A Quantitative Investment Strategy Based On High-frequency Data Between AH Shares

This paper presents a quantitative investment strategy based on high-frequencytrading. Selecting cross-listing companies as a sample, we examine the feasibility ofcross-border arbitrage strategies using AH shares. Specifically, we create a tradingstrategy using residual of the model to arbitrage by modeling the spread between theAH shares.This paper also provides a trading strategy under high-frequency situation andusing Markov chain transition probability matrix to find trading opportunities.Meanwhile, a detailed analysis is made about the transaction costs whenimplementing the trade tactics. The results show that, due to different transitionprobabilities, the strategy gets a net profit in buying circumstance. However, in theshort sale situation, it manifests a loss. In the further analysis of profit group, the scaleof transaction cost relies on market situation in implementation.Finally, considering all transaction costs, this strategy still gets a10%annualized gainand achieves a very good performance. Hence, this strategy has a practical implicationfor institutional investors.