, vol. 58(C), pages 153-165.
    24. Sanjay Sehgal & Piyush Pandey & Florent Deisting, 2018. "Stock Market Integration Dynamics and its Determinants in the East Asian Economic Community Region," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 16(2), pages 389-425, June.
    25. Yi-Chiuan Wang & Yi-hao Lai & Jyh-Lin Wu, 2024. "Asymmetries in risk spillovers between currency and stock markets: Evidence from the CoVaR-copula approach," Review of Quantitative Finance and Accounting, Springer, vol. 63(3), pages 1083-1119, October.
    26. Davood Pirayesh Neghab & Mucahit Cevik & M. I. M. Wahab, 2023. "Explaining Exchange Rate Forecasts with Macroeconomic Fundamentals Using Interpretive Machine Learning," Papers 2303.16149, arXiv.org.
    27. Boako, Gideon & Alagidede, Paul, 2017. "Currency price risk and stock market returns in Africa: Dependence and downside spillover effects with stochastic copulas," Journal of Multinational Financial Management, Elsevier, vol. 41(C), pages 92-114.
    28. Chiu-Lan Chang & Paul L. Hsueh, 2013. "An Investigation of the Flight-to-Quality Effect: Evidence from Asia-Pacific Countries," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 49(S4), pages 53-69, September.
    29. Ma, Xiuying & Yang, Zhihua & Xu, Xiangyun & Wang, Chengqi, 2018. "The impact of Chinese financial markets on commodity currency exchange rates," Global Finance Journal, Elsevier, vol. 37(C), pages 186-198.
    30. Liao, Jia & Qian, Qi & Xu, Xiangyun, 2018. "Whether the fluctuation of China’s financial markets have impact on global commodity prices?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 503(C), pages 1030-1040.

  4. Ning, Cathy & Wirjanto, Tony S., 2009. "Extreme return-volume dependence in East-Asian stock markets: A copula approach," Finance Research Letters, Elsevier, vol. 6(4), pages 202-209, December.
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  5. John Knight & Cathy Q. Ning, 2008. "Estimation of the stochastic conditional duration model via alternative methods," Econometrics Journal, Royal Economic Society, vol. 11(3), pages 593-616, November.

    Cited by:

    1. 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.
    2. Dingan Feng & Peter X.-K. Song & Tony S. Wirjanto, 2008. "Time-Deformation Modeling Of Stock Returns Directed By Duration Processes," Working Papers 08010, University of Waterloo, Department of Economics.
    3. BAUWENS, Luc & HAUTSCH, Nikolaus, 2009. "Modelling financial high frequency data using point processes," LIDAM Reprints CORE 2123, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    4. Galli, Fausto, 2014. "Stochastic conditonal range, a latent variable model for financial volatility," MPRA Paper 54030, University Library of Munich, Germany.
    5. 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.
    6. 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.
    7. 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.
    8. Simos G. Meintanis & Bojana Milošević & Marko Obradović, 2020. "Goodness-of-fit tests in conditional duration models," Statistical Papers, Springer, vol. 61(1), pages 123-140, February.
    9. 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.
    10. 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.
    11. 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.
    12. Galli, Fausto, 2014. "Stochastic conditonal range, a latent variable model for financial volatility," MPRA Paper 54841, University Library of Munich, Germany.
    13. 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.

  6. 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. 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).
    7. 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).
    8. Wu, Xinyu & Wang, Xiaona, 2020. "Forecasting volatility using realized stochastic volatility model with time-varying leverage effect," Finance Research Letters, Elsevier, vol. 34(C).

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