This book investigates the application of promising Machine Learning techniques to address two problems: (i) how to find profitable Pairs while constraining the search space and (ii) how to avoid long decline periods due to prolonged divergent pairs.
It also proposes the integration of an unsupervised Learning algorithm, OPTICS, to handle problem (i), and demonstrates that the suggested technique can outperform the common Pairs search methods, achieving an average portfolio Sharpe rati.
This book investigates the application of promising Machine Learning techniques to address two problems: (i) how to find profitable Pairs while constraining the search space and (ii) how to avoid long decline periods due to prolonged divergent pairs