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A Machine Learning based Pairs Trading Investment StrategyImplementation

A Machine Learning based Pairs Trading Investment Strategy: Implementation [This chapter discusses some specific research implementation aspects relevant to test the two previously suggested methods. It provides a thorough analysis of the adopted dataset, including the motivation for using ETFs, the sectors considered, the preprocessing steps followed and the partitions and time windows studied. It proceeds by describing how each research stage is implemented, regarding the test conditions and the algorithms used. At last, an in-depth explanation concerning the simulation conditions is provided: the portfolio construction is analyzed, followed by the transaction costs considered, and the market entry and exit points. A description regarding the evaluation metrics used and the underlying rationale can be found at the end of the chapter.] http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png

A Machine Learning based Pairs Trading Investment StrategyImplementation

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Publisher
Springer International Publishing
Copyright
© The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021
ISBN
978-3-030-47250-4
Pages
51 –74
DOI
10.1007/978-3-030-47251-1_5
Publisher site
See Chapter on Publisher Site

Abstract

[This chapter discusses some specific research implementation aspects relevant to test the two previously suggested methods. It provides a thorough analysis of the adopted dataset, including the motivation for using ETFs, the sectors considered, the preprocessing steps followed and the partitions and time windows studied. It proceeds by describing how each research stage is implemented, regarding the test conditions and the algorithms used. At last, an in-depth explanation concerning the simulation conditions is provided: the portfolio construction is analyzed, followed by the transaction costs considered, and the market entry and exit points. A description regarding the evaluation metrics used and the underlying rationale can be found at the end of the chapter.]

Published: Jul 14, 2020

Keywords: Exchange-Traded Funds; Data preprocessing; Trading simulation; Portfolio construction; Transaction costs

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