关键词: 算法交易, VWAP策略, 成交量分解, 日内周期结构

Abstract: By splitting the large commissioned orders and tracking the average market transaction prices, the traditional VWAP(volume weighted average price)strategies can minimize the market impact costs. Meanwhile, forecasting accurately the distribution of the intraday volume is the key to use the VWAP strategies to split orders. Investigating in detail the modeling methods and forecasting trading volume of the existing improved VWAP strategies, we find that the periodic structure of stock’s intraday volume is difficult to be separated completely, and the existing models are limited by the sample and difficult to apply to most stocks. From the perspective of the relationship between stocks’ volume and the trends of market volume, we deduce the equation of the stock volume and market volume, construct individual stocks’ factor loading on the market volume effects, and then decompose the intraday volume into two parts to forecast the trading volume distribution: one part describing the volume changes affected by the market; the second part reflecting the specific volume changes of the individual stock. Moreover, we build a dynamic VWAP strategy. The empirical results show that our trading volume decomposition model can effectively separate the periodic structure of the stocks’ intraday volume. Compared with the traditional VWAP strategies, our improved dynamic VWAP strategy has not only broader applicability but also smaller tracking error, and reduces the market impact costs more effectively.

Key words: algorithmic trading, VWAP strategy, trading volume decomposition, periodic structure of stock’s intraday volume