 Forecasting U.S. recessions using over 150 years of data: Stock-market moments versus oil-market momentsElie Bouri, Rangan Gupta, Christian Pierdzioch and Onur Polat Finance Research Letters, 2024, vol. 69, issue PB Abstract: Using monthly data from 1871 to 2024 and logistic models with shrinkage estimators, we compare the contribution of stock and oil-market moments (returns, volatility, skewness, and kurtosis) to the accuracy of out-of-sample forecasts of U.S. recessions at various forecast horizons, while controlling for standard macroeconomic predictors and the total connectedness indexes of the moments. Adding stock-market moments to the potential predictors improves significantly the accuracy of out-of-sample forecasts at an intermediate forecast horizon, where the lagged recession dummy, term spread, and stock returns are top predictors. Oil-market moments and connectedness indexes do not contribute much to forecast accuracy. Keywords: Recessions; Stock-market and oil-market moments; Forecasting; Shrinkage estimators; AUC statistics (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:finlet:v:69:y:2024:i:pb:s154461232401208x DOI: 10.1016/j.frl.2024.106179 Access Statistics for this article Finance Research Letters is currently edited by R. Gençay More articles in Finance Research Letters from Elsevier |
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