Arbeitspapier
Predictive inference for integrated volatility
In recent years, numerous volatility-based derivative products have been engineered. This has led to interest in constructing conditional predictive densities and confidence intervals for integrated volatility. In this paper, we propose nonparametric estimators of the aforementioned quantities, based on model free volatility estimators. We establish consistency and asymptotic normality for the feasible estimators and study their finite sample properties through a Monte Carlo experiment. Finally, using data from the New York Stock Exchange, we provide an empirical application to volatility directional predictability.
- Language
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Englisch
- Bibliographic citation
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Series: Working Paper ; No. 2011-09
- Classification
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Wirtschaft
- Subject
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diffusions
realized volatility measures
kernels
microstructure noise
jumps
prediction
Börsenkurs
Volatilität
Zeitreihenanalyse
Inferenzstatistik
Nichtparametrisches Verfahren
Theorie
- Event
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Geistige Schöpfung
- (who)
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Corradi, Valentina
Distaso, Walter
Swanson, Norman R.
- Event
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Veröffentlichung
- (who)
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Rutgers University, Department of Economics
- (where)
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New Brunswick, NJ
- (when)
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2011
- Handle
- Last update
-
10.03.2025, 11:43 AM CET
Data provider
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ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. If you have any questions about the object, please contact the data provider.
Object type
- Arbeitspapier
Associated
- Corradi, Valentina
- Distaso, Walter
- Swanson, Norman R.
- Rutgers University, Department of Economics
Time of origin
- 2011
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