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Multivariate time-varying parameter modelling for stock markets

Author

Listed:
  • Serdar Neslihanoglu

    (Eskisehir Osmangazi University)

  • Stelios Bekiros

    (European University Institute
    Wilfrid Laurier University)

  • John McColl

    (University of Glasgow)

  • Duncan Lee

    (University of Glasgow)

Abstract

This paper evaluates the appropriateness of a Linear Market Model (LMM) which allows for systematic covariance (beta) risk. The performance of LMM will be compared against two extensions, a comparison having yet to be undertaken in the literature. The first extension is the Time-varying Linear Market Model (Tv-LMM) which allows for time-varying systematic covariance risk in the form of a mean reverting state space model via the Kalman filter. The second extension is the multivariate Time-varying Linear Market Model (MTv-LMM) which allows for the time-varying systematic covariance risk of country stock market correlation structure via the multivariate KFMR. The comparison between LMM, Tv-LMM and MTv-LMM, is implemented utilising weekly data collected from several developed and emerging markets for the periods; before and after financial crisis in October 2008, and forecasting 2 years forwards. The empirical findings of that process overwhelmingly support the use of the Multivariate Time-varying Linear Market Model (MTv-LMM) when modelling and forecasting stock market returns, especially for developed stock markets.

Suggested Citation

  • Serdar Neslihanoglu & Stelios Bekiros & John McColl & Duncan Lee, 2021. "Multivariate time-varying parameter modelling for stock markets," Empirical Economics, Springer, vol. 61(2), pages 947-972, August.
    • Handle: RePEc:spr:empeco:v:61:y:2021:i:2:d:10.1007_s00181-020-01896-2
    DOI: 10.1007/s00181-020-01896-2
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    as
    1. Hansen, Lars Peter & Jagannathan, Ravi, 1997. "Assessing Specification Errors in Stochastic Discount Factor Models," Journal of Finance, American Finance Association, vol. 52(2), pages 557-590, June.
    2. Ping Wang & Tomoe Moore, 2008. "Stock Market Integration For The Transition Economies: Time‐Varying Conditional Correlation Approach," Manchester School, University of Manchester, vol. 76(s1), pages 116-133, September.
    3. Robert D. Brooks & Robert W. Faff & Michael D. McKenzie, 1998. "Time†Varying Beta Risk of Australian Industry Portfolios: A Comparison of Modelling Techniques," Australian Journal of Management, Australian School of Business, vol. 23(1), pages 1-22, June.
    4. Wen-Ling Lin & Takatoshi Ito, 1994. "Price Volatility and Volume Spillovers between the Tokyo and New York Stock Markets," NBER Chapters, in: The Internationalization of Equity Markets, pages 309-343, National Bureau of Economic Research, Inc.
    5. Darrell Duffie & David R. Skeie & James Vickery, 2013. "A sampling-window approach to transactions-based Libor fixing," Staff Reports 596, Federal Reserve Bank of New York.
    6. Serdar Neslihanoglu & Vasilios Sogiakas & John H. McColl & Duncan Lee, 2017. "Nonlinearities in the CAPM: Evidence from Developed and Emerging Markets," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 36(8), pages 867-897, December.
    7. Harvey, Campbell R, 1995. "Predictable Risk and Returns in Emerging Markets," The Review of Financial Studies, Society for Financial Studies, vol. 8(3), pages 773-816.
    8. Malliaris, M.E., 2012. "Comparison Of Currency Movement Before And After October 2008," The Journal of Economic Asymmetries, Elsevier, vol. 9(2), pages 45-57.
    9. Algieri, Bernardina, 2012. "Price Volatility, Speculation and Excessive Speculation in Commodity Markets: sheep or shepherd behaviour?," Discussion Papers 124390, University of Bonn, Center for Development Research (ZEF).
    10. William F. Sharpe, 1964. "Capital Asset Prices: A Theory Of Market Equilibrium Under Conditions Of Risk," Journal of Finance, American Finance Association, vol. 19(3), pages 425-442, September.
    11. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-144, January.
    12. Chiang, Thomas C. & Jeon, Bang Nam & Li, Huimin, 2007. "Dynamic correlation analysis of financial contagion: Evidence from Asian markets," Journal of International Money and Finance, Elsevier, vol. 26(7), pages 1206-1228, November.
    13. Barnett, Alina & Mumtaz, Haroon & Theodoridis, Konstantinos, 2014. "Forecasting UK GDP growth and inflation under structural change. A comparison of models with time-varying parameters," International Journal of Forecasting, Elsevier, vol. 30(1), pages 129-143.
    14. Ronald Doeswijk & Trevin Lam & Laurens Swinkels, 0. "Historical Returns of the Market Portfolio," The Review of Asset Pricing Studies, Society for Financial Studies, vol. 10(3), pages 521-567.
    15. Gibbons, Michael R & Ross, Stephen A & Shanken, Jay, 1989. "A Test of the Efficiency of a Given Portfolio," Econometrica, Econometric Society, vol. 57(5), pages 1121-1152, September.
    16. Sascha Mergner & Jan Bulla, 2008. "Time-varying beta risk of Pan-European industry portfolios: A comparison of alternative modeling techniques," The European Journal of Finance, Taylor & Francis Journals, vol. 14(8), pages 771-802.
    17. Robert W. Faff & David Hillier & Joseph Hillier, 2000. "Time Varying Beta Risk: An Analysis of Alternative Modelling Techniques," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 27(5‐6), pages 523-554, June.
    18. Saleem, Kashif, 2009. "International linkage of the Russian market and the Russian financial crisis: A multivariate GARCH analysis," Research in International Business and Finance, Elsevier, vol. 23(3), pages 243-256, September.
    19. Bekaert, Geert & Harvey, Campbell R., 1997. "Emerging equity market volatility," Journal of Financial Economics, Elsevier, vol. 43(1), pages 29-77, January.
    20. MacKinlay, A Craig & Richardson, Matthew P, 1991. "Using Generalized Method of Moments to Test Mean-Variance Efficiency," Journal of Finance, American Finance Association, vol. 46(2), pages 511-527, June.
    21. R. D. Brooks & R. W. Faff & M. McKenzie, 2002. "Time varying country risk: an assessment of alternative modelling techniques," The European Journal of Finance, Taylor & Francis Journals, vol. 8(3), pages 249-274.
    22. Santos, André A.P. & Moura, Guilherme V., 2014. "Dynamic factor multivariate GARCH model," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 606-617.
    23. Jayasuriya, Shamila A., 2011. "Stock market correlations between China and its emerging market neighbors," Emerging Markets Review, Elsevier, vol. 12(4), pages 418-431.
    24. Bos, T & Newbold, P, 1984. "An Empirical Investigation of the Possibility of Stochastic Systematic Risk in the Market Model," The Journal of Business, University of Chicago Press, vol. 57(1), pages 35-41, January.
    25. Robert W. Faff & David Hillier & Joseph Hillier, 2000. "Time Varying Beta Risk: An Analysis of Alternative Modelling Techniques," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 27(5‐6), pages 523-554, June.
    26. Taufiq Choudhry & Hao Wu, 2009. "Forecasting the weekly time-varying beta of UK firms: GARCH models vs. Kalman filter method," The European Journal of Finance, Taylor & Francis Journals, vol. 15(4), pages 437-444.
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    More about this item

    Keywords

    CAPM; Multivariate model; State space model; Stock market returns; Systematic covariance (beta) risk; Time-varying beta;
    All these keywords.

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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