Hedge Ratio Prediction with Noisy and Asynchronous High‐Frequency Data. Issue 3 (29th July 2015) - Lai, Yu‐Sheng
Abstract : A growing body of literature has focused on the design of covariance estimators for identifying when high‐frequency asset prices are asynchronous and contaminated by microstructure noise. This paper presents a comparison of the prediction ability of covariance estimators within a high‐frequency‐based multivariate volatility model for hedge ratio prediction. Empirical results show that the noise‐free predictions are superior to those contaminated by the noise, with the utility gains being particularly substantial for hedgers with pronounced risk aversion. The results demonstrate the importance of removing microstructure noise and asynchronous trading from covariance estimation to achieve accurate hedge ratio prediction. © 2015 Wiley Periodicals, Inc. Jrl Fut Mark 36:295–314, 2016