Non-linear forecasting of stock returns: Does volume help?

Citation

McMillan D (2007) Non-linear forecasting of stock returns: Does volume help?. International Journal of Forecasting, 23 (1), pp. 115-126. https://doi.org/10.1016/j.ijforecast.2006.06.002

Abstract
The testing for and estimation of non-linear dynamics in equity returns is a growing area of empirical finance research. This paper extends this line of research by examining whether a hitherto unconsidered variable, namely volume, imparts non-linear dynamics within equity returns and whether it has forecasting power. A significant amount of evidence supports a negative relationship between volume and future returns, which in turn suggests that volume could act as a suitable threshold variable. The results presented here provide evidence of a logistic smooth-transition model for four international stock market returns, with lagged volume as the threshold. Further, this model provides better out-of-sample forecasts than a corresponding logistic smooth-transition autoregressive model, a simple AR model and a random walk model based on a trading rule. In addition, this model also provides better forecasting performance in three cases against alternate non-linear specifications. This provides evidence in favour of non-linear dynamics, in contrast with previous evidence, which had suggested the relative failure of non-linear models in forecasting exercises.

Keywords
Stock market returns; volume; LSTR model; forecasting

Journal
International Journal of Forecasting: Volume 23, Issue 1

People

Professor David McMillan

Professor in Finance, Accounting & Finance