IDEAS home Printed from https://ideas.repec.org/a/eee/finana/v48y2016icp31-45.html
   My bibliography  Save this article

Modeling the dependence structures of financial assets through the Copula Quantile-on-Quantile approach

Author

Listed:
  • Sim, Nicholas

Abstract

This paper considers a new approach of analyzing asset dependence by estimating how the distributions (in particular, quantiles) of assets are related. Combining the techniques of quantile regression and copula modeling, I propose the Copula Quantile-on-Quantile Regression approach to estimate the correlation that is associated with the quantiles of asset returns, which is able to uncover obscure nonlinear characteristics in asset dependence. The estimation procedure proposed here can also be used for analyzing dependence structures in other settings, such as for studying how macroeconomic covariates are nonlinearly related by looking at the relationship between their quantiles.

Suggested Citation

  • Sim, Nicholas, 2016. "Modeling the dependence structures of financial assets through the Copula Quantile-on-Quantile approach," International Review of Financial Analysis, Elsevier, vol. 48(C), pages 31-45.
  • Handle: RePEc:eee:finana:v:48:y:2016:i:c:p:31-45
    DOI: 10.1016/j.irfa.2016.09.004
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1057521916301272
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.irfa.2016.09.004?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Chen, Xiaohong & Fan, Yanqin, 2006. "Estimation of copula-based semiparametric time series models," Journal of Econometrics, Elsevier, vol. 130(2), pages 307-335, February.
    2. Andrew Ang & Geert Bekaert, 2002. "International Asset Allocation With Regime Shifts," The Review of Financial Studies, Society for Financial Studies, vol. 15(4), pages 1137-1187.
    3. Eric Bouye & Mark Salmon, 2009. "Dynamic copula quantile regressions and tail area dynamic dependence in Forex markets," The European Journal of Finance, Taylor & Francis Journals, vol. 15(7-8), pages 721-750.
    4. Rui Albuquerque & Clara Vega, 2009. "Economic News and International Stock Market Co-movement," Review of Finance, European Finance Association, vol. 13(3), pages 401-465.
    5. Ma, Lingjie & Koenker, Roger, 2006. "Quantile regression methods for recursive structural equation models," Journal of Econometrics, Elsevier, vol. 134(2), pages 471-506, October.
    6. Connolly, Robert & Stivers, Chris & Sun, Licheng, 2005. "Stock Market Uncertainty and the Stock-Bond Return Relation," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 40(1), pages 161-194, March.
    7. Lutz Kilian, 2009. "Pitfalls in Estimating Asymmetric Effects of Energy Price Shocks," 2009 Meeting Papers 473, Society for Economic Dynamics.
    8. Koenker,Roger, 2005. "Quantile Regression," Cambridge Books, Cambridge University Press, number 9780521845731.
    9. Chen, Xiaohong & Fan, Yanqin & Patton, Andrew J., 2004. "Simple tests for models of dependence between multiple financial time series, with applications to U.S. equity returns and exchange rates," LSE Research Online Documents on Economics 24681, London School of Economics and Political Science, LSE Library.
    10. Chin Man Chui & Jian Yang, 2012. "Extreme Correlation of Stock and Bond Futures Markets: International Evidence," The Financial Review, Eastern Finance Association, vol. 47(3), pages 565-587, August.
    11. Yanqin Fan & Xiaohong Chen & Andrew Patton, 2004. "(IAM Series No 003) Simple Tests for Models of Dependence Between Multiple Financial Time Series, with Applications to U.S. Equity Returns and Exchange Rates," FMG Discussion Papers dp483, Financial Markets Group.
    12. Shanken, Jay & Weinstein, Mark I., 2006. "Economic forces and the stock market revisited," Journal of Empirical Finance, Elsevier, vol. 13(2), pages 129-144, March.
    13. Massimo Guidolin & Allan Timmermann, 2005. "Economic Implications of Bull and Bear Regimes in UK Stock and Bond Returns," Economic Journal, Royal Economic Society, vol. 115(500), pages 111-143, January.
