Predictability of Stock Return Volatility from GARCH Models

Predictability of Stock Return Volatility from GARCH Models
Author(s): Goyal, Amit
Year: 2000
Paper Number: GBS-FIN-2000-001
Goizueta Department: Finance

Abstract

This paper focuses on the performance of various GARCH models in terms of their ability of delivering volatility forecasts for stock return data. Volatility forecasts obtained from a variety of mean and variance specifications in GARCH models are compared to a proxy of actual volatility calculated using daily data. In-sample tests suggest that a regression of volatility estimates on actual volatility produces R2s of less than 8%. An interesting by-product is evidence of significantly negative relation between unexpected volatility and stock returns. Finally, out-of-sample tests indicate that a simpler ARMA specification performs better than a GARCH-M model.