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A Simple Expected Volatility (SEV) Index: Application to SET50 Index Options

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Author Info

  • Michael McAleer

    ()
    (University of Canterbury)

  • Chatayan Wiphatthanananthakul

Abstract

In 2003, the Chicago Board Options Exchange (CBOE) made two key enhancements to the volatility index (VIX) methodology based on S&P options. The new VIX methodology seems to be based on a complicated formula to calculate expected volatility. In this paper, with the use of Thailand’s SET50 Index Options data, we modify the VIX formula to a very simple relationship, which has a higher negative correlation between the VIX for Thailand (TVIX) and SET50 Index Options. We show that TVIX provides more accurate forecasts of option prices than the simple expected volatility (SEV) index, but the SEV index outperforms TVIX in forecasting expected volatility. Therefore, the SEV index would seem to be a superior tool as a hedging diversification tool because of the high negative correlation with the volatility index.

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File URL: http://www.econ.canterbury.ac.nz/RePEc/cbt/econwp/1015.pdf
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Bibliographic Info

Paper provided by University of Canterbury, Department of Economics and Finance in its series Working Papers in Economics with number 10/15.

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Length: 41 pages
Date of creation: 01 Mar 2010
Date of revision:
Handle: RePEc:cbt:econwp:10/15

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Keywords: Financial markets; model selection; new products; price forecasting; time series; volatility forecasting;

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References

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  1. Dennis, Patrick & Mayhew, Stewart & Stivers, Chris, 2006. "Stock Returns, Implied Volatility Innovations, and the Asymmetric Volatility Phenomenon," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 41(02), pages 381-406, June.
  2. Bakshi, Gurdip & Cao, Charles & Chen, Zhiwu, 1997. " Empirical Performance of Alternative Option Pricing Models," Journal of Finance, American Finance Association, vol. 52(5), pages 2003-49, December.
  3. Hull, John C & White, Alan D, 1987. " The Pricing of Options on Assets with Stochastic Volatilities," Journal of Finance, American Finance Association, vol. 42(2), pages 281-300, June.
  4. Charles Quanwei Cao & Gurdip S. Bakshi & Zhiwu Chen, 1997. "Empirical Performance of Alternative Option Pricing Models," Yale School of Management Working Papers ysm54, Yale School of Management.
  5. Beckers, Stan, 1981. "Standard deviations implied in option prices as predictors of future stock price variability," Journal of Banking & Finance, Elsevier, vol. 5(3), pages 363-381, September.
  6. Blair, Bevan J. & Poon, Ser-Huang & Taylor, Stephen J., 2001. "Forecasting S&P 100 volatility: the incremental information content of implied volatilities and high-frequency index returns," Journal of Econometrics, Elsevier, vol. 105(1), pages 5-26, November.
  7. Jorion, Philippe, 1995. " Predicting Volatility in the Foreign Exchange Market," Journal of Finance, American Finance Association, vol. 50(2), pages 507-28, June.
  8. Black, Fischer & Scholes, Myron S, 1973. "The Pricing of Options and Corporate Liabilities," Journal of Political Economy, University of Chicago Press, vol. 81(3), pages 637-54, May-June.
  9. Angelo Melino & Stuart M. Turnbull, 1991. "The Pricing of Foreign Currency Options," Canadian Journal of Economics, Canadian Economics Association, vol. 24(2), pages 251-81, May.
  10. Ser-Huang Poon & Peter, F. Pope, 2000. "Trading volatility spreads: a test of index option market efficiency," European Financial Management, European Financial Management Association, vol. 6(2), pages 235-260.
  11. Charles Quanwei Cao & Gurdip S. Bakshi & Zhiwu Chen, 1997. "Empirical Performance of Alternative Option Pricing Models," Yale School of Management Working Papers ysm65, Yale School of Management.
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Cited by:
  1. Roberto Casarin & Chia-Lin Chang & Juan-Ángel Jiménez-Martín & Michael McAleer & Teodosio Pérez Amaral, 2011. "Risk Management of Risk Under the Basel Accord: A Bayesian Approach to Forecasting Value-at-Risk of VIX Futures," Working Papers in Economics 11/26, University of Canterbury, Department of Economics and Finance.
  2. D.E. Allen & A. Kramadibrata & Michael McAleer & R. Powell & A. K. Singh, 2012. "A non-parametric and entropy based analysis of the relationship between the VIX and S&P500," Documentos del Instituto Complutense de Análisis Económico 2012-19, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales.
  3. Chang, Chia-Lin & González-Serrano, Lydia & Jimenez-Martin, Juan-Angel, 2013. "Currency hedging strategies using dynamic multivariate GARCH," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 94(C), pages 164-182.
  4. Chang, C-L. & Jimenez-Martin, J-A. & McAleer, M.J. & Perez-Amaral, T., 2011. "The Rise and Fall of S&P500 Variance Futures," Econometric Institute Research Papers EI2011-37, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
  5. Chia-Lin Chang & Juan-Ángel Jiménez-Martín & Michael McAleer & Teodosio Pérez-Amaral, 2011. "Risk Management of Risk under the Basel Accord: Forecasting Value-at-Risk of VIX Futures," Working Papers in Economics 11/12, University of Canterbury, Department of Economics and Finance.

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