A machine learning based pairs trading investment strategy [electronic resource] / Simão Moraes Sarmento, Nuno Horta.

Unlimited

Authorized users

Can lend chapters, not whole ebooks

A machine learning based pairs trading investment strategy [electronic resource] / Simão Moraes Sarmento, Nuno Horta.

9783030472511 (electronic bk.)
3030472515 (electronic bk.)
9783030472504

Cham : Springer, 2021.

English

1 online resource (108 pages).

10.1007/978-3-030-47251-1 doi
10.1007/978-3-030-47

Q325.5

006.3/1

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 ratio of 3.79, in comparison to 3.58 and 2.59 obtained using standard approaches. For problem (ii), the authors introduce a forecasting-based trading model capable of reducing the periods of portfolio decline by 75%. However, this comes at the expense of decreasing overall profitability. The authors also test the proposed strategy using an ARMA model, an LSTM and an LSTM encoder-decoder.

Includes bibliographical references.

Access limited to authorized users.

Description based on print version record.

SpringerBriefs in applied sciences and technology.

Online Resources > Ebooks
All Resources