Department of Economics and Business Economics

How precise is the finite sample approximation of the asymptotic distribution of realised variation measures in the presence of jumps?

Research output: Contribution to journal/Conference contribution in journal/Contribution to newspaperJournal articleResearchpeer-review

  • School of Economics and Management
This paper studies the impact of jumps on volatility estimation and inference based on various realised variation measures such as realised variance, realised multipower variation and truncated realised multipower variation.
We review the asymptotic theory of those realised variation measures and present a new estimator for the asymptotic "variance" of the centered realised variance in the presence of jumps.
Next, we compare the finite sample performance of the various estimators by means of detailed Monte Carlo studies. Here we study the impact of the jump activity, of the jump size of the jumps in the price and of the presence of additional independent or dependent jumps in the volatility.
We find that the finite sample performance of realised variance and, in particular, of log--transformed realised variance is generally good, whereas the jump--robust statistics tend to struggle in the presence of a highly active jump process.

Finally, we investigate the impact of jumps on inference on volatility
empirically, where we study
high frequency data from the Standard & Poor’s Depository Receipt (SPY).
Original languageEnglish
JournalA St A - Advances in Statistical Analysis
Volume95
Issue3
Pages (from-to)253-291
ISSN1863-8171
DOIs
Publication statusPublished - 2011

    Research areas

  • Realised variance, inference, stochastic volatility, jumps

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