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Algorithmic Trading Strategies for Informed Traders
This research found that using the implicit cost minimization trading strategy proposed in this paper has greater advantage in reducing transaction costs.
Abstract
Informed traders usually choose to trade a large number of stocks in a short period of time in order to take advantage of the time that they can profit from private information, which will inevitably cause a large impact on the share price of individual stocks and increase the implicit cost of trading. This research constructs a strategy for minimizing the implicit costs of informed traders based on the implicit costs of market shocks, opportunity costs, and time risk costs faced by informed traders in their trading process, and derive the theoretical optimal solution of this strategy through a nonlinear programming model. The optimal solution is also compared with the volume-weighted average price strategy using numerical examples, and this research found that using the implicit cost minimization trading strategy proposed in this paper has greater advantage in reducing transaction costs.