Nonparametric change-point analysis of volatility

Arbeitspapier

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.

Object Details

• Language: Englisch

References and Relationships

• Bibliographic citation: Series: SFB 649 Discussion Paper ; No. 2015-008

Classification and Topics

• Classification: Wirtschaft ; Hypothesis Testing: General ; Semiparametric and Nonparametric Methods: General
• Subject: high-frequency data ; nonparametric change-point test ; minimax-optimal test ; stochastic volatility ; volatility jumps

Contributors, Places and Time

• Event: Geistige Schöpfung
• (who): Bibinger, Markus ; Jirak, Moritz ; Vetter, Mathias
• Event: Veröffentlichung
• (who): Humboldt University of Berlin, Collaborative Research Center 649 - Economic Risk
• (where): Berlin
• (when): 2015

Further information

• Handle: http://hdl.handle.net/10419/107926
• Last update: 10.03.2025, 11:44 AM CET