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Stock index hedge using trend and volatility regime switch model considering hedging cost

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  • Su, EnDer

Abstract

This paper studies the risk hedging between stock index and underlying futures. The hedging ratios are optimized using the mean-variance utility function as considering the hedging cost. The trend of returns and variance are estimated by the model of regime switch on both vector autoregression (VAR) and GARCH(1,1) compared to three restricted models: VAR switch only, GARCH(1,1) switch only, and no switch. The hedge portfolio is constructed by Morgan Stanley Taiwan Index (MSTI) and Singapore Traded MSTI futures. The hedge horizon is set as a week to reduce the hedging cost and the weekly in-sample data cover from 08/09/2001 to 05/31/2007. The rolling window technique is used to evaluate the hedge performances of out-of-sample period spanning subprime, Greek debt, and post-risk durations. The subprime period indeed is evidenced very vital to achieve the hedge performance. All models perform surprisingly far above average during subprime period. The hedge ratios indeed are the tradeoff between maximum expected return and minimum variance. It is demonstrated challenging for all models to increase returns and reduce risk together. The hedge context is further classified into four hedge states: uu, ud, du, and dd (u and d denote respectively usual and down) using the state probabilities of series. The regime switch models are found to have much greater wealth increase when in dd state. It is decisive to hedge risk in dd state when volatility is extensively higher as observed recurrently in subprime period. Remarkably, the trend switch is found having larger wealth increase while the volatility switch is not found prominent between models. While the no switch model has larger utility increase in uu state as most observed in Greek debt or post risk period, its performance is far below average like other models.

Suggested Citation

  • Su, EnDer, 2013. "Stock index hedge using trend and volatility regime switch model considering hedging cost," MPRA Paper 49190, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:49190
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    References listed on IDEAS

