Proceedings of the 2022 2nd International Conference on Business Administration and Data Science (BADS 2022)

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Cointegration Approach for the Pair Trading based on the Kalman Filter

Authors
Jia Yu1, *
1Graduate School of Information, Production and Systems, Waseda University, Fukuoka, Japan
*Corresponding author. Email: joanna-yu@suou.waseda.jp
Corresponding Author
Jia Yu
Available Online 29 December 2022.
DOI
10.2991/978-94-6463-102-9_66How to use a DOI?
Keywords
Pairs Trading Strategy; Cointegration Approach; Kalman Filter; Time Series Analysis; State-space Model
Abstract

The conventional pairs trading strategy of cointegration approach employs a fixed cointegration coefficient, limiting the length of the applicable trading period and negatively influencing profitability. Given these two problems, this paper proposes a pairing trading system based on the co-integration method of the Kalman filter, which can provide investors with profitable trading pairing and market timing. First of all, study the co-integration relationship between every two stocks and co-integrate the stock as a trading pair. Then, based on the analysis of the trading value of the trading stock price by the state-space model, a Kalman filter system to update the co-integer coefficient value is designed. Finally, a trading strategy is developed for the proposed method. In addition, simulations were conducted to assess the performance of the proposed trading system. According to the conventional method and the recommended trading method, twenty pairs of cointegrated stocks were selected to build trading pairs respectively. The simulation results prove that the proposed approach has higher profitability and a more extended trading period than the conventional approach.

Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the 2022 2nd International Conference on Business Administration and Data Science (BADS 2022)
Series
Atlantis Highlights in Computer Sciences
Publication Date
29 December 2022
ISBN
10.2991/978-94-6463-102-9_66
ISSN
2589-4900
DOI
10.2991/978-94-6463-102-9_66How to use a DOI?
Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Jia Yu
PY  - 2022
DA  - 2022/12/29
TI  - Cointegration Approach for the Pair Trading based on the Kalman Filter
BT  - Proceedings of the 2022 2nd International Conference on Business Administration and Data Science (BADS 2022)
PB  - Atlantis Press
SP  - 633
EP  - 642
SN  - 2589-4900
UR  - https://doi.org/10.2991/978-94-6463-102-9_66
DO  - 10.2991/978-94-6463-102-9_66
ID  - Yu2022
ER  -