Improving Pair Trading Performances with Structural Change Detections and Revised Trading Strategies

Hao Han Chang, Tian Shyr Dai, Kuan Lun Wang, Chao Hsien Chu, Jun Zhe Wang

研究成果: Conference contribution同行評審

摘要

A pairs trading strategy (PTS) forms a market-neutral portfolio whose value moves back and forth around a certain price level. An investor can long (short) the portfolio when its price moves below (above) the price level and cash out when the portfolio value converges back to earn the price difference. The profit for each successful trading is relatively small, so transaction costs and structural changes (that invalidate market-neutral property) could significantly erode the profits. This paper proposes three improvement methods to reduce the costs and stabilize aggregated profits. First, we change the open and close thresholds to increase the number of transactions; this would increase and stabilize the aggregated profits due to the law of large numbers. Second, we derive the expected return for each trading before opening the portfolio and execute the trading only when the expected return exceed the transaction cost. Third, we detect the structural change with our revised (statistical) tests to close the position in advance to reduce losses. Empirical studies show that our three methods can be simultaneously adopted to improve trading performance significantly.

原文English
主出版物標題Proceedings - 2020 International Conference on Pervasive Artificial Intelligence, ICPAI 2020
發行者Institute of Electrical and Electronics Engineers Inc.
頁面105-109
頁數5
ISBN(電子)9780738142623
DOIs
出版狀態Published - 十二月 2020
事件1st International Conference on Pervasive Artificial Intelligence, ICPAI 2020 - Taipei, Taiwan
持續時間: 3 十二月 20205 十二月 2020

出版系列

名字Proceedings - 2020 International Conference on Pervasive Artificial Intelligence, ICPAI 2020

Conference

Conference1st International Conference on Pervasive Artificial Intelligence, ICPAI 2020
國家Taiwan
城市Taipei
期間3/12/205/12/20

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