Forecasting realized volatility: New evidence from time‐varying jumps in VIX

Anupam Dutta · Debojyoti Das

36 citations0/0 files storedJournal of Futures Markets

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Financial Risk and Volatility Modeling Stochastic processes and financial applications Market Dynamics and Volatility

Abstract

Abstract Given that jumps in the implied volatility index (VIX) lead to rapid changes in the level of volatility, they may contain significant predictive information for the realized variance (RV) of stock returns. Against this backdrop, the present study proposes to extend the heterogeneous autoregressive (HAR) model using the information content of time‐varying jumps occurring in VIX. We find that jumps in VIX have positive impacts on the RV of S&P 500 index and that the proposed HAR‐RV approach generates more accurate volatility forecasts than do the existing HAR‐RV type models. Importantly, these results hold for short‐, medium‐, and long‐term volatility components.

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References

1991Conditional Heteroskedasticity in Asset Returns: A New Approach 1993On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks 1992ARCH modeling in finance 1987A Conditionally Heteroskedastic Time Series Model for Speculative Prices and Rates of Return 2008A Simple Approximate Long-Memory Model of Realized Volatility 1995Techniques for Verifying the Accuracy of Risk Measurement Models 2004Power and Bipower Variation with Stochastic Volatility and Jumps 2002Comparing Predictive Accuracy

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