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Financial Risk Modelling and Portfolio Optimization with R
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Accompanied by a supporting website featuring examples and case studies in R, Financial Risk Modelling and Portfolio Optimization with R examines portfolio optimization from the perspective of computational finance and financial engineering. This comprehensive, computationally oriented treatment of modern portfolio optimization and construction methods provides readers with an advanced set of powerful tools to solve the problems in the field. Coverage includes: facts, loss function and risk measures, conditional and unconditional modelling of risk, extreme value theory, generalized hyperbolic distribution and volatility modeling, portfolio optimization, copulae, portfolio risk concepts, optimization with risk constraints, ALM, LDI, Core-Satellite, and minimum CVAR portfolio.
Introduces the latest techniques advocated for measuring financial market risk and portfolio optimization, and provides a plethora of R code examples that enable the reader to replicate the results featured throughout the book.
Financial Risk Modelling and Portfolio Optimization with R:
Demonstrates techniques in modelling financial risks and applying portfolio optimization techniques as well as recent advances in the field.
Introduces stylized facts, loss function and risk measures, conditional and unconditional modelling of risk; extreme value theory, generalized hyperbolic distribution, volatility modelling and concepts for capturing dependencies.
Explores portfolio risk concepts and optimization with risk constraints.
Enables the reader to replicate the results in the book using R code.
Is accompanied by a supporting website featuring examples and case studies in R.
Graduate and postgraduate students in finance, economics, risk management as well as practitioners in finance and portfolio optimization will find this book beneficial. It also serves well as an accompanying text in computer-lab classes and is therefore suitable for self-study.
Financial Risk Modelling and Portfolio Optimization with R:
Demonstrates techniques in modelling financial risks and applying portfolio optimization techniques as well as recent advances in the field.
Introduces stylized facts, loss function and risk measures, conditional and unconditional modelling of risk; extreme value theory, generalized hyperbolic distribution, volatility modelling and concepts for capturing dependencies.
Explores portfolio risk concepts and optimization with risk constraints.
Enables the reader to replicate the results in the book using R code.
Is accompanied by a supporting website featuring examples and case studies in R.
Graduate and postgraduate students in finance, economics, risk management as well as practitioners in finance and portfolio optimization will find this book beneficial. It also serves well as an accompanying text in computer-lab classes and is therefore suitable for self-study.