Algoritmo para otimização da estratégia de investimento em desempenho contrário

Abstract

The contrarian investing strategy consists of identifying a movement of a majority of investors in the stock market and trading against that movement. Although there is literature on the subject confirming the effectiveness of the strategy in generating excess return in relation to the market index, there seems to be no scientific work whose objective was to present the best way to implement the strategy in a given country . The present work aimed to fill this gap by estimating how each strategy implementation parameter contributes, on average, in the generation of Information Ratio. These estimates were made using the Ordinary Least Squares Method, performed on a database of simulation results (10,000 for the Brazilian case and 1,200 for the US case) of different random implementations of the strategy. These simulations were performed using an algorithm that represents the implementation of the strategy. Based on the coefficients estimated by the OLS, it was possible to identify the combination of parameters that maximizes the Information Ratio. The out-of-sample results for the Brazilian case were in the sense that this strategy optimization procedure is capable of generating an Information Ratio greater than the average of the random simulations, but still negative. In the US case, the results were inconclusive due to the small number of simulations performed due to the high computational cost, related to time and processing capacity.