Arbeitspapier
Seasonal long memory in intraday volatility and trading volume of Dow Jones stocks
It is well known that intraday volatilities and trading volumes exhibit strong seasonal features. These seasonalities are usually modeled using dummy variables or deterministic functions. Here, we propose a test for seasonal long memory with a known frequency. Using this test, we show that deterministic seasonality is an accurate model for the DJIA index but not for the component stocks. These still exhibit significant and persistent periodicity after seasonal de-meaning so that more evolved seasonal long memory models are required to model their behavior.
- Sprache
-
Englisch
- Erschienen in
-
Series: Hannover Economic Papers (HEP) ; No. 599
- Klassifikation
-
Wirtschaft
Hypothesis Testing: General
Single Equation Models; Single Variables: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
Financial Econometrics
Asset Pricing; Trading Volume; Bond Interest Rates
International Financial Markets
- Thema
-
Intraday Volatility
Trading Volume
Seasonality
Long Memory
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Voges, Michelle
Leschinski, Christian
Sibbertsen, Philipp
- Ereignis
-
Veröffentlichung
- (wer)
-
Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät
- (wo)
-
Hannover
- (wann)
-
2017
- Handle
- Letzte Aktualisierung
-
10.03.2025, 11:42 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
- Voges, Michelle
- Leschinski, Christian
- Sibbertsen, Philipp
- Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät
Entstanden
- 2017
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