    14. Lutz Kilian & Cheolbeom Park, 2009. "The Impact Of Oil Price Shocks On The U.S. Stock Market," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 50(4), pages 1267-1287, November.
    15. Xiaohong Chen & Roger Koenker & Zhijie Xiao, 2009. "Copula-based nonlinear quantile autoregression," Econometrics Journal, Royal Economic Society, vol. 12(s1), pages 50-67, January.
    16. Koenker, Roger & Bassett, Gilbert, Jr, 1982. "Robust Tests for Heteroscedasticity Based on Regression Quantiles," Econometrica, Econometric Society, vol. 50(1), pages 43-61, January.
    17. Ang, Andrew & Chen, Joseph, 2002. "Asymmetric correlations of equity portfolios," Journal of Financial Economics, Elsevier, vol. 63(3), pages 443-494, March.
    18. Sim, Nicholas & Zhou, Hongtao, 2015. "Oil prices, US stock return, and the dependence between their quantiles," Journal of Banking & Finance, Elsevier, vol. 55(C), pages 1-8.
    19. Jon Wongswan, 2006. "Transmission of Information across International Equity Markets," The Review of Financial Studies, Society for Financial Studies, vol. 19(4), pages 1157-1189.
    20. Ser-Huang Poon, 2004. "Extreme Value Dependence in Financial Markets: Diagnostics, Models, and Financial Implications," The Review of Financial Studies, Society for Financial Studies, vol. 17(2), pages 581-610.
    21. Krishnan, C.N.V. & Petkova, Ralitsa & Ritchken, Peter, 2009. "Correlation risk," Journal of Empirical Finance, Elsevier, vol. 16(3), pages 353-367, June.
    22. Longin, Francois & Solnik, Bruno, 1995. "Is the correlation in international equity returns constant: 1960-1990?," Journal of International Money and Finance, Elsevier, vol. 14(1), pages 3-26, February.
    23. James Peery Cover, 1992. "Asymmetric Effects of Positive and Negative Money-Supply Shocks," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 107(4), pages 1261-1282.
    24. Engle, Robert, 2002. "Dynamic Conditional Correlation: A Simple Class of Multivariate Generalized Autoregressive Conditional Heteroskedasticity Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(3), pages 339-350, July.
    25. Okimoto, Tatsuyoshi, 2008. "New Evidence of Asymmetric Dependence Structures in International Equity Markets," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 43(3), pages 787-815, September.
    26. Andrew J. Patton, 2006. "Modelling Asymmetric Exchange Rate Dependence," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 47(2), pages 527-556, May.
    27. Koenker, Roger W & Bassett, Gilbert, Jr, 1978. "Regression Quantiles," Econometrica, Econometric Society, vol. 46(1), pages 33-50, January.
    28. François Longin & Bruno Solnik, 2001. "Extreme Correlation of International Equity Markets," Journal of Finance, American Finance Association, vol. 56(2), pages 649-676, April.
    29. Janet E. Heffernan & Jonathan A. Tawn, 2004. "A conditional approach for multivariate extreme values (with discussion)," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 66(3), pages 497-546, August.
    30. 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.
    31. Ling Hu, 2006. "Dependence patterns across financial markets: a mixed copula approach," Applied Financial Economics, Taylor & Francis Journals, vol. 16(10), pages 717-729.
    32. Balvers, Ronald J & Cosimano, Thomas F & McDonald, Bill, 1990. "Predicting Stock Returns in an Efficient Market," Journal of Finance, American Finance Association, vol. 45(4), pages 1109-1128, September.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Ahmed, Walid M.A., 2021. "How do Islamic equity markets respond to good and bad volatility of cryptocurrencies? The case of Bitcoin," Pacific-Basin Finance Journal, Elsevier, vol. 70(C).
    2. Bouri, Elie & Kachacha, Imad & Roubaud, David, 2020. "Oil market conditions and sovereign risk in MENA oil exporters and importers," Energy Policy, Elsevier, vol. 137(C).
    3. Al-Yahyaee, Khamis Hamed & Shahzad, Syed Jawad Hussain & Mensi, Walid, 2020. "Tail dependence structures between economic policy uncertainty and foreign exchange markets: Nonparametric quantiles methods," International Economics, Elsevier, vol. 161(C), pages 66-82.
