Exponential Change of Measure for General Piecewise Deterministic Markov Processes

Abstract: We consider a general piecewise deterministic Markov process (PDMP) $X={X_t}{t\geqslant 0}$ with measure-valued generator $\mathcal{A}$, for which the conditional distribution function of the inter-occurrence time is not necessarily absolutely continuous. A general form of the exponential martingales is presented as $$M^f_t=\frac{f(X_t)}{f(X_0)}\left[\mathrm{Sexp}\left(\int{(0,t]}\frac{\mathrm{d}L(\mathcal{A}f)s}{f(X{s-})}\right)\right]^{-1}.$$ Using this exponential martingale as a likelihood ratio process, we define a new probability measure. It is shown that the original process remains a general PDMP under the new probability measure. And we find the new measure-valued generator and its domain.