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Financial risk modelling and portfolio optimization with R /
Introduces the latest techniques advocated for measuring financial market risk and portfolio optimisation, 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 Optimisation with R: Demonstrates...
| Clasificación: | Libro Electrónico |
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| Autor principal: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Chichester, West Sussex, UK :
John Wiley & Sons,
2013.
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| Colección: | Statistics in practice.
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| Temas: | |
| Acceso en línea: | Texto completo (Requiere registro previo con correo institucional) |
| Sumario: | Introduces the latest techniques advocated for measuring financial market risk and portfolio optimisation, 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 Optimisation with R: Demonstrates techniques in modelling financial risks and applying portfolio optimisation techniques as well as recent advances in the field. Introduces stylised facts, loss function and risk measures, conditional and unconditional modelling of risk; extreme value theory, generalised hyperbolic distribution, volatility modelling and concepts for capturing dependencies. Explores portfolio risk concepts and optimisation 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 optimisation will find this book beneficial. It also serves well as an accompanying text in computer-lab classes and is therefore suitable for self-study. |
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| Descripción Física: | 1 online resource |
| Bibliografía: | Includes bibliographical references and index. |
| ISBN: | 9781118477144 1118477146 9781118477137 1118477138 9781118477120 111847712X |