Online Universal Dirichlet Factor Portfolios

TL;DR

This paper introduces universal factor-weighted Dirichlet portfolios for online asset allocation, demonstrating their theoretical superiority and empirical effectiveness over uniform Dirichlet schemes in factor-driven markets.

Contribution

It proposes a novel factor-weighted Dirichlet portfolio approach and provides analytical and empirical evidence of its outperformance over uniform schemes.

Findings

Factor-weighted portfolios outperform uniform Dirichlet portfolios.

Analytical lower bounds on portfolio growth are established.

Empirical results confirm advantages in equity markets.

Abstract

We revisit the online portfolio allocation problem and propose universal portfolios that use factor weighing to produce portfolios that out-perform uniform dirichlet allocation schemes. We show a few analytical results on the lower bounds of portfolio growth when the returns are known to follow a factor model. We also show analytically that factor weighted dirichlet sampled portfolios dominate the wealth generated by uniformly sampled dirichlet portfolios. We corroborate our analytical results with empirical studies on equity markets that are known to be driven by factors.