Earticle

초록

영어

In this study, the well-known pairs trading strategy, one of typical market neutral strategies, is modified to be able to utilize high frequency equity data, and it is applied to the constituent shares of the KOSPI (Korea Composite Stock Price Index) 100 index. This study is distinguished from the most of previous work on the traditional pairs trading strategy in that we introduce the use of high frequency data in strategy modeling instead of daily closing prices, which allows us to analyze the performance of the strategy in high frequency domain. More specifically, we extract the trading signal, which is based on the spread between stocks of pair, by estimating time adaptive regression coefficients using the Kalman filter. As for underlying universe for the strategy, we confine ourselves to consider the most liquid 100 stocks in KOSPI as a basket for our experiment. Major findings include that arbitrage profitability is in fact present without being subject to market condition even when conservative transaction costs are taken into account. In particular, our strategy outperforms better in bear market condition while it varies depending on industry group. The results also demonstrate that the performance of the strategy is dependent upon timing of the market entry; the performance of trades entered around at opening and closing of the daily market is appeared to be relatively superior to that of trades executed in the rest of daily trading hours. Furthermore, we introduce an enhanced version of the strategy, which selects high-ranking pairs to trade for the next time period based on a set of in-sample statistics. It is verified that the enhanced strategy has better profitability and reliability compared to our basic strategy.

목차

Abstract
 I. Introduction
  1. Pairs trading strategy
  2. Application of the high frequency data to strategy modeling
  3. The aims of the study
  4. The brief overview of the study
  5. Organization of the paper
 II. Literature Review
  1. Market neutral strategy and high frequency data
  2. Time adaptive model – the Kalman Filter
  3. Cointegration
  4. Ornstein-Uhlenbeck process
 III. Data and Methodology
  1. Data
  2. Methodology
 IV. Results and Analysis
  1. Performance Summary
  2. Performance of the Strategy by Industry Group
  3. Intraday Performance
  4. Performance of the Enhanced Model
 V. Conclusion
 References
 Appendices

키워드

저자

• Jooyoung Yun [ Mirae Asset Maps Global Investments, Seoul, Korea ] Corresponding author
• Kangwhee Kim [ Harvard University, School of Engineering and Applied Science, Cambridge, USA ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  한국재무학회 학술대회

• 간기

  부정기

• 수록기간

  2006~2024

• 십진분류

  KDC 325 DDC 330