Arbeitspapier
Nonparametric change-point analysis of volatility
This work develops change-point methods for statistics of high-frequency data. The main interest is the volatility of an Itô semi-martingale, which is discretely observed over a fixed time horizon. We construct a minimax-optimal test to discriminate different smoothness classes of the underlying stochastic volatility process. In a high-frequency framework we prove weak convergence of the test statistic under the hypothesis to an extreme value distribution. As a key example, under extremely mild smoothness assumptions on the stochastic volatility we thereby derive a consistent test for volatility jumps. A simulation study demonstrates the practical value in finite-sample applications.
- Sprache
-
Englisch
- Erschienen in
-
Series: SFB 649 Discussion Paper ; No. 2015-008
- Klassifikation
-
Wirtschaft
Hypothesis Testing: General
Semiparametric and Nonparametric Methods: General
- Thema
-
high-frequency data
nonparametric change-point test
minimax-optimal test
stochastic volatility
volatility jumps
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Bibinger, Markus
Jirak, Moritz
Vetter, Mathias
- Ereignis
-
Veröffentlichung
- (wer)
-
Humboldt University of Berlin, Collaborative Research Center 649 - Economic Risk
- (wo)
-
Berlin
- (wann)
-
2015
- Handle
- Letzte Aktualisierung
-
10.03.2025, 11:44 MEZ
Datenpartner
Dieses Objekt wird bereitgestellt von:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Objekttyp
- Arbeitspapier
Beteiligte
- Bibinger, Markus
- Jirak, Moritz
- Vetter, Mathias
- Humboldt University of Berlin, Collaborative Research Center 649 - Economic Risk
Entstanden
- 2015
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