Volatility during the Global Financial Crisis and COVID-19 pandemic through the lens of high-frequency data: a Realized GARCH approach

Denisa Banulescu-Radu (), Peter Reinhard Hansen (), Zhuo Huang and Marius Matei
Additional contact information
Denisa Banulescu-Radu: LEO - Laboratoire d'Économie d'Orleans [2022-...] - UO - Université d'Orléans - UT - Université de Tours - UCA - Université Clermont Auvergne
Peter Reinhard Hansen: CBS - Copenhagen Business School [Copenhagen], CREATES - Center for Research in Econometric Analysis of Time Series, UNC - University of North Carolina System
Zhuo Huang: Peking University [Beijing]
Marius Matei: A.S.E. - The Bucharest University of Economic Studies / Academia de Studii Economice din Bucureşti

Working Papers from HAL

Abstract: This article has two primary objectives: 1) to propose a new parametric model of volatility and 2) to identify the days with the most significant volatility shocks, while exploring the events that triggered these shocks. We analyze financial volatility during the global financial crisis and the COVID-19 pandemic, utilizing high-frequency financial data and an improved model, which incorporates asymmetry and handles outliers, to estimate volatility and determine the timing of the largest shocks within the day. For instance, for the global financial crisis, major volatility shocks coincide with events such as the bankruptcy of Lehman Brothers and the failure of the Emergency Economic Stabilization Act. However, the largest shock occurred on February 27, 2007, which, despite coinciding with market events like a Chinese stock market crash and Freddie Mac's tighter subprime loan policy, was primarily caused by a computer glitch. Our analysis underscores the value of high-frequency data in modeling financial volatility and identifying the key events driving volatility shocks.

Keywords: Financial crisis; COVID-19 pandemic; Volatility; High-frequency data; Realized GARCH (search for similar items in EconPapers)
Date: 2025-10-12
Note: View the original document on HAL open archive server: https://hal.science/hal-05310604v1
References: Add references at CitEc
Citations:

Downloads: (external link)
https://hal.science/hal-05310604v1/document (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:hal:wpaper:hal-05310604

Access Statistics for this paper

More papers in Working Papers from HAL
Bibliographic data for series maintained by CCSD ().