Volatility Modeling and Prediction : The Role of Price Impact

In this paper, we are interested in exploring the role of price impact, derived from the order book, in modeling and predicting stock volatility. This is motivated by the microstructure literature that focuses on the mechanics of price formation and its relevance to market quality. Using a comprehensive dataset of intraday bids, asks, and three levels of market depths for 148 stocks in the Shanghai Stock Exchange from 2005 to 2016, we find substantial intraday impact from buy and sell limit and market orders on stock prices. More importantly, the permanent price impact at the daily level is a significant determinant in the volatility estimation for all sample stocks as shown by the panel VAR estimation, which allows us to examine simultaneously the dynamics of price impact on all sample stocks. Furthermore, when we augment traditional volatility models with the time series of daily price impact, the augmented models produce significantly more accurate forecasts at the one-day horizon. These forecasts from the augmented models offer economic gains to a mean-variance utility investor in a portfolio setting