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 kernel estimators of the aforementioned quantities. The kernel functions used in our analysis are based on different realized volatility measures, which are constructed using the ex post variation of asset prices. A set of sufficient conditions under which the estimators are asymptotically equivalent to their unfeasible counterparts, based on the unobservable volatility process, is provided. Asymptotic normality is also established. The efficacy of the estimators is examined via Monte Carlo experimentation, and an empirical illustration based upon data from the New York Stock Exchange is provided.
- Sprache
-
Englisch
- Erschienen in
-
Series: Working Paper ; No. 2011-08
- Klassifikation
-
Wirtschaft
Single Equation Models; Single Variables: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
Forecasting Models; Simulation Methods
Semiparametric and Nonparametric Methods: General
- Thema
-
diffusions
integrated volatility
realized volatility measures
kernels
microstructure noise
conditional confidence intervals
jumps
prediction
Börsenkurs
Volatilität
Zeitreihenanalyse
Inferenzstatistik
Nichtparametrisches Verfahren
Theorie
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Corradi, Valentina
Distaso, Walter
Swanson, Norman R.
- Ereignis
-
Veröffentlichung
- (wer)
-
Rutgers University, Department of Economics
- (wo)
-
New Brunswick, NJ
- (wann)
-
2011
- Handle
- Letzte Aktualisierung
-
10.03.2025, 11:45 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
- Corradi, Valentina
- Distaso, Walter
- Swanson, Norman R.
- Rutgers University, Department of Economics
Entstanden
- 2011
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