Year: 2022
Type: article
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.
Source: Journal of Futures Markets
DOI: 10.1002/fut.22372
Authors: Anupam Dutta, Debojyoti Das
Institutions: University of Vaasa, Indian Institute of Management Bangalore
Language: English
Subfield: Finance
Domain: Social Sciences
Open Access status: hybrid
Estimated APC paid: $2,850
OpenAlex ID: W4289745464