A machine learning based pairs trading investment strategy / Simão Moraes Sarmento, Nuno Horta.
Moraes Sarmento, Simão.; Horta, Nuno C. G.
2021
Q325.5
Available Online

Linked e-resources

Linked Resource Online Access
Concurrent users Unlimited
Authorized users Authorized users
Document Delivery Supplied Can lend chapters, not whole ebooks

Details

Title A machine learning based pairs trading investment strategy / Simão Moraes Sarmento, Nuno Horta.
Author Moraes Sarmento, Simão.
ISBN 9783030472511 (electronic bk.)
3030472515 (electronic bk.)
9783030472504
DOI https://doi.org/10.1007/978-3-030-47251-1
Publication Details Cham : Springer, 2021.
Language English
Description 1 online resource (108 pages)
Item Number 10.1007/978-3-030-47251-1 doi
10.1007/978-3-030-47
Call Number Q325.5
Dewey Decimal Classification 006.3/1
Summary 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.
Bibliography, etc. Note Includes bibliographical references.
Access Note Access limited to authorized users.
Source of Description Description based on print version record.
Added Author Horta, Nuno C. G.
Series SpringerBriefs in applied sciences and technology.
Available in Other Form A Machine Learning Based Pairs Trading Investment Strategy
Linked Resources Online Access
Record Appears in Online Resources > Ebooks
All Resources
Introduction
Pairs Trading
Background and Related Work
Proposed Pairs Selection Framework
Proposed Trading Model
Implementation
Results
Conclusions and Future Work.

Browse Subjects

Show more subjects...

Statistics

from
to
Export