23 Pages Posted: 8 Aug 2008 Last revised: 28 Aug 2014
Date Written: August 8, 2008
This paper presents evidence suggesting that artificial neural networks approach (ANNs) outperform traditional statistical methods and can forecast equity premiums reasonably well. The study replicates out-of-sample estimates of regression using ANN with economic fundamentals as inputs. The dividend yield variable was found to produce the best out-of-sample forecasts for equity premium. This result is useful for capital asset pricing model and in asset allocation decisions.
Keywords: Equity premium, Forecasting, CAPM, Neural networks
JEL Classification: C45, G1, G2, G3
Suggested Citation: Suggested Citation
Wong, Shee Q. and Hassan, Nik R. and Feroz, Ehsan H., The Equity Premium Puzzle: An Artificial Neural Network Approach (August 8, 2008). Review of Accounting and Finance, Vol. 6, No. 2, pp. 150-161, 2007 . Available at SSRN: https://ssrn.com/abstract=1211962