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A Machine Learning based Pairs Trading Investment StrategyPairs Trading—Background and Related Work

A Machine Learning based Pairs Trading Investment Strategy: Pairs Trading—Background and Related... [This chapter introduces some important mathematical and financial concepts required to fully understand the workings of a Pairs Trading strategy. These include the concepts of mean-reversion, stationarity, and cointegration. Subsequently, it goes over some widely used strategies to find pairs for trading, mentioning relevant research work in the field. Next, the most commonly used model in a Pairs Trading setup, the threshold-based model, is explained in detail. To complement, other possible alternatives are introduced as well. At last, an overview of the current state-of-the-art concerning the application of Machine Learning in the field of Pairs Trading is provided.] http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png

A Machine Learning based Pairs Trading Investment StrategyPairs Trading—Background and Related Work

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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
7 –19
DOI
10.1007/978-3-030-47251-1_2
Publisher site
See Chapter on Publisher Site

Abstract

[This chapter introduces some important mathematical and financial concepts required to fully understand the workings of a Pairs Trading strategy. These include the concepts of mean-reversion, stationarity, and cointegration. Subsequently, it goes over some widely used strategies to find pairs for trading, mentioning relevant research work in the field. Next, the most commonly used model in a Pairs Trading setup, the threshold-based model, is explained in detail. To complement, other possible alternatives are introduced as well. At last, an overview of the current state-of-the-art concerning the application of Machine Learning in the field of Pairs Trading is provided.]

Published: Jul 14, 2020

Keywords: Mean-reversion; Stationarity; Correlation; Cointegration; Machine learning

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