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Optimization of relative arbitrage

Ting-Kam Leonard Wong
Abstract

In stochastic portfolio theory, a relative arbitrage is an equity portfolio which outperforms a benchmark portfolio over a specified horizon. When the market is diverse and sufficiently volatile, and the benchmark is the market or a buy-and-hold portfolio, functionally generated portfolios provide a systematic way of constructing relative arbitrages. In this paper we show that if the market portfolio is replaced by the equal or entropy weighted portfolio among many others, no relative arbitrages can be constructed using functionally generated portfolios. We also introduce and study a shaped-constrained optimization problem for functionally generated portfolios in the spirit of maximum likelihood estimation of a log-concave density.

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