Linear regression versus backpropagation networks to predict quarterly stock market excess returns

DOI10.1007/BF00115692zbMATH Open0846.90026MaRDI QIDQ1915795

Ypke Hiemstra

Publication date: 1 July 1996

Published in: Computational Economics (Search for Journal in Brave)

zbMATH Keywords

sensitivity analysisnonparametric testnetwork performanceinput selectionbackpropagation networksout-of-sample predictions

Mathematics Subject Classification ID

Economic time series analysis (91B84)

Cites Work

• Multilayer feedforward networks are universal approximators
• Title not available (Why is that?)
• Title not available (Why is that?)

Related Items (1)

A comparison of linear regression and neural network methods for predicting excess returns on large stocks

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