    4. Syed jawad hussain Shahzad & Saba Ameer & Muhammad Shahbaz, 2016. "Disaggregating the correlation under bearish and bullish markets: A Quantile-quantile approach," Economics Bulletin, AccessEcon, vol. 36(4), pages 2465-2473.
    5. Shahzad, Syed Jawad Hussain & Mensi, Walid & Hammoudeh, Shawkat & Sohail, Asiya & Al-Yahyaee, Khamis Hamed, 2019. "Does gold act as a hedge against different nuances of inflation? Evidence from Quantile-on-Quantile and causality-in- quantiles approaches," Resources Policy, Elsevier, vol. 62(C), pages 602-615.
    6. Iqbal, Najaf & Fareed, Zeeshan & Wan, Guangcai & Shahzad, Farrukh, 2021. "Asymmetric nexus between COVID-19 outbreak in the world and cryptocurrency market," International Review of Financial Analysis, Elsevier, vol. 73(C).
    7. Wu, Bi-Bo, 2021. "The dynamics of oil on China’s commodity sectors: What can we learn from a quantile perspective?," Journal of Commodity Markets, Elsevier, vol. 23(C).
    8. Huilian Huang & Tao Xiong, 2023. "A good hedge or safe haven? The hedging ability of China's commodity futures market under extreme market conditions," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 43(7), pages 968-1035, July.
    9. Labidi, Chiaz & Rahman, Md Lutfur & Hedström, Axel & Uddin, Gazi Salah & Bekiros, Stelios, 2018. "Quantile dependence between developed and emerging stock markets aftermath of the global financial crisis," International Review of Financial Analysis, Elsevier, vol. 59(C), pages 179-211.
    10. Sui, Meng & Rengifo, Erick W. & Court, Eduardo, 2021. "Gold, inflation and exchange rate in dollarized economies – A comparative study of Turkey, Peru and the United States," International Review of Economics & Finance, Elsevier, vol. 71(C), pages 82-99.
    11. Ling Peng & Dong Han, 2021. "The Convergence Rate of High-Dimensional Sample Quantiles for φ -Mixing Observation Sequences," Mathematics, MDPI, vol. 9(6), pages 1-8, March.
    12. Xolani Sibande & Rangan Gupta & Riza Demirer & Elie Bouri, 2023. "Investor Sentiment and (Anti) Herding in the Currency Market: Evidence from Twitter Feed Data," Journal of Behavioral Finance, Taylor & Francis Journals, vol. 24(1), pages 56-72, January.
    13. Hussain Shahzad, Syed Jawad & Raza, Naveed & Shahbaz, Muhammad & Ali, Azwadi, 2017. "Dependence of stock markets with gold and bonds under bullish and bearish market states," Resources Policy, Elsevier, vol. 52(C), pages 308-319.
    14. Urom, Christian & Abid, Ilyes & Guesmi, Khaled & Chevallier, Julien, 2020. "Quantile spillovers and dependence between Bitcoin, equities and strategic commodities," Economic Modelling, Elsevier, vol. 93(C), pages 230-258.
    15. Yang, Dong-Xiao & Wu, Bi-Bo & Tong, Jing-Yang, 2021. "Dynamics and causality of oil price shocks on commodities: Quantile-on-quantile and causality-in-quantiles methods," Resources Policy, Elsevier, vol. 74(C).
    16. Walid Mensi & Debasish Maitra & Refk Selmi & Xuan Vinh Vo, 2023. "Extreme dependencies and spillovers between gold and stock markets: evidence from MENA countries," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-27, December.
    17. Al-Yahyaee, Khamis Hamed & Mensi, Walid & Maitra, Debasish & Al-Jarrah, Idries Mohammad Wanas, 2019. "Portfolio management and dependencies among precious metal markets: Evidence from a Copula quantile-on-quantile approach," Resources Policy, Elsevier, vol. 64(C).
    18. Chen, Hao & Xu, Chao, 2022. "The impact of cryptocurrencies on China's carbon price variation during COVID-19: A quantile perspective," Technological Forecasting and Social Change, Elsevier, vol. 183(C).
    19. Hau, Liya & Zhu, Huiming & Huang, Rui & Ma, Xiang, 2020. "Heterogeneous dependence between crude oil price volatility and China’s agriculture commodity futures: Evidence from quantile-on-quantile regression," Energy, Elsevier, vol. 213(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Dimic, Nebojsa & Piljak, Vanja & Swinkels, Laurens & Vulanovic, Milos, 2021. "The structure and degree of dependence in government bond markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 74(C).
    2. Cerrato, Mario & Crosby, John & Kim, Minjoo & Zhao, Yang, 2015. "US Monetary and Fiscal Policies - Conflict or Cooperation?," SIRE Discussion Papers 2015-78, Scottish Institute for Research in Economics (SIRE).
