Jump tails, extreme dependencies, and the distribution of stock returns

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  • Tim Bollerslev
  • V. Todorov, Northwestern University
  • ,
  • S.Z. Li, Duke University
We provide a new framework for estimating the systematic and idiosyncratic jump tail risks in financial asset prices. Our estimates are based on in-fill asymptotics for directly identifying the jumps, together with Extreme Value Theory (EVT) approximations and methods-of-moments for assessing the tail decay parameters and tail dependencies. On implementing the procedures with a panel of intraday prices for a large cross-section of individual stocks and the S&P 500 market portfolio, we find that the distributions of the systematic and idiosyncratic jumps are both generally heavy-tailed and close to symmetric, and show how the jump tail dependencies deduced from the high-frequency data together with the day-to-day variation in the diffusive volatility account for the "extreme" joint dependencies observed at the daily level.
OriginalsprogEngelsk
TidsskriftJournal of Econometrics
Vol/bind172
Nummer2
Sider (fra-til)307-324
Antal sider18
ISSN0304-4076
DOI
StatusUdgivet - 1 feb. 2013

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