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The economic value of volatility timing using a range-based volatility model

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  • Chou, Ray Yeutien
  • Liu, Nathan

Abstract

There is growing interest in utilizing the range data of asset prices to study the role of volatility in financial markets. In this paper, a new range-based volatility model was used to examine the economic value of volatility timing in a mean-variance framework. We compared its performance with a return-based dynamic volatility model in both in-sample and out-of-sample volatility timing strategies. For a risk-averse investor, it was shown that the predictable ability captured by the dynamic volatility models is economically significant, and that a range-based volatility model performs better than a return-based one.

Suggested Citation

  • Chou, Ray Yeutien & Liu, Nathan, 2010. "The economic value of volatility timing using a range-based volatility model," Journal of Economic Dynamics and Control, Elsevier, vol. 34(11), pages 2288-2301, November.
  • Handle: RePEc:eee:dyncon:v:34:y:2010:i:11:p:2288-2301
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    References listed on IDEAS

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    1. Garman, Mark B & Klass, Michael J, 1980. "On the Estimation of Security Price Volatilities from Historical Data," The Journal of Business, University of Chicago Press, vol. 53(1), pages 67-78, January.
    2. Engle, Robert F. & Kroner, Kenneth F., 1995. "Multivariate Simultaneous Generalized ARCH," Econometric Theory, Cambridge University Press, vol. 11(1), pages 122-150, February.
    3. Ray Chou & Chun-Chou Wu & Nathan Liu, 2009. "Forecasting time-varying covariance with a range-based dynamic conditional correlation model," Review of Quantitative Finance and Accounting, Springer, vol. 33(4), pages 327-345, November.
    4. Marquering, Wessel & Verbeek, Marno, 2004. "The Economic Value of Predicting Stock Index Returns and Volatility," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 39(2), pages 407-429, June.
    5. Martens, Martin & van Dijk, Dick, 2007. "Measuring volatility with the realized range," Journal of Econometrics, Elsevier, vol. 138(1), pages 181-207, May.
    6. Robert Engle, 2004. "Risk and Volatility: Econometric Models and Financial Practice," American Economic Review, American Economic Association, vol. 94(3), pages 405-420, June.
    7. Y.K. Tse & Albert K.C. Tsui, 2000. "A Multivariate GARCH Model with Time-Varying Correlations," Econometrics 0004007, University Library of Munich, Germany.
    8. Wiggins, James B, 1991. "Empirical Tests of the Bias and Efficiency of the Extreme-Value Variance Estimator for Common Stocks," The Journal of Business, University of Chicago Press, vol. 64(3), pages 417-432, July.
    9. Robert Engle, 2002. "New frontiers for arch models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 17(5), pages 425-446.
    10. West, Kenneth D. & Edison, Hali J. & Cho, Dongchul, 1993. "A utility-based comparison of some models of exchange rate volatility," Journal of International Economics, Elsevier, vol. 35(1-2), pages 23-45, August.
    11. Lorenzo Cappiello & Robert F. Engle & Kevin Sheppard, 2006. "Asymmetric Dynamics in the Correlations of Global Equity and Bond Returns," Journal of Financial Econometrics, Oxford University Press, vol. 4(4), pages 537-572.
    12. Jeff Fleming & Chris Kirby & Barbara Ostdiek, 2001. "The Economic Value of Volatility Timing," Journal of Finance, American Finance Association, vol. 56(1), pages 329-352, February.
    13. 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.
    14. Engle, Robert F & Sheppard, Kevin K, 2001. "Theoretical and Empirical Properties of Dynamic Conditional Correlation Multivariate GARCH," University of California at San Diego, Economics Working Paper Series qt5s2218dp, Department of Economics, UC San Diego.
    15. Pasquale Della Corte & Lucio Sarno & Ilias Tsiakas, 2009. "An Economic Evaluation of Empirical Exchange Rate Models," The Review of Financial Studies, Society for Financial Studies, vol. 22(9), pages 3491-3530, September.
    16. Engle, Robert & Colacito, Riccardo, 2006. "Testing and Valuing Dynamic Correlations for Asset Allocation," Journal of Business & Economic Statistics, American Statistical Association, vol. 24, pages 238-253, April.
    17. Fernandes, Marcelo & de Sa Mota, Bernardo & Rocha, Guilherme, 2005. "A multivariate conditional autoregressive range model," Economics Letters, Elsevier, vol. 86(3), pages 435-440, March.
    18. 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.
    19. Parkinson, Michael, 1980. "The Extreme Value Method for Estimating the Variance of the Rate of Return," The Journal of Business, University of Chicago Press, vol. 53(1), pages 61-65, January.
    20. Susan Thorp & George Milunovich, 2007. "Symmetric Versus Asymmetric Conditional Covariance Forecasts: Does It Pay To Switch?," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 30(3), pages 355-377, September.
    21. Brandt, Michael W. & Jones, Christopher S., 2006. "Volatility Forecasting With Range-Based EGARCH Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 24, pages 470-486, October.
    22. Yang, Dennis & Zhang, Qiang, 2000. "Drift-Independent Volatility Estimation Based on High, Low, Open, and Close Prices," The Journal of Business, University of Chicago Press, vol. 73(3), pages 477-491, July.
    23. Sassan Alizadeh & Michael W. Brandt & Francis X. Diebold, 2002. "Range‐Based Estimation of Stochastic Volatility Models," Journal of Finance, American Finance Association, vol. 57(3), pages 1047-1091, June.
    24. Kunitomo, Naoto, 1992. "Improving the Parkinson Method of Estimating Security Price Volatilities," The Journal of Business, University of Chicago Press, vol. 65(2), pages 295-302, April.
    25. Foster, Dean P & Nelson, Daniel B, 1996. "Continuous Record Asymptotics for Rolling Sample Variance Estimators," Econometrica, Econometric Society, vol. 64(1), pages 139-174, January.
    26. Bollerslev, Tim & Chou, Ray Y. & Kroner, Kenneth F., 1992. "ARCH modeling in finance : A review of the theory and empirical evidence," Journal of Econometrics, Elsevier, vol. 52(1-2), pages 5-59.
    27. 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.
    28. Chou, Ray Yeutien, 2005. "Forecasting Financial Volatilities with Extreme Values: The Conditional Autoregressive Range (CARR) Model," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 37(3), pages 561-582, June.
    29. Merton, Robert C., 1980. "On estimating the expected return on the market : An exploratory investigation," Journal of Financial Economics, Elsevier, vol. 8(4), pages 323-361, December.
    30. Fleming, Jeff & Kirby, Chris & Ostdiek, Barbara, 2003. "The economic value of volatility timing using "realized" volatility," Journal of Financial Economics, Elsevier, vol. 67(3), pages 473-509, March.
    31. Busse, Jeffrey A, 1999. "Volatility Timing in Mutual Funds: Evidence from Daily Returns," The Review of Financial Studies, Society for Financial Studies, vol. 12(5), pages 1009-1041.
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