Long Term Optimal Investment in Matrix Valued Factor Models
Abstract
Long term optimal investment problems are studied in a factor model with matrix valued state variables. Explicit parameter restrictions are obtained under which, for an isoelastic investor, the finite horizon value function and optimal strategy converge to their long-run counterparts as the investment horizon approaches infinity. This convergence also yields portfolio turnpikes for general utilities. By using results on large time behaviour of semi-linear partial differential equations, our analysis extends affine models, where the Wishart process drives investment opportunities, to a non-affine setting. Furthermore, in the affine setting, an example is constructed where the value function is not exponentially affine, in contrast to models with vector-valued state variables.
Keywords
Cite
@article{arxiv.1408.7010,
title = {Long Term Optimal Investment in Matrix Valued Factor Models},
author = {Scott Robertson and Hao Xing},
journal= {arXiv preprint arXiv:1408.7010},
year = {2014}
}
Comments
33 pages