Credit Standards: A New Predictor of U.S. Stock Market Realized Volatility

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
Oguzhan Cepni: Ostim Technical University, Ankara, Turkiye; University of Edinburgh Business School, Centre for Business, Climate Change, and Sustainability; Department of Economics, Copenhagen Business School, Denmark
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 202607, Working Papers from University of Pretoria, Department of Economics

Abstract: We introduce credit standards from the Federal Reserve's Senior Loan Officer Opinion Survey (SLOOS) as a novel predictor of U.S. stock market realized volatility over 1990:04-2024:12. We show that tighter credit standards significantly predict higher realized volatility both in- and out-of-sample at one-, three-, and six-month-ahead horizons. A parsimonious model with only the credit standards factor outperforms more complex specifications incorporating macroeconomic factors, uncertainty indexes, and realized moments, estimated via elastic-net and random forest methods, with forecasting gains increasing at longer horizons. These findings establish credit standards as a powerful and distinct predictor of stock market volatility with practical implications for portfolio allocation and risk management.

Keywords: Credit conditions; Realized stock market volatility; Forecasting (search for similar items in EconPapers)
JEL-codes: C22 C53 E23 G10 G17 (search for similar items in EconPapers)
Pages: 16 pages
Date: 2026-03
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