    3. Cerrato, Mario & Crosby, John & Kim, Minjoo & Zhao, Yang, 2015. "US Monetary and Fiscal Policies - Conflict or Cooperation?," 2007 Annual Meeting, July 29-August 1, 2007, Portland, Oregon TN 2015-78, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    4. Mario Cerrato & John Crosby & Minjoo Kim & Yang Zhao, 2015. "Modeling Dependence Structure and Forecasting Market Risk with Dynamic Asymmetric Copula," Working Papers 2015_15, Business School - Economics, University of Glasgow.
    5. Anandadeep Mandal & Sunil S. Poshakwale & Gabriel J. Power, 2021. "Do investors gain from forecasting the asymmetric return co‐movements of financial and real assets?," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(3), pages 3246-3268, July.
    6. Chollete, Loran & Ning, Cathy, 2010. "Asymmetric Dependence in US Financial Risk Factors?," UiS Working Papers in Economics and Finance 2011/2, University of Stavanger.
    7. 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.
    8. Baur, Dirk G., 2013. "The structure and degree of dependence: A quantile regression approach," Journal of Banking & Finance, Elsevier, vol. 37(3), pages 786-798.
    9. Refk Selmi & Christos Kollias & Stephanos Papadamou & Rangan Gupta, 2017. "A Copula-Based Quantile-on-Quantile Regression Approach to Modeling Dependence Structure between Stock and Bond Returns: Evidence from Historical Data of India, South Africa, UK and US," Working Papers 201747, University of Pretoria, Department of Economics.
    10. Andersen, Torben G. & Bollerslev, Tim & Christoffersen, Peter F. & Diebold, Francis X., 2013. "Financial Risk Measurement for Financial Risk Management," Handbook of the Economics of Finance, in: G.M. Constantinides & M. Harris & R. M. Stulz (ed.), Handbook of the Economics of Finance, volume 2, chapter 0, pages 1127-1220, Elsevier.
    11. Martin Hoesli & Kustrim Reka, 2013. "Volatility Spillovers, Comovements and Contagion in Securitized Real Estate Markets," The Journal of Real Estate Finance and Economics, Springer, vol. 47(1), pages 1-35, July.
    12. Sim, Nicholas & Zhou, Hongtao, 2015. "Oil prices, US stock return, and the dependence between their quantiles," Journal of Banking & Finance, Elsevier, vol. 55(C), pages 1-8.
    13. Mensah, Jones Odei & Premaratne, Gamini, 2014. "Dependence patterns among Banking Sectors in Asia: A Copula Approach," MPRA Paper 60119, University Library of Munich, Germany.
    14. Cerrato, Mario & Crosby, John & Kim, Minjoo & Zhao, Yang, 2014. "Modeling Dependence Structure and Forecasting Portfolio Value-at-Risk with Dynamic Copulas," SIRE Discussion Papers 2015-25, Scottish Institute for Research in Economics (SIRE).
    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. 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.
    17. Udichibarna Bose & Ronald MacDonald & Serafeim Tsoukas, 2014. "The role of education in equity portfolios during the recent financial crisis," Working Papers 2014_17, Business School - Economics, University of Glasgow.
    18. 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.
    19. Jian Zhou & Yanmin Gao, 2012. "Tail Dependence in International Real Estate Securities Markets," The Journal of Real Estate Finance and Economics, Springer, vol. 45(1), pages 128-151, June.
    20. Cerrato, Mario & Crosby, John & Kim, Minjoo & Zhao, Yang, 2014. "Modeling Dependence Structure and Forecasting Portfolio Value-at-Risk with Dynamic Copulas," 2007 Annual Meeting, July 29-August 1, 2007, Portland, Oregon TN 2015-25, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).

    More about this item

    Keywords

    Asset returns; Australia; Copula; Correlation; Quantile regression;
    All these keywords.

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • F3 - International Economics - - International Finance
    • G1 - Financial Economics - - General Financial Markets

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:finana:v:48:y:2016:i:c:p:31-45. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/inca/620166 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.