Does implied volatility provide any information beyond that captured in model-based volatility forecasts?

This paper contributes to our understanding of the informational content of implied volatility. Here we examine whether the S&P 500 implied volatility index (VIX) contains any information relevant to future volatility beyond that available from model based volatility forecasts. It is argued that this approach differs from the traditional forecast encompassing approach used in earlier studies. The findings indicate that the VIX index does not contain any such additional information relevant for forecasting volatility.

[1]  Paul Newbold,et al.  Tests for multiple forecast encompassing , 2000 .

[2]  F. Diebold,et al.  Comparing Predictive Accuracy , 1994, Business Cycles.

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

[4]  Paul Newbold,et al.  Testing the equality of prediction mean squared errors , 1997 .

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

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

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

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

[9]  A. Lo,et al.  THE ECONOMETRICS OF FINANCIAL MARKETS , 1996, Macroeconomic Dynamics.

[10]  F. Diebold,et al.  The Distribution of Realized Exchange Rate Volatility , 2000 .

[11]  C. Wetzel,et al.  The Midas Touch , 1984 .

[12]  E. Ghysels,et al.  Série Scientifique Scientific Series Predicting Volatility: Getting the Most out of Return Data Sampled at Different Frequencies , 2022 .

[13]  L. Glosten,et al.  On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks , 1993 .

[14]  F. Diebold,et al.  The Distribution of Exchange Rate Volatility , 1999 .

[15]  N. Prabhala,et al.  The relation between implied and realized volatility , 1998 .

[16]  Siem Jan Koopman,et al.  Forecasting Daily Variability of the S&P 100 Stock Index Using Historical, Realised and Implied Volatility Measurements , 2005 .

[17]  James D. Hamilton.  Time Series Analysis , 1994 .

[18]  H. Hotelling.  The Generalization of Student’s Ratio , 1931 .

[19]  C. Granger,et al.  Forecasting Volatility in Financial Markets: A Review , 2003 .

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

[21]  F. Diebold,et al.  (Understanding, Optimizing, Using and Forecasting) Realized Volatility and Correlation * , 1999 .

[22]  P. Newbold,et al.  Tests for Forecast Encompassing , 1998 .

[23]  Eric Ghysels,et al.  Série Scientifique Scientific Series the Midas Touch: Mixed Data Sampling Regression Models the Midas Touch: Mixed Data Sampling Regression Models* , 2022 .

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