Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/237807
Year of Publication: 
2020
Publisher: 
MDPI, Basel
Abstract: 
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.
Subjects: 
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
Persistent Identifier of the first edition: 
ISBN: 
978-3-03943-574-6
Creative Commons License: 
cc-by-nc-nd Logo
Document Type: 
Book
Document Version: 
Published Version
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