Delta-hedging in fractional volatility models

Research output: Contribution to journalArticlepeer-review


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.

Original languageEnglish (US)
JournalAnnals of Finance
StateAccepted/In press - 2022


  • Hedging
  • Hedging bias
  • Long-memory
  • Stochastic volatility

ASJC Scopus subject areas

  • Finance
  • Economics, Econometrics and Finance(all)


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