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Mathematical Finance with Applications

dc.contributor.editorWong, Wing-Keung
dc.contributor.editorGuo, Xu
dc.contributor.editorLozza, Sergio Ortobelli
dc.date.accessioned2021-05-01T15:48:26Z
dc.date.available2021-05-01T15:48:26Z
dc.date.issued2020
dc.identifierONIX_20210501_9783039435739_1132
dc.identifier.urihttps://directory.doabooks.org/handle/20.500.12854/69386
dc.description.abstractMathematical 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.
dc.languageEnglish
dc.subject.classificationbic Book Industry Communication::W Lifestyle, sport & leisure::WC Antiques & collectables::WCF Coins, banknotes, medals, seals (numismatics)
dc.subject.othercluster analysis
dc.subject.otherequity index networks
dc.subject.othermachine learning
dc.subject.othercopulas
dc.subject.otherdependence structures
dc.subject.otherquotient of random variables
dc.subject.otherdensity functions
dc.subject.otherdistribution functions
dc.subject.othermulti-factor model
dc.subject.otherrisk factors
dc.subject.otherOLS and ridge regression model
dc.subject.otherpython
dc.subject.otherchi-square test
dc.subject.otherquantile
dc.subject.otherVaR
dc.subject.otherquadrangle
dc.subject.otherCVaR
dc.subject.otherconditional value-at-risk
dc.subject.otherexpected shortfall
dc.subject.otherES
dc.subject.othersuperquantile
dc.subject.otherdeviation
dc.subject.otherrisk
dc.subject.othererror
dc.subject.otherregret
dc.subject.otherminimization
dc.subject.otherCVaR estimation
dc.subject.otherregression
dc.subject.otherlinear regression
dc.subject.otherlinear programming
dc.subject.otherportfolio safeguard
dc.subject.otherPSG
dc.subject.otherequity option pricing
dc.subject.otherfactor models
dc.subject.otherstochastic volatility
dc.subject.otherjumps
dc.subject.othermathematics
dc.subject.otherprobability
dc.subject.otherstatistics
dc.subject.otherfinance
dc.subject.otherapplications
dc.subject.otherinvestment home bias (IHB)
dc.subject.otherbivariate first-degree stochastic dominance (BFSD)
dc.subject.otherkeeping up with the Joneses (KUJ)
dc.subject.othercorrelation loving (CL)
dc.subject.otherreturn spillover
dc.subject.othervolatility spillover
dc.subject.otheroptimal weights
dc.subject.otherhedge ratios
dc.subject.otherUS financial crisis
dc.subject.otherChinese stock market crash
dc.subject.otherstock price prediction
dc.subject.otherauto-regressive integrated moving average
dc.subject.otherartificial neural network
dc.subject.otherstochastic process-geometric Brownian motion
dc.subject.otherfinancial models
dc.subject.otherfirm performance
dc.subject.othercausality tests
dc.subject.otherleverage
dc.subject.otherlong-term debt
dc.subject.othercapital structure
dc.subject.othershock spillover
dc.titleMathematical Finance with Applications
dc.typebook
oapen.identifier.doi10.3390/books978-3-03943-574-6
oapen.relation.isPublishedBy46cabcaa-dd94-4bfe-87b4-55023c1b36d0
oapen.relation.isbn9783039435739
oapen.relation.isbn9783039435746
oapen.pages232
oapen.place.publicationBasel, Switzerland


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