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.
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