Arbeitspapier
A test for serial dependence using neural networks
Testing serial dependence is central to much of time series econometrics. A number of tests that have been developed and used to explore the dependence properties of various processes. This paper builds on recent work on nonparametric tests of independence. We consider a fact that characterises serially dependent processes using a generalisation of the autocorrelation function. Using this fact we build dependence tests that make use of neural network based approximations. We derive the theoretical properties of our tests and show that they have superior power properties. Our Monte Carlo evaluation supports the theoretical findings. An application to a large dataset of stock returns illustrates the usefulness of the proposed tests.
- Sprache
-
Englisch
- Erschienen in
-
Series: Working Paper ; No. 609
Klassifikation
Wirtschaft
Multiple or Simultaneous Equation Models: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
Multiple or Simultaneous Equation Models: Panel Data Models; Spatio-temporal Models
Asset Pricing; Trading Volume; Bond Interest Rates
Multiple or Simultaneous Equation Models: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
Multiple or Simultaneous Equation Models: Panel Data Models; Spatio-temporal Models
Asset Pricing; Trading Volume; Bond Interest Rates
Thema
Independence
Neural networks
Strict stationarity
Bootstrap, S&P500
Zeitreihenanalyse
Autokorrelation
Neuronale Netze
Kapitalertrag
Theorie
Neural networks
Strict stationarity
Bootstrap, S&P500
Zeitreihenanalyse
Autokorrelation
Neuronale Netze
Kapitalertrag
Theorie
Ereignis
Geistige Schöpfung
(wer)
Kapetanios, George
Ereignis
Veröffentlichung
(wer)
Queen Mary University of London, Department of Economics
(wo)
London
(wann)
2007
- Handle
- Letzte Aktualisierung
-
20.09.2024, 08:23 MESZ
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
- Kapetanios, George
- Queen Mary University of London, Department of Economics
Entstanden
- 2007
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