“Taps”: A trading approach based on deterministic sign patterns

Abstract

We propose a new methodology for trading financial instruments based on deterministic sign patterns. These patterns are obtained from the m-dimensional elementary sample space consisting of -1,1m, the two possible signs for trading and with m varying. The collection of all possible sign combinations coming from this sample space creates a zero-cost trading strategy and we consider strategies that are selected from rotations among the possible sign sequences using several statistical criteria. Performing simulations, based on a geometric Brownian motion, we find that – on average – our strategies can outperform the buy & hold benchmark about 30% of the time in terms of total return and around 60% of the time in terms of maximum drawdown. We then illustrate the practical efficacy of the proposed strategies using daily returns from the S&P500 index, two of the largest Chinese stock market indices, the CSI300 and the SSE50, and three exchange traded funds (ETFs). Our results strongly suggest performance improvements over the corresponding buy & hold benchmarks and, furthermore, that these performance differences can be attributed to the entropy of the US and Chinese markets: we find that the two Chinese indices, which have larger entropy than the US index, provide considerable performance enhancements when traded based on our suggested methodology.