Hedging cryptocurrency options

Arbeitspapier

The cryptocurrency (CC) market is volatile, non-stationary and non-continuous. This poses unique challenges for pricing and hedging CC options. We study the hedge behaviour and effectiveness for a wide range of models. First, we calibrate market data to SVI-implied volatility surfaces, which in turn are used to price options. To cover a wide range of market dynamics, we generate price paths using two types of Monte Carlo simulations. In the first approach, price paths follow an SVCJ model (stochastic volatility with correlated jumps). The second approach simulates paths from a GARCH-filtered kernel density estimation. In these two markets, options are hedged with models from the class of affine jump diffusions and infinite activity Lévy processes. 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. Dynamic Delta, Delta-Gamma, Delta-Vega and minimum variance hedge strategies are applied. The calibration results reveal a strong indication for stochastic volatility, low jump intensity and evidence of infinite activity. With the exception of short-dated options, a consistently good performance is achieved with Delta-Vega hedging in stochastic volatility models. Judging on the calibration and hedging results, the study provides evidence that stochastic volatility is the driving force in CC markets.

Object Details

• Language: Englisch

References and Relationships

• Bibliographic citation: Series: IRTG 1792 Discussion Paper ; No. 2021-021

Classification and Topics

• Classification: Wirtschaft

Contributors, Places and Time

• Event: Geistige Schöpfung
• (who): Matic, Jovanka ; Packham, Natalie ; Härdle, Wolfgang
• Event: Veröffentlichung
• (who): Humboldt-Universität zu Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series"
• (where): Berlin
• (when): 2021

Further information

• Handle: http://hdl.handle.net/10419/247318
• Last update: 10.03.2025, 11:42 AM CET