Trading index mutual funds with evolutionary forecasting

This paper proposes an intuitive strategy for trading index mutual funds via the prediction of the next-day closing index of a stock market. The prediction model is built from a set of basic technical indicators. The model is optimized with a self-adaptive differential evolution algorithm in which users require no expertise in parameter settings. The proposed strategy is evaluated using Nikkei, FTSE, S&P500, Dow Jones Industrial Average, and NASDAQ indices. The experiment demonstrates that the proposed strategy results in higher returns than those from buy-and-hold strategy, which is generally employed by index mutual funds.