Characterizing financial crises using high-frequency data

Mardi Dungey, Jet Holloway, Abdullah Yalaman, Wenying Yao

    Research output: Contribution to journalArticle


    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.
    Original languageEnglish
    Pages (from-to)743-760
    JournalQuantitative Finance
    Issue number4
    Publication statusPublished - 2022


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