Author(s)

Skander Slim

Laboratory Research for Economy, Management and Quantitative Finance (LaREMFiQ), Institute of High Commercial Studies, University of Sousse, Sousse, Tunisia.

This paper examines the information content of trading volume in terms of forecasting the conditional volatility and market risk of international stock markets. The performance of parametric Value at Risk (VaR) models including the traditional RiskMetrics model and a heavy-tailed EGARCH model with and without trading volume is investigated during crisis and post-crisis periods. Our empirical results provide compelling evidence that volatility forecasts based on volume-augmented models cannot be outperformed by their competitors. Furthermore, our findings indicate that including trading volume into the volatility specification greatly enhances the performance of the proposed VaR models, especially during the crisis period. However, the volume effect is fairly overshadowed by the sufficient accuracy of the heavy-tailed EGARCH model, during the post-crisis period.

Value at Risk, Risk Management, Trading Volume, EGARCH Model

Slim, S. (2016) The Role of Trading Volume in Forecasting Market Risk. Journal of Financial Risk Management, 5, 22-34. doi: 10.4236/jfrm.2016.51004.