Arbeitspapier
Empirical characteristic functions-based estimation and distance correlation for locally stationary processes
In this paper, we propose a kernel-type estimator for the local characteristic function of locally stationary processes. Under weak moment conditions, we prove joint asymptotic normality for local empirical characteristic functions. For time-varying linear processes, we establish a central limit theorem under the assumption of finite absolute first moments of the process. Additionally, we prove weak convergence of the local empirical characteristic process. We apply our asymptotic results to parameter estimation. Furthermore, by extending the notion of distance correlation of Szekely, Rizzo and Bakirov (2007) to locally stationary processes, we are able to provide asymptotic theory for local empirical distance correlations. Finally, we provide a simulation study on minimum distance estimation for a-stable distributions and illustrate the pairwise dependence structure over time of log returns of German stock prices via local empirical distance correlations.
- Language
-
Englisch
- Bibliographic citation
-
Series: Working Paper Series ; No. 16-15
- Classification
-
Wirtschaft
- Subject
-
empirical characteristic function
local stationarity
time series
stable distributions
(local) distance correlation
minimum distance estimation
process convergence
asymptotic theory
- Event
-
Geistige Schöpfung
- (who)
-
Jentsch, Carsten
Leucht, Anne
Meyer, Marco
Beering, Carina
- Event
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Veröffentlichung
- (who)
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University of Mannheim, Department of Economics
- (where)
-
Mannheim
- (when)
-
2016
- Handle
- URN
-
urn:nbn:de:bsz:180-madoc-414388
- Last update
-
10.03.2025, 11:45 AM CET
Data provider
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
- Jentsch, Carsten
- Leucht, Anne
- Meyer, Marco
- Beering, Carina
- University of Mannheim, Department of Economics
Time of origin
- 2016
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