No-arbitrage semi-martingale restrictions for continuous-time volatility models subject to leverage effects, jumps and i.i.d. noise: Theory and testable distributional implications

Torben G. Andersen*, Tim Bollerslev, Dobrislav Dobrev

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

140 Scopus citations

Abstract

We develop a sequential procedure to test the adequacy of jump-diffusion models for return distributions. We rely on intraday data and nonparametric volatility measures, along with a new jump detection technique and appropriate conditional moment tests, for assessing the import of jumps and leverage effects. A novel robust-to-jumps approach is utilized to alleviate microstructure frictions for realized volatility estimation. Size and power of the procedure are explored through Monte Carlo methods. Our empirical findings support the jump-diffusive representation for S&P500 futures returns but reveal it is critical to account for leverage effects and jumps to maintain the underlying semi-martingale assumption.

Original languageEnglish (US)
Pages (from-to)125-180
Number of pages56
JournalJournal of Econometrics
Volume138
Issue number1
DOIs
StatePublished - May 2007

Keywords

  • Financial time sampling
  • High-frequency data
  • Jump detection
  • Normality tests
  • Realized volatility

ASJC Scopus subject areas

  • Economics and Econometrics

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