Minimum-variance hedging of Bitcoin inverse futures

ABSTRACT

We formulate an optimal hedging problem of Bitcoin inverse futures under the minimum-variance framework. We obtain the optimal hedging strategy in closed forms for both short and long hedges and compute hedging effectiveness under the optimal strategy. Our empirical analyses show that the optimal hedging strategy achieves superior effectiveness in reducing risk and outperforms the naïve hedge in all scenarios.

KEYWORDS:

• Bitcoin
• futures
• hedging effectiveness
• risk management

JEL CLASSIFICATION:

• G11
• G32

Acknowledgments

Our most sincere gratitude goes to an anonymous referee, whose comments are both encouraging and critical, and truly help us improve the quality of this paper. We also would like to thank Liyan Yang and Kewei Hou for insightful comments. The research of Bin Zou is supported in part by a start-up from the University of Connecticut.

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

¹ Both CBOE and CME launched their Bitcoin futures independently in December 2017. But CBOE had ceased offering Bitcoin futures after 19 June 2019, leaving CME the only venue for trading standard Bitcoin futures. See news report https://www.wsj.com/articles/cboe-abandons-bitcoin-futures-11552914001.

² ICBIT was later acquired by Swedish-based Bitcoin exchange Safello; see https://en.bitcoin.it/wiki/ICBIT.

³ Here, margin rate refers to the initial margin requirement of the inverse futures contracts, and is used to calculate the number of Bitcoins that need to be deposited into the margin account before trading inverse futures. Please see analyses leading to (2.2).

⁴ Such a choice on inverse futures settlement is beneficial to the understanding of $P\text{amp}L$. As can be seen from (2.1), an increase in the futures price leads to trading gains in long positions, which is consistent with common knowledge on standard futures. More details can be found on https://support.okex.com/hc/en-us/articles/360000104591-Futures-Account-Profit-Loss.

Additional information

Funding

This work was supported by the Fundamental Research Funds for the Central Universities”, Zhongnan University of Economics and Law (2722020JCG071), the National Natural Science Foundation of China [11501105, 71773143]; the Fundamental Research Funds for the Central Universities in UIBE [19YB10; 19YB27]; University of Connecticut [start-up grant]; Smart Finance Lab of Research Institute for ShenZhen in UIBE.