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Machine Learning Based Pairs by Moraes Sarmento (9 results)
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A Machine Learning based Pairs Trading Investment Strategy (SpringerBriefs in Computational Intelligence)
Book 96 of 472: SpringerBriefs in Applied Sciences and TechnologySeller: Ria Christie Collections, Uxbridge, United Kingdom
Seller rating 5 out of 5 stars
US$ 82.42
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Ships from United Kingdom to U.S.A.Quantity: Over 20 available
Add to basketCondition: New. In.
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A Machine Learning based Pairs Trading Investment Strategy
Book 96 of 472: SpringerBriefs in Applied Sciences and TechnologyUS$ 80.63
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Ships from United Kingdom to U.S.A.Quantity: 10 available
Add to basketPF. Condition: New.
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A Machine Learning based Pairs Trading Investment Strategy
Book 96 of 472: SpringerBriefs in Applied Sciences and TechnologyLanguage: English
Published by Springer International Publishing, 2020
ISBN 10: 3030472507 ISBN 13: 9783030472504
Condition: New.
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A Machine Learning Based Pairs Trading Investment Strategy
Book 96 of 472: SpringerBriefs in Applied Sciences and TechnologyUS$ 134.34
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Ships from United Kingdom to U.S.A.Quantity: 2 available
Add to basketPaperback. Condition: Brand New. 116 pages. 9.25x6.10x0.32 inches. In Stock.
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Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book investigates the application of promising machine learning techniques toaddresstwo 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.
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Taschenbuch. Condition: Neu. A Machine Learning based Pairs Trading Investment Strategy | Simão Moraes Sarmento (u. a.) | Taschenbuch | SpringerBriefs in Applied Sciences and Technology | ix | Englisch | 2020 | Springer | EAN 9783030472504 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
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A Machine Learning based Pairs Trading Investment Strategy (SpringerBriefs in Applied Sciences and Technology)
Book 96 of 472: SpringerBriefs in Applied Sciences and TechnologyUS$ 151.91
US$ 33.83 shipping
Ships from United Kingdom to U.S.A.Quantity: 1 available
Add to basketPaperback. Condition: New. NEW. SHIPS FROM MULTIPLE LOCATIONS. book.
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Condition: new. Questo è un articolo print on demand.
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A Machine Learning based Pairs Trading Investment Strategy
Book 96 of 472: SpringerBriefs in Applied Sciences and TechnologyLanguage: English
Published by Springer, Springer Jul 2020, 2020
ISBN 10: 3030472507 ISBN 13: 9783030472504
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germany
Seller rating 5 out of 5 stars
Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -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.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 116 pp. Englisch.
