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Hedging Cryptocurrency Options

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  • Matic, Jovanka Lili
  • Packham, Natalie
  • Härdle, Wolfgang Karl

Abstract

The cryptocurrency (CC) market is volatile, non-stationary and non-continuous. Together with liquid derivatives markets, this poses a unique opportunity to study risk management, especially the hedging of options, in a turbulent market. We study the hedge behaviour and effectiveness for the class of affine jump diffusion models and infinite activity Lévy processes. First, market data is calibrated to SVI-implied volatility surfaces to price options. To cover a wide range of market dynamics, we generate Monte Carlo price paths using an SVCJ model (stochastic volatility with correlated jumps) assumption and a close-to-actual-market GARCH-filtered kernel density estimation. In these two markets, options are dynamically hedged with Delta, Delta-Gamma, Delta-Vega and Minimum Variance strategies. Including a wide range of market models allows to understand the trade-off in the hedge performance between complete, but overly parsimonious models, and more complex, but incomplete models. The calibration results reveal a strong indication for stochastic volatility, low jump frequency and evidence of infinite activity. Short-dated options are less sensitive to volatility or Gamma hedges. For longer-date options, good tail risk reduction is consistently achieved with multiple-instrument hedges. This is persistently accomplished with complete market models with stochastic volatility.

Suggested Citation

  • Matic, Jovanka Lili & Packham, Natalie & Härdle, Wolfgang Karl, 2021. "Hedging Cryptocurrency Options," MPRA Paper 110985, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:110985
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    References listed on IDEAS

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    More about this item

    Keywords

    Cryptocurrency options; hedging; bitcoin; digital finance; volatile markets;
    All these keywords.

    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

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