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arXiv 0901.4925math.PRmath.STstat.TH
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分数阶Ornstein-Uhlenbeck过程的参数估计

Parameter estimation for fractional Ornstein-Uhlenbeck processes

Yaozhong Hu, David Nualart

摘要:

研究了分数布朗运动驱动下的Ornstein-Uhlenbeck过程$dX_t=θX_t dt+σdB^H_t$的最小二乘估计$\hat θ_T$,该过程的参数为$H\ge \frac12$ .证明了$\hat θ_T$的强相合性($\hat θ_T$几乎必然收敛于真参数${% θ}$).我们还得到了这种收敛速度时,$1/2\le H<3/4$,应用中心极限定理的多个维纳积分。这个最小二乘估计量可以用来研究其他更适合模拟的估计量,如公式4.1定义的估计量$\tilde θ_T$。

英文摘要:

We study a least squares estimator $\hat θ_T$ for the Ornstein-Uhlenbeck process, $dX_t=θX_t dt+σdB^H_t$, driven by fractional Brownian motion $B^H$ with Hurst parameter $H\ge \frac12$. We prove the strong consistence of $\hat θ_T$ (the almost surely convergence of $\hat θ_T$ to the true parameter ${% θ}$). We also obtain the rate of this convergence when $1/2\le H<3/4$, applying a central limit theorem for multiple Wiener integrals. This least squares estimator can be used to study other more simulation friendly estimators such as the estimator $\tilde θ_T$ defined by (4.1).

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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