A new algorithmic trading strategy for high-frequency trading

Over the past decade,financial markets have witnessed an explosion of algorithmic trading strategy which can help investors efficiently reduce transaction cost. In order to reduce the trading cost,investors usually break block orders into small pieces in high-frequency trading. However,the behavior of such order splitting may result in inevitable opportunity cost as well as timing risk. This paper establishes a new algorithmic trading strategy to minimize implicit trading costs,including the market impact,opportunity cost,timing risk and the price appreciation. We find the performance of our optimal algorithmic trading strategy is better than that of MIOC or VWAP strategies in all the cases of increased,decreased and U-shaped execution probability. The new algorithmic trading strategy established in this paper can effectively reduce the trading cost.