Pricing Exotic Derivatives for Cryptocurrency Assets—A Monte Carlo Perspective

In the current paper, we develop a methodology to price lookback options for cryptocurrencies. We propose discreetly monitored window average option, whose monitoring frequencies are randomly selected within time maturity, and is asset in specified surrounding instant. these underlying CCI30 index of various Cryptocurrencies, as opposed single cryptocurrency, with intention reducing volatility, thus, option price. employ Normal Inverse Gaussian (NIG) Rough Fractional Stochastic Volatility (RFSV) models cryptocurrency market, using Black-Scholes benchmark model. doing so, intend capture extreme characteristics such jumps volatility roughness fluctuations. Since there no availability closed-form solution prices under models, utilize Monte Carlo simulation pricing, augment it antithetic method variance reduction. Finally, present results options, compare resulting from NIG model, RFSV model those find that indeed lower our proposed than traditional option. found Hurst parameter be H=0.09 which confirms market rough.