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
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Objekttyp
- Arbeitspapier
Beteiligte
- Bibinger, Markus
- Jirak, Moritz
- Vetter, Mathias
- Humboldt University of Berlin, Collaborative Research Center 649 - Economic Risk
Entstanden
- 2015
 
        
    