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An econometric analysis of volatility discovery

Fruet Dias, Gustavo, Papailias, Fotis and Scherrer, Cristina ORCID: 0000-0002-7935-5378 (2023) An econometric analysis of volatility discovery. Journal of Business and Economic Statistics. ISSN 0735-0015

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Identification Number: 10.1080/07350015.2023.2292178

Abstract

We investigate information processing in the stochastic process driving stock’s volatility (volatility discovery). We apply fractionally cointegration techniques to decompose the estimates of the market-specific integrated variances into an estimate of the common integrated variance of the efficient price and a transitory component. The market weights on the common integrated variance of the efficient price are the volatility discovery measures. We relate the volatility discovery measure to the price discovery framework and formally show their roles on the identification of the integrated variance of the efficient price. We establish the limiting distribution of the volatility discovery measures by resorting to both long span and in-fill asymptotics. The empirical application is in line with our theoretical results, as it reveals that trading venues incorporate new information into the stochastic volatility process in an individual manner and that the volatility discovery analysis identifies a distinct information process than that based on the price discovery analysis.

Item Type: Article
Additional Information: © 2024 The Author(s).
Divisions: Finance
Subjects: H Social Sciences > HA Statistics
H Social Sciences
H Social Sciences > HB Economic Theory
JEL classification: C - Mathematical and Quantitative Methods > C3 - Econometric Methods: Multiple; Simultaneous Equation Models; Multiple Variables; Endogenous Regressors > C30 - General
Date Deposited: 12 Jan 2024 17:48
Last Modified: 03 Oct 2024 22:03
URI: http://eprints.lse.ac.uk/id/eprint/121363

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