    as
    1. Moschini, GianCarlo & Myers, Robert J., 2002. "Testing for constant hedge ratios in commodity markets: a multivariate GARCH approach," Journal of Empirical Finance, Elsevier, vol. 9(5), pages 589-603, December.
    2. Sergio H. Lence, 1995. "The Economic Value of Minimum-Variance Hedges," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 77(2), pages 353-364.
    3. Leland L. Johnson, 1960. "The Theory of Hedging and Speculation in Commodity Futures," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 27(3), pages 139-151.
    4. Haas, Markus & Mittnik, Stefan, 2008. "Multivariate regimeswitching GARCH with an application to international stock markets," CFS Working Paper Series 2008/08, Center for Financial Studies (CFS).
    5. 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.
    6. Ronald A. Babula & Fred J. Ruppel & David A. Bessler, 1995. "U.S. corn exports: the role of the exchange rate," Agricultural Economics, International Association of Agricultural Economists, vol. 13(2), pages 75-88, November.
    7. Heifner, Richard G., 1972. "Optimal Hedging Levels and Hedging Effectiveness in Cattle Feeding," Journal of Agricultural Economics Research, United States Department of Agriculture, Economic Research Service, vol. 24(2), pages 1-14, April.
    8. Honda, Toshiki, 2003. "Optimal portfolio choice for unobservable and regime-switching mean returns," Journal of Economic Dynamics and Control, Elsevier, vol. 28(1), pages 45-78, October.
    9. Lien, Donald & Yang, Li, 2008. "Asymmetric effect of basis on dynamic futures hedging: Empirical evidence from commodity markets," Journal of Banking & Finance, Elsevier, vol. 32(2), pages 187-198, February.
    10. Franc Klaassen, 2002. "Improving GARCH volatility forecasts with regime-switching GARCH," Empirical Economics, Springer, vol. 27(2), pages 363-394.
    11. Pelletier, Denis, 2006. "Regime switching for dynamic correlations," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 445-473.
    12. Kee-Hong Bae & G. Andrew Karolyi & René M. Stulz, 2003. "A New Approach to Measuring Financial Contagion," The Review of Financial Studies, Society for Financial Studies, vol. 16(3), pages 717-763, July.
    13. Kroner, Kenneth F. & Sultan, Jahangir, 1993. "Time-Varying Distributions and Dynamic Hedging with Foreign Currency Futures," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 28(4), pages 535-551, December.
    14. Yun, Won-Cheol & Jae Kim, Hyun, 2010. "Hedging strategy for crude oil trading and the factors influencing hedging effectiveness," Energy Policy, Elsevier, vol. 38(5), pages 2404-2408, May.
    15. Darren L. Frechette, 2000. "The Demand for Hedging and the Value of Hedging Opportunities," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 82(4), pages 897-907.
    16. Markus Haas, 2004. "A New Approach to Markov-Switching GARCH Models," Journal of Financial Econometrics, Oxford University Press, vol. 2(4), pages 493-530.
    17. Bjorn Hansson & Peter Hordahl, 1998. "Testing the conditional CAPM using multivariate GARCH-M," Applied Financial Economics, Taylor & Francis Journals, vol. 8(4), pages 377-388.
    18. Baillie, Richard T & Myers, Robert J, 1991. "Bivariate GARCH Estimation of the Optimal Commodity Futures Hedge," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 6(2), pages 109-124, April-Jun.
    19. Ederington, Louis H, 1979. "The Hedging Performance of the New Futures Markets," Journal of Finance, American Finance Association, vol. 34(1), pages 157-170, March.
    20. Bollerslev, Tim & Engle, Robert F & Wooldridge, Jeffrey M, 1988. "A Capital Asset Pricing Model with Time-Varying Covariances," Journal of Political Economy, University of Chicago Press, vol. 96(1), pages 116-131, February.
    21. Marcucci Juri, 2005. "Forecasting Stock Market Volatility with Regime-Switching GARCH Models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 9(4), pages 1-55, December.
    22. Harry Markowitz, 1952. "Portfolio Selection," Journal of Finance, American Finance Association, vol. 7(1), pages 77-91, March.
    23. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Paul Labys, 2003. "Modeling and Forecasting Realized Volatility," Econometrica, Econometric Society, vol. 71(2), pages 579-625, March.
    24. Michael S. Haigh & Matthew T. Holt, 2002. "Hedging foreign currency, freight, and commodity futures portfolios—A note," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 22(12), pages 1205-1221, December.
    25. Alizadeh, Amir H. & Nomikos, Nikos K. & Pouliasis, Panos K., 2008. "A Markov regime switching approach for hedging energy commodities," Journal of Banking & Finance, Elsevier, vol. 32(9), pages 1970-1983, September.
    26. Hamilton, James D., 1990. "Analysis of time series subject to changes in regime," Journal of Econometrics, Elsevier, vol. 45(1-2), pages 39-70.
    27. Gagnon, Louis & Lypny, Gregory J. & McCurdy, Thomas H., 1998. "Hedging foreign currency portfolios," Journal of Empirical Finance, Elsevier, vol. 5(3), pages 197-220, September.
    28. Liu, Kang E. & Geaun, Jerome & Lei, Li-Fen, 2001. "Optimal hedging decisions for Taiwanese corn traders on the way to liberalisation," Agricultural Economics, Blackwell, vol. 25(2-3), pages 303-309, September.
    29. Jin, Hyun J. & Koo, Won W., 2006. "Offshore hedging strategy of Japan-based wheat traders under multiple sources of risk and hedging costs," Journal of International Money and Finance, Elsevier, vol. 25(2), pages 220-236, March.
    30. Hamilton, James D, 1991. "A Quasi-Bayesian Approach to Estimating Parameters for Mixtures of Normal Distributions," Journal of Business & Economic Statistics, American Statistical Association, vol. 9(1), pages 27-39, January.
    31. Bollerslev, Tim, 1990. "Modelling the Coherence in Short-run Nominal Exchange Rates: A Multivariate Generalized ARCH Model," The Review of Economics and Statistics, MIT Press, vol. 72(3), pages 498-505, August.
    32. Hamilton, James D. & Susmel, Raul, 1994. "Autoregressive conditional heteroskedasticity and changes in regime," Journal of Econometrics, Elsevier, vol. 64(1-2), pages 307-333.
    33. Michael S. Haigh & Matthew T. Holt, 2000. "Hedging Multiple Price Uncertainty in International Grain Trade," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 82(4), pages 881-896.
    34. Ng, Lilian, 1991. "Tests of the CAPM with Time-Varying Covariances: A Multivariate GARCH Approach," Journal of Finance, American Finance Association, vol. 46(4), pages 1507-1521, September.
    35. Tse, Y K & Tsui, Albert K C, 2002. "A Multivariate Generalized Autoregressive Conditional Heteroscedasticity Model with Time-Varying Correlations," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(3), pages 351-362, July.
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    More about this item

    Keywords

    stock index; regime switch; hedging cost; hedging ratio;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation

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