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Hedging with Bitcoin Futures: The Effect of Liquidation Loss Aversion and Aggressive Trading

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  • Carol Alexander
  • Jun Deng
  • Bin Zou

Abstract

We consider the hedging problem where a futures position can be automatically liquidated by the exchange without notice. We derive a semi-closed form for an optimal hedging strategy with dual objectives - to minimise both the variance of the hedged portfolio and the probability of liquidations due to insufficient collateral. The optimal solution depends on the statistical characteristics of the spot and futures extreme returns and parameters that characterise the hedger by loss aversion, choice of leverage and collateral management. An empirical analysis of bitcoin shows that the optimal strategy combines superior hedge effectiveness with a reduction in the probability of liquidation. We compare the performance of seven major direct and inverse hedging instruments traded on five different exchanges, based on minute-level data. We also link this performance to novel speculative trading metrics, which differ markedly between venues.

Suggested Citation

  • Carol Alexander & Jun Deng & Bin Zou, 2021. "Hedging with Bitcoin Futures: The Effect of Liquidation Loss Aversion and Aggressive Trading," Papers 2101.01261, arXiv.org, revised Aug 2021.
    • Handle: RePEc:arx:papers:2101.01261
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    References listed on IDEAS

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    3. Cotter, John, 2001. "Margin exceedences for European stock index futures using extreme value theory," Journal of Banking & Finance, Elsevier, vol. 25(8), pages 1475-1502, August.
    4. Carol Alexander & Jaehyuk Choi & Heungju Park & Sungbin Sohn, 2020. "BitMEX bitcoin derivatives: Price discovery, informational efficiency, and hedging effectiveness," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 40(1), pages 23-43, January.
    5. Acharya, Viral V. & Lochstoer, Lars A. & Ramadorai, Tarun, 2013. "Limits to arbitrage and hedging: Evidence from commodity markets," Journal of Financial Economics, Elsevier, vol. 109(2), pages 441-465.
    6. Alexander, Carol & Heck, Daniel F., 2020. "Price discovery in Bitcoin: The impact of unregulated markets," Journal of Financial Stability, Elsevier, vol. 50(C).
    7. Daskalaki, Charoula & Skiadopoulos, George, 2016. "The effects of margin changes on commodity futures markets," Journal of Financial Stability, Elsevier, vol. 22(C), pages 129-152.
    8. Jun Deng & Huifeng Pan & Shuyu Zhang & Bin Zou, 2020. "Minimum-variance hedging of Bitcoin inverse futures," Applied Economics, Taylor & Francis Journals, vol. 52(58), pages 6320-6337, December.
    9. Billio, Monica & Casarin, Roberto & Osuntuyi, Anthony, 2018. "Markov switching GARCH models for Bayesian hedging on energy futures markets," Energy Economics, Elsevier, vol. 70(C), pages 545-562.
    10. Cifarelli, Giulio & Paladino, Giovanna, 2015. "A dynamic model of hedging and speculation in the commodity futures markets," Journal of Financial Markets, Elsevier, vol. 25(C), pages 1-15.
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    12. Ederington, Louis H, 1979. "The Hedging Performance of the New Futures Markets," Journal of Finance, American Finance Association, vol. 34(1), pages 157-170, March.
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    Cited by:

    1. Dirk G. Baur & Lee A. Smales, 2022. "Trading behavior in bitcoin futures: Following the “smart money”," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(7), pages 1304-1323, July.
    2. Alexander, Carol & Deng, Jun & Feng, Jianfen & Wan, Huning, 2023. "Net buying pressure and the information in bitcoin option trades," Journal of Financial Markets, Elsevier, vol. 63(C).
    3. Jovanka Lili Matic & Natalie Packham & Wolfgang Karl Härdle, 2023. "Hedging cryptocurrency options," Review of Derivatives Research, Springer, vol. 26(1), pages 91-133, April.
    4. Artem Lensky & Mingyu Hao, 2023. "Learning to Predict Short-Term Volatility with Order Flow Image Representation," Papers 2304.02472, arXiv.org, revised Mar 2024.
    5. Jovanka Lili Matic & Natalie Packham & Wolfgang Karl Hardle, 2021. "Hedging Cryptocurrency Options," Papers 2112.06807, arXiv.org, revised Dec 2022.

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