Quasi-likelihood method estimates parameters in the fractional black–scholes model, suggesting enhanced accuracy in financial data analysis.
In this paper, we consider the parameter estimation for the fractional Black–Scholes model of the form StH=S0H+μ∫0tSsHds+σ∫0tSsHdBsH, where σ>0 and μ∈R are the parameters to be estimated. Here, BH={BtH,t≥0} denotes a fractional Brownian motion with Hurst index 0<H<1. Using the quasi-likelihood method, we estimate the parameters μ and σ based on observations taken at discrete time points {ti=ih,i=0,1,2,…,n}. Under the conditions h=h(n)→0, nh→∞, and h1+γn→1 for some γ>0, as n→∞, the asymptotic properties of the quasi-likelihood estimators are established. The analysis further reveals how the convergence rate of nh1+γ−1 approaching zero affects the accuracy of estimation. To validate the effectiveness of our method, we conduct numerical simulations using real-world stock market data, demonstrating the practical applicability of the proposed estimation framework.
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Lu et al. (2025) studied this question.
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