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Hedge Ratio Prediction with Noisy and Asynchronous High‐Frequency Data
Author(s) -
Lai YuSheng
Publication year - 2016
Publication title -
journal of futures markets
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.88
H-Index - 55
eISSN - 1096-9934
pISSN - 0270-7314
DOI - 10.1002/fut.21735
Subject(s) - estimator , econometrics , covariance , noise (video) , asynchronous communication , volatility (finance) , hedge , computer science , statistics , economics , mathematics , artificial intelligence , telecommunications , ecology , biology , image (mathematics)
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