A1071
Title: Pairs trading using machine learning models
Authors: Spyros Vrontos - University of Essex (United Kingdom) [presenting]
Abstract: The application of machine learning models to pairs trading is explored, a popular market-neutral trading strategy that involves taking simultaneous long and short positions in two correlated securities. The approach leverages advanced machine learning techniques to enhance the selection and timing of trades. By employing machine learning models, the aim is to improve the prediction accuracy of price movements and the overall profitability of the strategy. The performance of these models is evaluated using historical market data, comparing their effectiveness against conventional pairs trading methods.
