Delta-hedging in fractional volatility models

Qi Zhao () and Alexandra Chronopoulou ()
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Qi Zhao: University of Illinois at Urbana-Champaign
Alexandra Chronopoulou: University of Illinois at Urbana-Champaign

Annals of Finance, 2023, vol. 19, issue 1, No 5, 119-140

Abstract: Abstract In this paper, we propose a delta-hedging strategy for a long memory stochastic volatility model (LMSV). This is a model in which the volatility is driven by a fractional Ornstein–Uhlenbeck process with long-memory parameter H. We compute the so-called hedging bias, i.e. the difference between the Black–Scholes Delta and the LMSV Delta as a function of H, and we determine when a European-type option is over-hedged or under-hedged.

Keywords: Long-memory; Stochastic volatility; Hedging; Hedging bias (search for similar items in EconPapers)
JEL-codes: C02 C32 C65 G12 (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s10436-022-00415-w

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