Intraday volatility forecasting from implied volatility

Purpose - The purpose of this paper is to examine whether the superiority of the implied volatility from a stochastic volatility model over the implied volatility from the Black and Scholes model on the forecasting performance of future realized volatility still holds when intraday data are analyzed. Design/methodology/approach - Two implied volatilities and a realized volatility on KOSPI200 index options are estimated every hour. The grander causality tests between an implied volatility and a realized volatility is carried out for checking the forecasting performance. A dummy variable is added to the grander causality test to examine the change of the forecasting performance when a specific environment is chosen. A trading simulation is conducted to check the economic value of the forecasting performance. Findings - Contrary to the previous studies, the implied volatility from a stochastic volatility model is not superior to that from the Black and Scholes model for the intraday volatility forecasting even if both implied volatilities are informative on one hour ahead future volatility. The forecasting performances of both implied volatilities are improved under high volatile market or low return market. Practical implications - The trading strategy using the forecasting power of an implied volatility earns positively, in particular, more positively under high volatile market or low return market. However, it looks risky to follow the trading strategy because the performance is too volatile. Between two implied volatilities, it is hardly to say that one implied volatility beats another in terms of the economic value. Originality/value - This is the first study which shows the forecasting performances of implied volatilities on the intraday future volatility.

[1]  Philippe Jorion Predicting Volatility in the Foreign Exchange Market , 1995 .

[2]  S. Heston A Closed-Form Solution for Options with Stochastic Volatility with Applications to Bond and Currency Options , 1993 .

[3]  S. Heston,et al.  A Closed-Form GARCH Option Valuation Model , 2000 .

[4]  Gurdip Bakshi,et al.  Empirical Performance of Alternative Option Pricing Models , 1997 .

[5]  Dajiang Guo The Information Content of Implied Stochastic Volatility from Currency Options , 1996 .

[6]  David S. Bates The Crash of ʼ87: Was It Expected? The Evidence from Options Markets , 1991 .

[7]  Marwan Izzeldin,et al.  Forecasting Daily Stock Volatility: the Role of Intraday Information and Market Conditions , 2008 .

[8]  D. Shanno,et al.  Option Pricing when the Variance Is Changing , 1987, Journal of Financial and Quantitative Analysis.

[9]  David S. Bates Post-'87 crash fears in the S&P 500 futures option market , 2000 .

[10]  J. Poterba,et al.  The Persistence of Volatility and Stock Market Fluctuations , 1984 .

[11]  F. Diebold,et al.  The distribution of realized stock return volatility , 2001 .

[12]  Gurdip Bakshi,et al.  Pricing and hedging long-term options , 2000 .

[13]  Stephen L Taylor,et al.  Forecasting Currency Volatility: A Comparison of Implied Volatilities and AR(FI)MA Models , 2003 .

[14]  Craig Hiemstra,et al.  Testing for Linear and Nonlinear Granger Causality in the Stock Price-Volume Relation , 1994 .

[15]  Francis X. Diebold,et al.  Modeling and Forecasting Realized Volatility , 2001 .

[16]  A. Christie,et al.  The stochastic behavior of common stock variances: value , 1982 .

[17]  I. Kim,et al.  Empirical comparison of alternative stochastic volatility option pricing models: Evidence from Korean KOSPI 200 index options market , 2004 .

[18]  F. Black,et al.  The Pricing of Options and Corporate Liabilities , 1973, Journal of Political Economy.

[19]  Stephen Taylor,et al.  Forecasting S&P 100 Volatility: The Incremental Information Content of Implied Volatilities and High Frequency Index Returns , 2000 .

[20]  I. Kim,et al.  The lead‐lag relationship between stock index options and the stock index market: Model, moneyness, and news , 2009 .

[21]  Wei Guan,et al.  Is implied volatility an informationally efficient and effective predictor of future volatility , 2002 .

[22]  Alan G. White,et al.  The Pricing of Options on Assets with Stochastic Volatilities , 1987 .

[23]  S. Turnbull,et al.  Pricing foreign currency options with stochastic volatility , 1990 .

[24]  Donald P. Chiras,et al.  The information content of option prices and a test of market efficiency , 1978 .

[25]  T. Day,et al.  Stock market volatility and the information content of stock index options , 1992 .

[26]  Allen M. Poteshman Forecasting Future Volatility from Option Prices , 2000 .

[27]  Christopher G. Lamoureux,et al.  Forecasting Stock-Return Variance: Toward an Understanding of Stochastic Implied Volatilities , 1993 .

[28]  Jeff Fleming The quality of market volatility forecasts implied by S&P 100 index option prices , 1998 .

[29]  Richard J. Rendleman,et al.  STANDARD DEVIATIONS OF STOCK PRICE RATIOS IMPLIED IN OPTION PRICES , 1976 .

[30]  James B. Wiggins Option values under stochastic volatility: Theory and empirical estimates , 1987 .

[31]  S. Byun,et al.  Forecasting Future Volatility from Option Prices under the Stochastic Volatility Model , 2009 .

[32]  P. Giot Implied Volatility Indexes and Daily Value at Risk Models , 2005 .

[33]  Jonathan M. Karpoff The Relation between Price Changes and Trading Volume: A Survey , 1987, Journal of Financial and Quantitative Analysis.

[34]  J. Duan THE GARCH OPTION PRICING MODEL , 1995 .

[35]  E. Stein,et al.  Stock Price Distributions with Stochastic Volatility: An Analytic Approach , 1991 .

[36]  H. Bessembinder,et al.  Price Volatility, Trading Volume, and Market Depth: Evidence from Futures Markets , 1993, Journal of Financial and Quantitative Analysis.

[37]  Louis O. Scott Option Pricing when the Variance Changes Randomly: Theory, Estimation, and an Application , 1987, Journal of Financial and Quantitative Analysis.