Statistics and Data Analysis for Financial Engineering
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 ana...
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2015
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oai:scholar.dlu.edu.vn:DLU123456789-574552023-11-11T05:45:35Z Statistics and Data Analysis for Financial Engineering Ruppert, David Matteson, David S Financial engineering Statistical methods 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. These methods are critical because financial engineers now have access to enormous quantities of data. To make use of this data, the powerful methods in this book for working with quantitative information, 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, 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. 2015-08-14T03:12:47Z 2015-08-14T03:12:47Z 2015 Book 978-1-4939-2614-5 https://scholar.dlu.edu.vn/thuvienso/handle/DLU123456789/57455 en application/pdf Springer |
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Thư viện Trường Đại học Đà Lạt |
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Thư viện số |
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English |
topic |
Financial engineering Statistical methods |
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Financial engineering Statistical methods Ruppert, David Matteson, David S Statistics and Data Analysis for Financial Engineering |
description |
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. These methods are critical because financial engineers now have access to enormous quantities of data. To make use of this data, the powerful methods in this book for working with quantitative information, 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, 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. |
format |
Book |
author |
Ruppert, David Matteson, David S |
author_facet |
Ruppert, David Matteson, David S |
author_sort |
Ruppert, David |
title |
Statistics and Data Analysis for Financial Engineering |
title_short |
Statistics and Data Analysis for Financial Engineering |
title_full |
Statistics and Data Analysis for Financial Engineering |
title_fullStr |
Statistics and Data Analysis for Financial Engineering |
title_full_unstemmed |
Statistics and Data Analysis for Financial Engineering |
title_sort |
statistics and data analysis for financial engineering |
publisher |
Springer |
publishDate |
2015 |
url |
https://scholar.dlu.edu.vn/thuvienso/handle/DLU123456789/57455 |
_version_ |
1819781612195282944 |