Evolutionary Arbitrage

Abstract

The prices of exchange-traded funds (ETFs) can deviate significantly from their net asset values (NAVs). Exploiting such inefficiencies is often too costly because it involves taking positions in hundreds of underlying illiquid securities. We develop a method that identifies a liquid mimicking portfolio that tracks the NAV using only ETFs. Our method combines a genetic algorithm with non-negative least squares. We apply it to the fixed income ETF market. Our long-short strategy generates a Sharpe ratio of 4-5, incurs little transaction cost, and does well under all market conditions.

Keywords: Statistical Arbitrage, Mimicking Portfolio, Corporate bond ETFs, Evolutionary algorithms