Abstract
The mean-variance hedging (MVH) with a significant risk-aversion coefficient is approximately equal to the minimum-variance (MV) hedge. However, how large the risk-aversion coefficient should be in practice? We determine the boundaries of risk-aversion coefficients that significantly distinguish the MV hedge and the MVH based on the different magnitudes of statistical errors in the presence of estimation risk. Based on the hedged variance, hedged return, and hedge ratio, we show that the MV hedge is statistically justified for MVH investor with an extensive range of risk-aversion coefficients. Additionally, the upper bound of the significant risk-aversion coefficient is positively related to the squared information ratio of futures.
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Notes
Other forms of mean-variance optimization can also approximate the expected utility maximization. Das et al. (2010, p. 316) use the mean-variance utility maximization for this quadratic optimization.
We are grateful to Investing.com for providing the simulation data. Henceforth, we refer to these futures as the FTSE 100 and the S&P 500, respectively.
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Acknowledgements
The author is thankful to the Editor and a anonymous reviewer for helpful suggestions which have improved the presentation in the paper. The author also gratefully acknowledges partial financial support from the National United University through project 109NUUPRJ-10.
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Chiu, WY. Mean-variance hedging in the presence of estimation risk. Rev Deriv Res 24, 221–241 (2021). https://doi.org/10.1007/s11147-021-09176-6
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DOI: https://doi.org/10.1007/s11147-021-09176-6
Keywords
- Minimum-variance hedge
- Mean-variance hedging
- Risk-aversion coefficient
- Information ratio
- Significance test