Statistics and data analysis for financial engineering : with R examples
Material type:
TextPublication details: New York Springer 2015 Edition: 2ndDescription: xxvi, 719 pISBN: 9781493951734Subject(s): Finance--Statistical methods | Statistics | Economics | Mathematical statisticsDDC classification: 658.15 Summary: About this book
The new edition of this influential textbook, geared towards graduate or advanced undergraduate students, teaches the statistics necessary for financial engineering. In doing so, it illustrates concepts using financial markets and economic data, R Labs with real-data exercises, and graphical and analytic methods for modeling and diagnosing modeling errors. Financial engineers now have access to enormous quantities of data. To make use of these data, the powerful methods in this book, particularly about volatility and risks, are essential. Strengths of this fully-revised edition include major additions to the R code and the advanced topics covered. Individual chapters cover, among other topics, multivariate distributions, copulas, Bayesian computations, risk management, multivariate volatility and cointegration. Suggested prerequisites are basic knowledge of statistics and probability, matrices and linear algebra, and calculus. There is an appendix on probability, statistics and linear algebra. Practicing financial engineers will also find this book of interest.
| Item type | Current library | Collection | Call number | Copy number | Status | Date due | Barcode |
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Indian Institute of Management LRC General Stacks | Finance & Accounting | 658.15 RUP (Browse shelf(Opens below)) | 1 | Available | 003547 |
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| 658.15 ROS Corporate finance | 658.15 ROS Corporate finance | 658.15 ROS Corporate finance | 658.15 RUP Statistics and data analysis for financial engineering : | 658.15 SAG Dynamical corporate finance: an equilibrium approach | 658.15 SIN Corporate accounting: theory and practice | 658.15 SUM Where's the Moolah?: |
About this book
The new edition of this influential textbook, geared towards graduate or advanced undergraduate students, teaches the statistics necessary for financial engineering. In doing so, it illustrates concepts using financial markets and economic data, R Labs with real-data exercises, and graphical and analytic methods for modeling and diagnosing modeling errors. Financial engineers now have access to enormous quantities of data. To make use of these data, the powerful methods in this book, particularly about volatility and risks, are essential. Strengths of this fully-revised edition include major additions to the R code and the advanced topics covered. Individual chapters cover, among other topics, multivariate distributions, copulas, Bayesian computations, risk management, multivariate volatility and cointegration. Suggested prerequisites are basic knowledge of statistics and probability, matrices and linear algebra, and calculus. There is an appendix on probability, statistics and linear algebra. Practicing financial engineers will also find this book of interest.
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