Readers might be interested in an article that A. Duran and I have published in Quantitative Finance this year entitled A Profitable Trading and Risk Management Strategy Despite Transaction Cost. In the article, a number of the tools I’ve presented on the blog here have been used in the development of strategy which outperforms the S&P500 in rigorous out-of-sample testing. We’ve made sure to check the robustness of the results, and have performed Monte Carlo simulations while varying the sets of stocks and time periods used in the calculation. Here’s the abstract and a sample figure:
We present a new profitable trading and risk management strategy with transaction cost for an adaptive equally weighted portfolio. Moreover, we implement a rule-based expert system for the daily financial decision making process by using the power of spectral analysis. We use several key components such as principal component analysis, partitioning, memory in stock markets, percentile for relative standing, the first four normalized central moments, learning algorithm, switching among several investments positions consisting of short stock market, long stock market and money market with real risk-free rates. We find that it is possible to beat the proxy for equity market without short selling for S&P 500-listed 168 stocks during the 1998-2008 period and Russell 2000-listed 213 stocks during the 1995-2007 period. Our Monte Carlo simulation over both the various set of stocks and the interval of time confirms our findings.