Use of high‐frequency data to evaluate the performance of dynamic hedging strategies

The hedging performance results of generalized autoregressive conditional heteroskedasticity models are mixed; we address this herein by adopting an asymptotic setting to determine the relative performance of competing hedge ratios. The proxy variable is constructed through precise realized measures...

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Bibliographic Details
Published in:The journal of futures markets 2022-01, Vol.42 (1), p.104-124
Main Author: Lai, Yu‐Sheng
Format: Article
Language:English
Subjects:
futures hedge ratio
GARCH forecasts
Hedging
hedging effectiveness
high‐frequency data
Performance evaluation
predictive ability test
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Summary:The hedging performance results of generalized autoregressive conditional heteroskedasticity models are mixed; we address this herein by adopting an asymptotic setting to determine the relative performance of competing hedge ratios. The proxy variable is constructed through precise realized measures rather than through noisy squared returns because the substitution of the latent true hedged portfolio variance with a noisy proxy renders the loss function incapable of ranking forecasts consistently. The merits of allowing some features in modeling the spot–futures distribution are assessed. Empirical comparisons suggest that hedgers may favor the wrong model when the quality of the proxy variable deteriorates.
ISSN:0270-7314
1096-9934
DOI:10.1002/fut.22272