The Equity Premium Puzzle: An Artificial Neural Network Approach
23 Pages Posted: 8 Aug 2008 Last revised: 4 Jan 2019
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
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