A Better Way to Trade Small Caps: The Power of Volume Volatility in Algorithm Design

Abstract

The goal of this research was to study methods of altering the standard approach to volume weighted average price such that it respects stock-specific volume volatility. The early returns are promising, and we think this concept can be applied to other algorithms where inappropriately tight constraints create excess cost. In this article, we review the state of the art for volume forecasting and how these efforts are rewarded. We show the results of a random trial of orders that use a static tolerance around the target schedule versus orders that use a tolerance set by the volume volatility of the stock. The results show less aggressive trading. We also argue that traders should not choose algorithms based on stock characteristics. Instead, algorithm choice should focus on the tradeoff between cost and timing risk.