On long term investment optimality

TL;DR

This paper develops a comprehensive framework for long-term portfolio optimization aiming to outperform a benchmark, using large deviation theory to identify optimal strategies under various risk and performance criteria.

Contribution

It introduces a unified approach employing large deviation theory to analyze long-term portfolio optimization with nonlinear economic factors and general Itô models.

Findings

Optimal portfolios are time-homogeneous functions of economic factors.

Existence of portfolios that optimize decay rates of both outperformance and underperformance probabilities.

The approach unifies risk-averse, risk-seeking, and performance probability optimization.

Abstract

We study the problem of optimal long term portfolio selection with a view to beat a benchmark. Two kinds of objectives are considered. One concerns the probability of outperforming the benchmark and seeks either to minimise the decay rate of the probability that the portfolio exceeds the benchmark or to maximise the decay rate that the portfolio falls short. The other criterion concerns the growth rate of the risk-sensitive utility of wealth which has to be either minimised, for the risk-averse investor, or maximised, for the risk-seeking investor. It is assumed that the mean returns and volatilities of the securities are affected by an economic factor, possibly, in a nonlinear fashion. The economic factor and the benchmark are modelled with general It\^o differential equations. The results identify optimal portfolios and produce decay, or growth, rates. The portfolios have the form of time-homogeneous functions of the economic factor. Furthermore, a uniform treatment is given to the out- and under- performance probability optimisation as well as to the risk-averse and risk-seeking optimisation. In particular, it is shown that there exists a portfolio that optimises the decay rates of both the outperfomance probability and the underperformance probability. Whereas earlier research on the subject has relied on the techniques of stochastic optimal control and dynamic programming, in this contribution the quantities of interest are studied directly by employing the methods of the large deviation theory. The key to the analysis is to recognise the setup in question as a case of coupled diffusions with time scale separation, with the economic factor representing "the fast process".