A Note on Combining Machine Learning with Statistical Modeling for Financial Data Analysis

Autor:	José María Sarabia, Faustino Prieto, Vanesa Jordá, Stefan Sperlich
Jazyk:	angličtina
Rok vydání:	2020
Předmět:	semiparametric modeling machine learning VaR estimation analyzing financial data Insurance HG8011-9999
Zdroj:	Risks, Vol 8, Iss 2, p 32 (2020)
Druh dokumentu:	article
ISSN:	2227-9091
DOI:	10.3390/risks8020032
Popis:	This note revisits the ideas of the so-called semiparametric methods that we consider to be very useful when applying machine learning in insurance. To this aim, we first recall the main essence of semiparametrics like the mixing of global and local estimation and the combining of explicit modeling with purely data adaptive inference. Then, we discuss stepwise approaches with different ways of integrating machine learning. Furthermore, for the modeling of prior knowledge, we introduce classes of distribution families for financial data. The proposed procedures are illustrated with data on stock returns for five companies of the Spanish value-weighted index IBEX35.
Databáze:	Directory of Open Access Journals
Externí odkaz:	https://doaj.org/article/68ddd929db6945088426e8fd3c4cf127 Zobrazit plný text záznamu View record in DOAJ Plný text ve formátu PDF Plný text ve formátu HTML
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