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

Published

Journal Article

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. © 2012 Elsevier B.V. All rights reserved.

Full Text

Duke Authors

Cited Authors

  • Bollerslev, T; Todorov, V; Li, SZ

Published Date

  • January 1, 2013

Published In

Volume / Issue

  • 172 / 2

Start / End Page

  • 307 - 324

International Standard Serial Number (ISSN)

  • 0304-4076

Digital Object Identifier (DOI)

  • 10.1016/j.jeconom.2012.08.014

Citation Source

  • Scopus