Hedging market risk and uncertainty via a robust portfolio approach

2026-04-02

AI Summary

This study addresses the limitations of traditional hedging strategies under market dynamics uncertainty, which often suffer from excessive risk exposure and high turnover. The authors propose a robust dynamic minimum-variance hedging framework that explicitly incorporates volatility forecast uncertainty into the optimization process, yielding closed-form robust hedge ratios. The approach integrates high-frequency realized variances and covariances, multi-step autoregressive volatility forecasts, and box-type uncertainty sets within a robust optimization setting. Empirical analysis using multiple ETFs from 2016 to 2024 demonstrates that the proposed framework significantly reduces portfolio turnover, enhances protection against downside risk, and improves risk-adjusted returns after accounting for transaction costs. Statistical significance of these results is confirmed through bootstrap tests.

Abstract

Shorting for hedging exposes to risk when the market dynamics is uncertain. Managing uncertainty and risk exposure is key in portfolio management practice. This paper develops a robust framework for dynamic minimum-variance hedging that explicitly accounts for forecast uncertainty in volatility estimation to achieve empirical stability and reduced turnover, further improving other standard performance metrics. The approach combines high-frequency realized variance and covariance measures, autoregressive models for multi-step volatility forecasting, and a box-uncertainty robust optimization scheme. We derive a closed-form solution for the robust hedge ratio, which adjusts the standard minimum-variance hedge by incorporating variance forecast uncertainty. Using a diversified sample of equity, bond, and commodity ETFs over 2016-2024, we show that robust hedge ratios are more stable and entail lower turnover than standard dynamic hedges. While overall variance reduction is comparable, the robust approach improves downside protection and risk-adjusted performance, particularly when transaction costs are considered. Bootstrap evidence supports the statistical significance of these gains.

Problem

• market risk
• forecast uncertainty
• dynamic hedging
• volatility estimation
• portfolio management

Innovation

• robust optimization
• dynamic hedging
• forecast uncertainty
• realized volatility
• minimum-variance hedge ratio