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arXiv · 1408.7010

Long Term Optimal Investment in Matrix Valued Factor Models

Scott Robertson·Hao Xing
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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.

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Scott Robertson, Hao Xing. 2014-08-29. Long Term Optimal Investment in Matrix Valued Factor Models. https://arxiv.org/abs/1408.7010

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