Abstract
In this article, we discuss the balance between risk and cost in the context of portfolio trading algorithms. We provide examples of how trading a basket in a coordinated manner can lead to more efficient execution than trading each stock independently. Specifically, by trading buy and sell orders in a synchronized way, advanced algorithms can execute more passively, reducing cost without increasing risk. We discuss how this cost–risk trade-off can be achieved via an optimization approach, even when additional constraints such as cash- or beta-neutrality are applied. Finally, we address the importance of incorporating intraday variation in cost and risk when formulating an optimal algorithmic trading strategy.
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