We consider the probabilistic approach to the problems treated in \cite{GMR2}. We focus on the diffusion models generated by $L_{\vec{\theta}, a}\, u(x) := \theta_2\, x^{2a}\, u'' + (\, \theta_2\, a\, x^{2a-1} + \theta_1\, x^{a})\, u', \ \vec{\theta} = (\theta_1, \theta_2)^T\in\R\times (0, +\infty)$, when $a = \frac12$ or $a = 1$ and face the problem of finding optimal (in the asymptotic sense) estimators of the unknown parameter vector $\vec{\theta}$.
Markov semigroups and estimating functions, with applications to some financial models
MININNI, Rosamaria;ROMANELLI, Silvia
2007-01-01
Abstract
We consider the probabilistic approach to the problems treated in \cite{GMR2}. We focus on the diffusion models generated by $L_{\vec{\theta}, a}\, u(x) := \theta_2\, x^{2a}\, u'' + (\, \theta_2\, a\, x^{2a-1} + \theta_1\, x^{a})\, u', \ \vec{\theta} = (\theta_1, \theta_2)^T\in\R\times (0, +\infty)$, when $a = \frac12$ or $a = 1$ and face the problem of finding optimal (in the asymptotic sense) estimators of the unknown parameter vector $\vec{\theta}$.File in questo prodotto:
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