Mathematics – Probability
Scientific paper
2008-10-16
Journal of Mathematical Analysis and Applications, 380(2), 2011, 405-424
Mathematics
Probability
27 pages, references are updated
Scientific paper
We consider a process $(X_t)_{t\in[0,T)}$ given by the SDE $dX_t = \alpha b(t)X_t dt + \sigma(t) dB_t$, $t\in[0,T)$, with initial condition $X_0=0$, where $T\in(0,\infty]$, $\alpha\in R$, $(B_t)_{t\in[0,T)}$ is a standard Wiener process, $b:[0,T)\to R\setminus\{0\}$ and $\sigma:[0,T)\to(0,\infty)$ are continuously differentiable functions. Assuming that $b$ and $\sigma$ satisfy a certain differential equation we derive an explicit formula for the joint Laplace transform of $\int_0^t\frac{b(s)^2}{\sigma(s)^2}(X_s)^2 ds$ and $(X_t)^2$ for all $t\in[0,T)$. As an application, we study asymptotic behavior of the maximum likelihood estimator of $\alpha$ for $\sign(\alpha-K)=\sign(K)$, $K\ne0$, and for $\alpha=K$, $K\ne0$. As an example, we examine the so-called $\alpha$-Wiener bridges given by SDE $dX_t = -\frac{\alpha}{T-t}X_t dt + dB_t$, $t\in[0,T)$, with initial condition $X_0=0$.
Barczy Matyas
Pap Gyula
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