Improving Risk Forecasts Through Cross-Sectional Observations

摘要

Volatility forecasting allows institutional investors to monitor the uncertainty, or variability, in their portfolio returns. However, many traditional approaches to forecasting volatility have shortcomings related to sampling error and other limitations. Here is a new approach that uses cross-sectional observations to produce more timely and accurate risk forecasts.