Application of Machine Learning Tools in Predictive Modeling of Pairs Trade in Indian Stock Market

Abstract

The paper applies machine learning tools in pairs trading. Three different algorithms, namely, Support Vector Machine (SVM), Random Forest (RF) and Adaptive Neuro Fuzzy Inference System (ANFIS), have been used for predictive modeling of the value of the ratio of share prices of pairs of companies. The study considers nine different independent variables/features for forecasting. The analytical framework combines the mean reverting property of the movement of a pair of prices along with technical indicators. We also use feature selection algorithms for justification of the nine independent variables. The results support our methodology and also selection of the features for prediction.