Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/239175 
Year of Publication: 
2020
Citation: 
[Journal:] Journal of Risk and Financial Management [ISSN:] 1911-8074 [Volume:] 13 [Issue:] 5 [Publisher:] MDPI [Place:] Basel [Year:] 2020 [Pages:] 1-3
Publisher: 
MDPI, Basel
Abstract: 
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.
Subjects: 
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
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Article

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