Characterizing financial crises using high-frequency data. Issue 4 (3rd April 2022)

• Record Type: Journal Article
• Authors: Dungey, Mardi; Holloway, Jet; Yalaman, Abdullah; Yao, Wenying
• Is Part Of: Quantitative finance. Volume 22:Issue 4(2022)
• Page Start: 743
• Page End: 760
• Publication Date: 2022-04-03
• Subjects: High-frequency data -- Tail behavior -- Financial crisis -- US Treasury markets; C58 -- G01 -- G12; Finance -- Periodicals; Business mathematics -- Periodicals; Finance -- Mathematical models -- Periodicals; Investments -- Mathematics -- Periodicals; Economics -- Periodicals; Finances -- Modèles mathématiques -- Périodiques; 332.015118
• DOI: 10.1080/14697688.2022.2027504
• Languages: English
• ISSNs: 1469-7688

Abstract

Abstract : Recent advances in high-frequency financial econometrics enable us to characterize which components of the data generating processes change in crisis, and which do not. This paper introduces a new statistic which captures large discontinuities in the composition of a given price series. Monte Carlo simulations suggest that this statistic is useful in characterizing the tail behavior across different sample periods. An application to US Treasury market provides evidence consistent with identifying periods of stress via flight-to-cash behavior which results in increased abrupt price falls at the short end of the term structure and decreased negative price jumps at the long end.