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  • Search: subject:"financial time series data"
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Year of publication
Subject
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Finanzmarkt 2 Theorie 2 Zeitreihenanalyse 2 cycles 2 financial time series data 2 trends 2 ARCH model 1 ARCH-Modell 1 Aktienindex 1 Börsenkurs 1 Estimation 1 Financial market 1 Fractional integration 1 GARCH 1 High-frequency financial time series data 1 Prognoseverfahren 1 Rendite 1 Schätzung 1 Share price 1 Stock index 1 Theory 1 Time series analysis 1 Trend 1 USA 1 Volatility 1 Volatilität 1 autocorrelation 1 fractional integration 1 stationarity 1 stylized facts 1
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Online availability
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Free 2 Undetermined 1
Type of publication
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Book / Working Paper 2 Article 1
Type of publication (narrower categories)
All
Article in journal 1 Aufsatz in Zeitschrift 1 Working Paper 1
Language
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English 3
Author
All
Caporale, Guglielmo Maria 2 Cunado, Juncal 2 Gil-Alana, Luis A. 2 Shakeel, Moonis 1 Srivastava, Bhavana 1
Institution
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CESifo 1
Published in...
All
CESifo Working Paper 1 CESifo Working Paper Series 1 Global business review 1
Source
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ECONIS (ZBW) 1 EconStor 1 RePEc 1
Showing 1 - 3 of 3
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Stylized facts of high-frequency financial time series data
Shakeel, Moonis; Srivastava, Bhavana - In: Global business review 22 (2021) 2, pp. 550-564
Persistent link: https://www.econbiz.de/10012520248
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Modelling long-run trends and cycles in financial time series data
Caporale, Guglielmo Maria; Cunado, Juncal; Gil-Alana, … - 2008
This paper proposes a very general time series framework to capture the long-run behaviour of financial series. The suggested model includes linear and non-linear time trends, and stationary and nonstationary processes based on integer and/or fractional degrees of differentiation. Moreover, the...
Persistent link: https://www.econbiz.de/10010264382
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Cover Image
Modelling Long-Run Trends and Cycles in Financial Time Series Data
Caporale, Guglielmo Maria; Cunado, Juncal; Gil-Alana, … - CESifo - 2008
This paper proposes a very general time series framework to capture the long-run behaviour of financial series. The suggested model includes linear and non-linear time trends, and stationary and nonstationary processes based on integer and/or fractional degrees of differentiation. Moreover, the...
Persistent link: https://www.econbiz.de/10005181402
Saved in:
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