Financial time series: methods and models

Massimiliano Caporin and Giuseppe Storti

The statistical analysis of financial time series is a rich and diversified research field whose inherent complexity requires an interdisciplinary approach, gathering together several disciplines, such as statistics, economics, and computational sciences. This special issue of the Journal of Risk and Financial Management on "Financial Time Series: Methods & Models" contributes to the evolution of research on the analysis of financial time series by presenting a diversified collection of scientific contributions exploring different lines of research within this field.

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Year of publication:	2020
Authors:	Caporin, Massimiliano ; Storti, Giuseppe
Published in:	Journal of risk and financial management : JRFM. - Basel : MDPI, ISSN 1911-8074, ZDB-ID 2739117-6. - Vol. 13.2020, 5/86, p. 1-3
Subject:	financial time series \| GARCH models \| capital markets \| emerging markets \| realized volatility \| dynamic conditional correlation models \| cointegration \| model-based clustering \| structural breaks \| market efficiency \| misery index \| ARCH-Modell \| ARCH model \| Volatilität \| Volatility \| Zeitreihenanalyse \| Time series analysis \| Finanzmarkt \| Financial market \| Kapitaleinkommen \| Capital income \| Schätzung \| Estimation \| Strukturbruch \| Structural break \| Kointegration \| Cointegration \| Schwellenländer \| Emerging economies \| Aktienmarkt \| Stock market \| Effizienzmarkthypothese \| Efficient market hypothesis

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Type of publication:	Article
Type of publication (narrower categories):	Aufsatz in Zeitschrift ; Article in journal
Language:	English
Other identifiers:	10.3390/jrfm13050086 [DOI] hdl:10419/239175 [Handle]
Source:	ECONIS - Online Catalogue of the ZBW

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