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A Machine Learning based Pairs Trading Investment StrategyProposed Trading Model

A Machine Learning based Pairs Trading Investment Strategy: Proposed Trading Model [This chapter starts by exploring the issues associated with most Pairs Trading models, thus motivating the rationale for this work’s second research question: “Can a forecasting-based trading model achieve a more robust performance?”. A novel trading model, which makes use of forecast data to make trading decisions at the present time, is introduced. The reasoning for each model component is analyzed, and an illustrative example is provided. The remaining part of the chapter investigates which forecasting algorithm may be more suitable to integrate the proposed trading model, exploring the ARMA model, along with two Deep Learning based models, an LSTM and an LSTM Encoder-Decoder.] http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png

A Machine Learning based Pairs Trading Investment StrategyProposed Trading Model

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References (8)

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
37 –49
DOI
10.1007/978-3-030-47251-1_4
Publisher site
See Chapter on Publisher Site

Abstract

[This chapter starts by exploring the issues associated with most Pairs Trading models, thus motivating the rationale for this work’s second research question: “Can a forecasting-based trading model achieve a more robust performance?”. A novel trading model, which makes use of forecast data to make trading decisions at the present time, is introduced. The reasoning for each model component is analyzed, and an illustrative example is provided. The remaining part of the chapter investigates which forecasting algorithm may be more suitable to integrate the proposed trading model, exploring the ARMA model, along with two Deep Learning based models, an LSTM and an LSTM Encoder-Decoder.]

Published: Jul 14, 2020

Keywords: Time-series forecasting; ARMA; Deep Learning; LSTM; Encoder-Decoder

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