ISMIS 2017 Data Mining Competition: Trading Based on Recommendations - XGBoost Approach with Feature Engineering

Abstract

This paper presents an approach to predict trading based on recommendations of experts using XGBoost model, created during ISMIS 2017 Data Mining Competition: Trading Based on Recommendations. We present a method to manually engineer features from sequential data and how to evaluate its relevance. We provide a summary of feature engineering, feature selection, and evaluation based on experts recommendations of stock return.