Mathematical finance with applications

Mathematical finance plays a vital role in many fields within finance and provides the theories and tools that have been widely used in all areas of finance. Knowledge of mathematics, probability, and statistics is essential to develop finance theories and test their validity through the analysis of empirical, real-world data. For example, mathematics, probability, and statistics could help to develop pricing models for financial assets such as equities, bonds, currencies, and derivative securities.

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Year of publication:	2020
Other Persons:	Wong, Wing Keung (contributor) ; Guo, Xu (contributor) ; Ortobelli Lozza, Sergio (contributor)
Publisher:	Basel : MDPI
Subject:	cluster analysis \| equity index networks \| machine learning \| copulas \| dependence structures \| quotient of random variables \| density functions \| distribution functions \| multi-factor model \| risk factors \| OLS and ridge regression model \| python \| chi-square test \| quantile \| VaR \| quadrangle \| CVaR \| conditional value-at-risk

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Type of publication:	Book / Working Paper
Language:	English
ISBN:	978-3-03943-574-6
Other identifiers:	10.3390/books978-3-03943-574-6 [DOI] 1762896737 [GVK] hdl:10419/237807 [Handle]
Source:	EconStor

Persistent link: https://www.econbiz.de/10012606040