Prediction of Stock Returns: A New Way to Look at It

DOI10.2143/AST.33.2.503700zbMath1095.91019OpenAlexW4253137383MaRDI QIDQ4661691

Stefan Sperlich, Jens Perch Nielsen

Publication date: 30 March 2005

Published in: ASTIN Bulletin (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.2143/ast.33.2.503700

zbMATH Keywords

cross validationdividend price ratio

Mathematics Subject Classification ID

Related Items (5)

Forecasting benchmarks of long-term stock returns via machine learning ⋮ Nonparametric long term prediction of stock returns with generated bond yields ⋮ Nonparametric prediction of stock returns based on yearly data: the long-term view ⋮ Long-term real dynamic investment planning ⋮ Comments on: Model-free model-fitting and predictive distributions

Cites Work

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• Smoothing Parameter Selection in Nonparametric Regression Using an Improved Akaike Information Criterion
• A discussion of parameter and model uncertainty in insurance

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