A simple expected volatility (SEV) index
In 1993, the Chicago Board Options Exchange (CBOE) introduced the Volatility Index, VIX, based on S&P100 options (OEX), which quickly became the benchmark for stock volatility. As VIX is based on real-time option prices, it reflects investors’ consensual view of future expected stock market volatility. In 2003, CBOE made two key enhancements to the VIX methodology. The New VIX is based on an up-to-the-minute market estimation of expected volatility that is calculated by using real-time S&P500 Index (SPX) option bid/ask quotes and a wider range of strike prices rather than just at-the-money series with the market’s expectation of 30-day volatility and using nearby and second-nearby options. The new VIX methodology may appear to be based on a complicated formula to calculate expected volatility. In this paper, with the use of SET50 Index Options data, we simplify the apparently complicated expected volatility formula to a simple relationship, which has a higher negative correlation between the VIX for Thailand (TVIX) and SET50 Index Options.
|Date of creation:||01 Dec 2008|
|Contact details of provider:|| Postal: Postbus 1738, 3000 DR Rotterdam|
Phone: 31 10 4081111
Web page: http://www.eur.nl/ese
More information through EDIRC
References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- 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.
- Bakshi, Gurdip & Cao, Charles & Chen, Zhiwu, 1997.
" Empirical Performance of Alternative Option Pricing Models,"
Journal of Finance,
American Finance Association, vol. 52(5), pages 2003-2049, December.
- 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.
- 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.
- Jorion, Philippe, 1995. " Predicting Volatility in the Foreign Exchange Market," Journal of Finance, American Finance Association, vol. 50(2), pages 507-528, June.
- 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.
- 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 637-654, May-June.
- 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.
- 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.
- 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. Full references (including those not matched with items on IDEAS)