Forecasting commodity futures returns with stepwise regressions: do commodity-specific factors help?

DOI10.1007/s10479-020-03515-wzbMath1477.62292OpenAlexW3004787732MaRDI QIDQ2241123

Manuela Pedio, Massimo Guidolin

Publication date: 8 November 2021

Published in: Annals of Operations Research (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10479-020-03515-w

zbMATH Keywords

predictabilitystepwise regressioncommodity returnsportfolio back-testing

Mathematics Subject Classification ID

Inference from stochastic processes and prediction (62M20) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Applications of statistics to actuarial sciences and financial mathematics (62P05) Hypothesis testing in multivariate analysis (62H15) Portfolio theory (91G10)

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Cites Work

• Stepwise regression data envelopment analysis for variable reduction
• Handbook of economic forecasting. Volume 1
• A sequential predictor retraining algorithm and its application to market prediction
• Asset allocation under multivariate regime switching
• Estimating stochastic discount factor models with hidden regimes: applications to commodity pricing
• Temporal clustering of time series via threshold autoregressive models: application to commodity prices
• Can commodities dominate stock and bond portfolios?
• Forecasting Using Principal Components From a Large Number of Predictors
• EFFECTS OF INDEX‐FUND INVESTING ON COMMODITY FUTURES PRICES
• A Stepwise AIC Method for Variable Selection in Linear Regression

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