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The Equity Premium Puzzle: An Artificial Neural Network ApproachShee Q. WongLabovitz School of Business Nik R. Hassanaffiliation not provided to SSRN Ehsan H. FerozUniversity of Washington - Tacoma-Milgard School of Business; Vernon Zimmerman Center, University of Illinois; US Government Accountability Office August 8, 2008 Review of Accounting and Finance, Vol. 6, No. 2, pp. 150-161, 2007 Abstract: 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.
Number of Pages in PDF File: 23 Keywords: Equity premium, Forecasting, CAPM, Neural networks JEL Classification: C45, G1, G2, G3 Accepted Paper SeriesDate posted: August 8, 2008 ; Last revised: June 15, 2009Suggested CitationContact Information
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