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.

Sprache
Englisch

Erschienen in
Series: Working Paper Series ; No. 16-15

Klassifikation
Wirtschaft
Thema
empirical characteristic function
local stationarity
time series
stable distributions
(local) distance correlation
minimum distance estimation
process convergence
asymptotic theory

Ereignis
Geistige Schöpfung
(wer)
Jentsch, Carsten
Leucht, Anne
Meyer, Marco
Beering, Carina
Ereignis
Veröffentlichung
(wer)
University of Mannheim, Department of Economics
(wo)
Mannheim
(wann)
2016

Handle
URN
urn:nbn:de:bsz:180-madoc-414388
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.

Objekttyp

  • Arbeitspapier

Beteiligte

  • Jentsch, Carsten
  • Leucht, Anne
  • Meyer, Marco
  • Beering, Carina
  • University of Mannheim, Department of Economics

Entstanden

  • 2016

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