Generalized autoregressive score model with high‐frequency data for optimal futures hedging

This study compares the performance of hedged equity index portfolios constructed using either a generalized autoregressive score (GAS) or a realized GAS (GRAS) model. GAS models encompass popular models, and studies indicate that high‐frequency data improve a model's forecasting ability. The i...

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Bibliographic Details
Published in:The journal of futures markets 2021-12, Vol.41 (12), p.2023-2045
Main Author: Lai, Yu‐Sheng
Format: Article
Language:English
Subjects:
copula
equity indices
futures hedge ratio
generalized autoregressive score
Hedging
high‐frequency data
Portfolios
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Summary:This study compares the performance of hedged equity index portfolios constructed using either a generalized autoregressive score (GAS) or a realized GAS (GRAS) model. GAS models encompass popular models, and studies indicate that high‐frequency data improve a model's forecasting ability. The in‐sample estimation results demonstrate that the GRAS model has better explanatory power and more robust time‐varying variance and dependence parameters when fat‐tailed distributions are accounted for. The out‐of‐sample comparison confirms its superiority in reducing hedged portfolio variance and accruing economic benefits to highly risk‐averse hedgers.
ISSN:0270-7314
1096-9934
DOI:10.1002/fut.22254