Systemic Tail Risk: High-Frequency Measurement, Evidence and Implications

Deniz Erdemlioglu, Christopher Neely and Xiye Yang

No 2023-016, Working Papers from Federal Reserve Bank of St. Louis

Abstract: We develop a new framework to measure market-wide (systemic) tail risk in the cross-section of high-frequency stock returns. We estimate the time-varying jump intensities of asset prices and introduce a testing approach that identifies multi-asset tail risk based on the release times of scheduled news announcements. Using high-frequency data on individual U.S. stocks and sector-specific ETF portfolios, we find that most of the FOMC announcements create systemic left tail risk, but there is no evidence that macro announcements do so. The magnitude of the tail risk induced by Fed news varies over the business cycle, peaks during the global financial crisis and remains high over different phases of unconventional monetary policy. We use our approach to construct a Fed-induced systemic tail risk (STR) indicator. STR helps explain the pre-FOMC announcement drift and significantly increases variance risk premia, particularly for the meetings without press conferences.

Keywords: time-varying tail risk; high-frequency data; Federal Open Market Committee (FOMC) news; monetary policy announcements; cojumps; systemic risk; jump intensity (search for similar items in EconPapers)
JEL-codes: C12 C14 C22 C32 C58 G12 G14 (search for similar items in EconPapers)
Pages: 47 pages
Date: 2023-07-20
New Economics Papers: this item is included in nep-ban, nep-cba, nep-ecm, nep-fmk, nep-mst and nep-rmg
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DOI: 10.20955/wp.2023.016

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