Ross Recovery with Recurrent and Transient Processes
Mathematical Finance
2015-10-20 v5
Abstract
Recently, Ross showed that it is possible to recover an objective measure from a risk-neutral measure. His model assumes that there is a finite-state Markov process X that drives the economy in discrete time. Many authors extended his model to a continuous-time setting with a Markov diffusion process X with state space R. Unfortunately, the continuous-time model fails to recover an objective measure from a risk-neutral measure. We determine under which information recovery is possible in the continuous-time model. It was proven that if X is recurrent under the objective measure, then recovery is possible. In this article, when X is transient under the objective measure, we investigate what information is sufficient to recover.
Cite
@article{arxiv.1410.2282,
title = {Ross Recovery with Recurrent and Transient Processes},
author = {Hyungbin Park},
journal= {arXiv preprint arXiv:1410.2282},
year = {2015}
}