Machine Learning Based Pairs by Moraes Sarmento (9 results)
Language: English
Published by Springer 2020
Series: SpringerBriefs in Applied Sciences and Technology, Book 96 of 472. Book 96 of 472 - SpringerBriefs in Applied Sciences and Technology
- Softcover
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Published by Springer 2020-07 2020
Series: SpringerBriefs in Applied Sciences and Technology, Book 96 of 472. Book 96 of 472 - SpringerBriefs in Applied Sciences and Technology
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Language: English
Published by Springer International Publishing 2020
Series: SpringerBriefs in Applied Sciences and Technology, Book 96 of 472. Book 96 of 472 - SpringerBriefs in Applied Sciences and Technology
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Language: English
Published by Springer Nature 2020
Series: SpringerBriefs in Applied Sciences and Technology, Book 96 of 472. Book 96 of 472 - SpringerBriefs in Applied Sciences and Technology
- Softcover
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Paperback. Condition: Brand New. 116 pages. 9.25x6.10x0.32 inches. In Stock.
Language: English
Published by Springer, Springer 2020
Series: SpringerBriefs in Applied Sciences and Technology, Book 96 of 472. Book 96 of 472 - SpringerBriefs in Applied Sciences and Technology
- Softcover
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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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Published by Springer 2020
Series: SpringerBriefs in Applied Sciences and Technology, Book 96 of 472. Book 96 of 472 - SpringerBriefs in Applied Sciences and Technology
- Softcover
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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 Heidel…berg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
Language: English
Published by Springer 2020
Series: SpringerBriefs in Applied Sciences and Technology, Book 96 of 472. Book 96 of 472 - SpringerBriefs in Applied Sciences and Technology
- Softcover
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Language: English
Published by Springer 2020
Series: SpringerBriefs in Applied Sciences and Technology, Book 96 of 472. Book 96 of 472 - SpringerBriefs in Applied Sciences and Technology
- Softcover
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Language: English
Published by Springer, Springer Jul 2020 2020
Series: SpringerBriefs in Applied Sciences and Technology, Book 96 of 472. Book 96 of 472 - SpringerBriefs in Applied Sciences and Technology
- Softcover
- Print on Demand
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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 di…vergent 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.
