Statistics and Data Analysis for Financial Engineering

David S. Matteson

ISBN 10: 1493926136 / ISBN 13: 9781493926138

Verlag: Springer New York, Springer US Apr 2015, 2015

Beschreibung

This item is printed on demand - it takes 3-4 days longer - Neuware -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 and an Instructor s Manual with solutions to all exercises and problems in the R labs. Practicing financial engineers will also find this book of interest. 748 pp. Englisch. Bestandsnummer des Verkäufers 9781493926138

Bibliografische Details

Titel: Statistics and Data Analysis for Financial ...

Verlag: Springer New York, Springer US Apr 2015

Erscheinungsdatum: 2015

Einband: Buch

Zustand: Neu

Auflage: 2. Auflage

Über diesen Titel

Inhaltsangabe:

<P>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. </P>

Reseña del editor:

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.