Time series regression-based pairs trading in the Korean equities market
- Authors
- Kim, Saejoon; Heo, Jun
- Issue Date
- 2017
- Publisher
- TAYLOR & FRANCIS LTD
- Keywords
- Pairs trading; ARIMA; SVR; DTW; cointegration
- Citation
- JOURNAL OF EXPERIMENTAL & THEORETICAL ARTIFICIAL INTELLIGENCE, v.29, no.4, pp.755 - 768
- Indexed
- SCIE
SCOPUS
- Journal Title
- JOURNAL OF EXPERIMENTAL & THEORETICAL ARTIFICIAL INTELLIGENCE
- Volume
- 29
- Number
- 4
- Start Page
- 755
- End Page
- 768
- URI
- https://scholar.korea.ac.kr/handle/2021.sw.korea/86378
- DOI
- 10.1080/0952813X.2016.1259265
- ISSN
- 0952-813X
- Abstract
- Pairs trading is an instance of statistical arbitrage that relies on heavy quantitative data analysis to profit by capitalising low-risk trading opportunities provided by anomalies of related assets. A key element in pairs trading is the rule by which open and close trading triggers are defined. This paper investigates the use of time series regression to define the rule which has previously been identified with fixed threshold-based approaches. Empirical results indicate that our approach may yield significantly increased excess returns compared to ones obtained by previous approaches on large capitalisation stocks in the Korean equities market.
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Collections - College of Engineering > School of Electrical Engineering > 1. Journal Articles
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