Electricity Sales and Forecasting of Stock Market Realized Volatility: A State-Level Analysis of the United States

Matteo Bonato (), Oguzhan Cepni, Rangan Gupta () and Christian Pierdzioch ()
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Matteo Bonato: Department of Economics and Econometrics, University of Johannesburg, Auckland Park, South Africa; IPAG Business School, 184 Boulevard Saint-Germain, 75006 Paris, France; B-CCaS, University of Edinburgh Business School
Rangan Gupta: Department of Economics, University of Pretoria, Private Bag X20, Hatfield 0028, South Africa
Christian Pierdzioch: Department of Economics, Helmut Schmidt University, Holstenhofweg 85, P.O.B. 700822, 22008 Hamburg, Germany

No 202540, Working Papers from University of Pretoria, Department of Economics

Abstract: We study the out-of-sample forecasting value of and state-level and market-wideoverall commercial, industrial, and residential electricity sales for monthly state-level (1995--2025) realized stock market volatility (RV) of the United States (U.S.). We control for state-level and market-wide realized moments (leverage, skewness, kurtosis, and tail risks). We estimate our forecasting models using a boosting algorithm, and two alternative statistical learning algorithms (forward best predictor selection and random forests). We find evidence that realized moments have predictive power for subsequent RV at forecast horizons up to one year in some model configurations, while evidence of predictive power of the growth rate of electricity sales, whether measured at state-level or at the market-level, is mixed and mainly concentrated, on average across states, at the short forecast horizon.

Keywords: Stock market; Realized volatility; Electricity sales; Statistical learning; Forecasting (search for similar items in EconPapers)
JEL-codes: C22 C53 G10 G17 Q41 (search for similar items in EconPapers)
Pages: 76 pages
Date: 2025-11
New Economics Papers: this item is included in nep-ene, nep-fmk, nep-for and nep-rmg
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