An econometric analysis of volatility discovery

Fruet Dias, Gustavo ORCID: https://orcid.org/0000-0001-6428-5074, Papailias, Fotis and Scherrer, Cristina (2023) An econometric analysis of volatility discovery. Journal of Business & Economic Statistics. ISSN 0735-0015

[thumbnail of Fruet-Dias_etal_2023_JBES_AAM]
Preview
PDF (Fruet-Dias_etal_2023_JBES_AAM) - Accepted Version
Available under License Creative Commons Attribution.

Download (1MB) | Preview

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
Uncontrolled Keywords: long memory,fractionally cointegrated vector autoregressive model,realized measures,market microstructure,price discovery,high-frequency data,double asymptotics,high-frequency data,long memory,price discovery,market microstructure,fractionally cointegrated vector autoregressive model,realized measures,double asymptotics,economics and econometrics,statistics and probability,social sciences (miscellaneous),statistics, probability and uncertainty,4*,jbes is a 4 star journal in econometrics ,/dk/atira/pure/subjectarea/asjc/2000/2002
Faculty \ School: Faculty of Social Sciences > School of Economics
UEA Research Groups: Faculty of Social Sciences > Research Groups > Applied Econometrics And Finance
Related URLs:
Depositing User: LivePure Connector
Date Deposited: 20 Dec 2023 02:57
Last Modified: 17 Jan 2024 01:36
URI: https://ueaeprints.uea.ac.uk/id/eprint/94007
DOI: 10.1080/07350015.2023.2292178

Actions (login required)

View Item View Item