Quasi-likelihood estimation in a mixed fractional Black-Scholes model

Let $B^H=\{B_t^H, t \geq 0\}$ be a fractional Brownian motion with Hurst index $0<H<1$, and let $B=\{B_t, t \geq 0\}$ be an independent Brownian motion. In this study, we investigate the parameter estimation of a mixed fractional Black-Scholes model $ S_t^H=S_0^H+\mu\displaystyle \int_0^tS_s^H{\mathrm{d}}s+\sigma\displaystyle \int_{0}^{t}S_s^H{\mathrm{d}}(B_s+B_s^H)$,where $\sigma>0$, $\mu\in {\mathbb R}$ are two unknown parameters. Using quasi-likelihood estimation, when the system is observed at some discrete time instants $\{t_i=ih,i=0,1,2,\ldots,n\}$, we give estimations of the parameters $\mu$ and $\sigma$ provided $h=h(n)\to 0$, $nh\to \infty$ and $h^{1+\gamma}n\to 1$ for some $\gamma>0$, as $n\to \infty$. We present the asymptotic normality of the estimators based on the velocity of $nh^{1+\gamma}-1$ tending to zero as $n$ tends to infinity. Finally, we perform numerical calculus and simulations using factual data from the stock market to verify the effectiveness of the established estimators.

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Publication Details

Journal
Probability Uncertainty and Quantitative Risk
Published
2025-01-01
DOI
https://doi.org/10.3934/puqr.2025022
Primary Topic
Statistical Distribution Estimation and Applications
Type
article
Field-Weighted Citation Impact
0.00

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article

Quasi-likelihood estimation in a mixed fractional Black-Scholes model

Litan Yan, Wenhan Lu, Junjie Xia
Probability Uncertainty and Quantitative Risk
Statistical Distribution Estimation and Applications
article

Quasi-likelihood estimation in a mixed fractional Black-Scholes model

Litan Yan, Wenhan Lu, Junjie Xia
article en

Abstract

Let $B^H=\{B_t^H, t \geq 0\}$ be a fractional Brownian motion with Hurst index $0<H<1$, and let $B=\{B_t, t \geq 0\}$ be an independent Brownian motion. In this study, we investigate the parameter estimation of a mixed fractional Black-Scholes model $ S_t^H=S_0^H+\mu\displaystyle \int_0^tS_s^H{\mathrm{d}}s+\sigma\displaystyle \int_{0}^{t}S_s^H{\mathrm{d}}(B_s+B_s^H)$,where $\sigma>0$, $\mu\in {\mathbb R}$ are two unknown parameters. Using quasi-likelihood estimation, when the system is observed at some discrete time instants $\{t_i=ih,i=0,1,2,\ldots,n\}$, we give estimations of the parameters $\mu$ and $\sigma$ provided $h=h(n)\to 0$, $nh\to \infty$ and $h^{1+\gamma}n\to 1$ for some $\gamma>0$, as $n\to \infty$. We present the asymptotic normality of the estimators based on the velocity of $nh^{1+\gamma}-1$ tending to zero as $n$ tends to infinity. Finally, we perform numerical calculus and simulations using factual data from the stock market to verify the effectiveness of the established estimators.

Probability Uncertainty and Quantitative RiskVol. 10(4)
Donghua University (CN)
Natural Science Foundation of Shanghai, National Natural Science Foundation of China
Openalex Percentile: Top 73%
Statistical Distribution Estimation and Applications
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Quasi-likelihood estimation in a mixed fractional Black-Scholes model — Litan Yan, Wenhan Lu, et al. · Probability Uncertainty and Quantitative Risk (2025) | TGRS Research Map | TGRS