A Bivariate High‐Frequency‐Based Volatility Model for Optimal Futures Hedging

This study examines the usefulness of high‐frequency data for estimating hedge ratios for different hedging horizons. By jointly modeling the returns and conditional expectation of the covariation, the multivariate high‐frequency‐based volatility (HEAVY) model generates spot‐futures distributions ov...

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Bibliographic Details
Published in:The journal of futures markets 2017-09, Vol.37 (9), p.913-929
Main Authors: Lai, Yu‐Sheng, Lien, Donald
Format: Article
Language:English
Subjects:
Futures trading
Hedging
Ratios
Usefulness
Volatility
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Summary:This study examines the usefulness of high‐frequency data for estimating hedge ratios for different hedging horizons. By jointly modeling the returns and conditional expectation of the covariation, the multivariate high‐frequency‐based volatility (HEAVY) model generates spot‐futures distributions over longer horizons. Using the data on international equity index futures, performance comparisons between HEAVY and generalized autoregressive conditional heteroskedasticity (GARCH) hedge ratios indicate that HEAVY hedge ratios perform more effectively than GARCH hedge ratios at shorter hedging horizons. This implies that the distinct properties of short‐time response and short‐run momentum effects revealed in the HEAVY model are vital for hedge ratio estimation. © 2017 Wiley Periodicals, Inc. Jrl Fut Mark 37:913–929, 2017
ISSN:0270-7314
1096-9934
DOI:10.1002/fut.21841