Business Applications and State-Level Stock Market Realized Volatility: A Forecasting Experiment

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

No 202247, Working Papers from University of Pretoria, Department of Economics

Abstract: We analyze the predictive value of state-level business applications, as a proxy of local investor sentiment, for the state-level realized US stock-market volatility. We use highfrequency data for the period from September, 2011 to October, 2021 to compute realized volatility. We show, using an extended version of the popular heterogenous autoregressive realized volatility model, that business applications have predictive value at intermediate and long prediction horizons, after controlling for realized moments (realized skewness, realized kurtosis, realized tail risks), for realized state-level stock-market volatility, and for upside (``good") and downside (``bad") realized volatility.

Keywords: State-level stock markets; State-level investor sentiment; Business applications; Realized volatility; Forecasting (search for similar items in EconPapers)
JEL-codes: C22 C53 G10 G17 G41 (search for similar items in EconPapers)
Pages: 23 pages
Date: 2022-10
New Economics Papers: this item is included in nep-fmk and nep-rmg
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Journal Article: Business applications and state‐level stock market realized volatility: A forecasting experiment (2024)
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