Optimizing Technical Analysis Indicator Parameters with Grey Wolf Optimization

Abstract

Technical market indicators play an important role in the technical analysis due to their key role of predicting trend changes and making trade decisions. Besides choosing an indicator to use, deciding the right parameters for higher returns is a common problem for market professionals. Even though technical indicators with common parameters create a general perspective for most of the financial securities, it is possible to tune these parameters specific for each security. In this paper, Grey Wolf Optimization (GWO) algorithm is proposed to determine the right parameters to achieve the maximum Sharpe Ratio on 5 different U.S. stocks individually. Relative Strength Index (RSI) is chosen to be optimized. Optimizations are implemented for two scenarios, with or without considering the trend of security. After optimizing the RSI parameters, mean returns of the stocks increased 24.987% without and 104.395% with trend specification on test sets. Even though this is a preliminary study, the results indicate that GWO can be useful for optimizing algorithmic trading strategy parameters.