Let $\{p_t\}_{t \geq 0}$ be a family of densities. Is there any result concerning the existence of a semi-martingale $\{X_t\}_{t \geq 0}$ such that for all $t\geq 0$, the density of $X_t$ is $p_t$ ?
Existence of a semi-martingale that matches given densities
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probability-theory
probability-distributions
stochastic-processes
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1It really only relies on the fact that if $p$ is a density wrt. the Lebesgue measure, then there exists a random variable $X$ with density $p$. – 2012-07-02
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0My bad, it is indeed a stupid question. The only interesting case would be if the covariance structure was specified, e.g. finite dimensional laws. Kolmogorov extension theorem would be the answer in this case. – 2012-07-02
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0@StefanHansen I changed stochastic process to semi-martingale, which is what I am actually looking at. – 2012-07-02
1 Answers
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After some investigations I found this theorem due to Kellerer.
Theorem (Kellerer, 1972) $-$ Let $(\mu_t)_{t\in[0,T]}$ be a family of probability measures of $(\mathbb{R},\mathcal{B}(\mathbb{R}))$ with first moments, such that for $s