Forecasting and Managing Correlation Risks
68 Pages Posted: 21 Nov 2022 Last revised: 1 Sep 2023
Date Written: September 09, 2024
Abstract
We propose a novel and easy-to-implement framework for forecasting correlation risks based on a large set of salient realized correlation features and the sparsity-encouraging LASSO technique. Considering the universe of S&P 500 stocks, we find that the new approach manifests in statistically superior out-of-sample forecasts compared to commonly used procedures. We further demonstrate how the forecasts translate into significant economic gains in the form of higher pairs trading profits, better equity premium predictions, more accurate portfolio risk targeting, and superior overall risk control and minimization.
Keywords: Correlation forecasting, high-frequency data, LASSO, risk targeting and control, pairs trading, equity premium prediction
JEL Classification: C13, C14, C52, C53, C55, C58
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