International high-frequency arbitrage for cross-listed stocks |
| |
| Institution: | 1. Université de Montréal, Canada;2. HEC Montréal, Canada;1. Joint Research Centre of the European Commission (JRC), Via E. Fermi 2749, 21027 Ispra (VA), Italy;2. University of Edinburgh Business School, 29 Buccleuch Pl, Edinburgh EH8 9JS, United Kingdom;3. Queen''s University Belfast, Queen''s Management School, 185 Stranmillis Road, Belfast, Northern Ireland BT9 5EE, United Kingdom;4. University College Dublin Michael Smurfit Graduate School of Business, Carysfort Ave, Carrysfort, Blackrock, Co. Dublin, Ireland;1. Chongyang Institute for Financial Studies, Renmin University of China, 6th Floor, Culture Building, No.59 Zhongguancun Avenue, Haidian District, Beijing 100872, China;2. School of Finance, Renmin University of China, Room 812, Mingde Building, No. 59 Zhongguancun Avenue, Haidian District, Beijing 100872, China;1. Worcester Polytechnic Institute, 100 Institute Rd, Worcester, MA 01609, United States of America;2. Broadwell College of Business and Economics, Fayetteville State University, Fayetteville, NC 28301., United States of America;1. School of Mathematics, Southwest Jiaotong University, Chengdu, China;2. School of Finance, Renmin University of China, Beijing, China;3. School of Finance, Nanjing University of Finance and Economics, Nanjing, China |
| |
| Abstract: | We explore high-frequency arbitrage activities on international cross-listed stocks and develop a methodology to study the effect of information latency in high-frequency trading. We derive statistical arbitrage bounds for a mean-reverting synthetic instrument engineered from cross-listed stock prices, and we propose a new strategy that takes advantage of price deviations outside these bounds. Market frictions such as trade costs, inventory control, and arbitrage risks are considered. The strategy is tested with cross-listed stocks involving three exchanges in Canada and the United States in 2019. The annual net profit with the limit order strategy is around US$6 million, whereas the market order version is not profitable because of the great interconnectedness between exchanges in our data. |
| |
| Keywords: | |
| 本文献已被 ScienceDirect 等数据库收录！ |
|
