Time series regression-based pairs trading in the Korean equities market

Saejoon Kim, Jun Heo

Research output: Contribution to journalArticle

4 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)755-768
Number of pages14
JournalJournal of Experimental and Theoretical Artificial Intelligence
Volume29
Issue number4
DOIs
Publication statusPublished - 2017 Jul 4

Fingerprint

Equity
Time series
Profitability
Regression
Arbitrage
Trigger
Anomaly
Excess
Profit
Data analysis
Market

Keywords

  • ARIMA
  • cointegration
  • DTW
  • Pairs trading
  • SVR

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Software
  • Artificial Intelligence

Cite this

Time series regression-based pairs trading in the Korean equities market. / Kim, Saejoon; Heo, Jun.

In: Journal of Experimental and Theoretical Artificial Intelligence, Vol. 29, No. 4, 04.07.2017, p. 755-768.

Research output: Contribution to journalArticle

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