Arbeitspapier
TVICA - time varying independent component analysis and its application to financial data
Source extraction and dimensionality reduction are important in analyzing high dimensional and complex financial time series that are neither Gaussian distributed nor stationary. Independent component analysis (ICA) method can be used to factorize the data into a linear combination of independent components, so that the high dimensional problem is converted to a set of univariate ones. However conventional ICA methods implicitly assume stationarity or stochastic homogeneity of the analyzed time series, which leads to a low accuracy of estimation in case of a changing stochastic structure. A time varying ICA (TVICA) is proposed here. The key idea is to allow the ICA filter to change over time, and to estimate it in so-called local homogeneous intervals. The question of how to identify these intervals is solved by the LCP (local change point) method. Compared to a static ICA, the dynamic TVICA provides good performance both in simulation and real data analysis. The data example is concerned with independent signal processing and deals with a portfolio of highly traded stocks.
- Sprache
-
Englisch
- Erschienen in
-
Series: SFB 649 Discussion Paper ; No. 2011-054
- Klassifikation
-
Wirtschaft
Semiparametric and Nonparametric Methods: General
Financial Econometrics
Financial Forecasting and Simulation
- Thema
-
adaptive sequential testing
independent component analysis
local homogeneity
signal processing
realized volatility
Finanzmarkt
Zeitreihenanalyse
Theorie
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Chen, Ray-Bing
Chen, Ying
Härdle, Wolfgang Karl
- Ereignis
-
Veröffentlichung
- (wer)
-
Humboldt University of Berlin, Collaborative Research Center 649 - Economic Risk
- (wo)
-
Berlin
- (wann)
-
2011
- Handle
- Letzte Aktualisierung
-
10.03.2025, 11:42 MEZ
Datenpartner
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Objekttyp
- Arbeitspapier
Beteiligte
- Chen, Ray-Bing
- Chen, Ying
- Härdle, Wolfgang Karl
- Humboldt University of Berlin, Collaborative Research Center 649 - Economic Risk
Entstanden
- 2011
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