Predictive Ability of Similarity-based Futures Trading Strategies

Abstract

A trading rule that draws on the similarity-based analogical reasoning is proposed in an attempt to simulate the technical trading mentality—one that selectively perceives structural resemblances between market scenarios of the present and the past. In more than half of the nineteen futures markets that we test against for profitability of this similarity-based trading rule, we find evidence of predictive ability that is robust to data-snooping and transaction-cost adjustments. When aided by an exit strategy that liquidates the trader`s positions across some evenly-spaced time points, this rule generates the most robust returns and survives the in- and out-of-sample tests.