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عنوان
Statistics and data analysis for financial engineering :

پدید آورنده
David Ruppert, David S. Matteson.

موضوع
Finance-- Statistical methods.,Financial engineering-- Statistical methods.,Business & Economics-- Finance.,Business & Economics-- Statistics.,Finance & accounting.,Finance-- Statistical methods.,Finance.,Financial Engineering,Mathematics-- Applied.,Mathematics-- Probability & Statistics-- General.,Probability & statistics.,Statistik,Statistische Analyse

رده
HG176
.
7
.
R86
2015eb

کتابخانه
Center and Library of Islamic Studies in European Languages

محل استقرار
استان: Qom ـ شهر: Qom

Center and Library of Islamic Studies in European Languages

تماس با کتابخانه : 32910706-025

INTERNATIONAL STANDARD BOOK NUMBER

(Number (ISBN
1493926136
(Number (ISBN
1493926144
(Number (ISBN
9781493926138
(Number (ISBN
9781493926145
Erroneous ISBN
9781493926138

NATIONAL BIBLIOGRAPHY NUMBER

Country Code
bnb
Number
b623741

TITLE AND STATEMENT OF RESPONSIBILITY

Title Proper
Statistics and data analysis for financial engineering :
General Material Designation
[Book]
Other Title Information
with R examples /
First Statement of Responsibility
David Ruppert, David S. Matteson.

EDITION STATEMENT

Edition Statement
Second edition.

PHYSICAL DESCRIPTION

Specific Material Designation and Extent of Item
1 online resource (xxvi, 719 pages) :
Other Physical Details
illustrations (some color)

SERIES

Series Title
Springer texts in statistics,
ISSN of Series
1431-875X

INTERNAL BIBLIOGRAPHIES/INDEXES NOTE

Text of Note
Includes bibliographical references and index.

CONTENTS NOTE

Text of Note
Introduction -- Returns -- Fixed income securities -- Exploratory data analysis -- Modeling univariate distributions -- Resampling -- Multivariate statistical models -- Copulas -- Time series models: basics -- Time series models: further topics -- Portfolio theory -- Regression: basics -- Regression: troubleshooting -- Regression: advanced topics -- Cointegration -- The capital asset pricing model -- Factor models and principal components -- GARCH models -- Risk management -- Bayesian data analysis and MCMC -- Nonparametric regression and splines.
0

SUMMARY OR ABSTRACT

Text of Note
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. David Ruppert is Andrew Schultz, Jr., Professor of Engineering and Professor of Statistical Science at Cornell University, where he teaches statistics and financial engineering and is a member of the Program in Financial Engineering. Professor Ruppert received his PhD in Statistics at Michigan State University. He is a Fellow of the American Statistical Association and the Institute of Mathematical Statistics and won the Wilcoxon prize. He is Editor of the Journal of the American Statistical Association-Theory and Methods and former Editor of the Electronic Journal of Statistics and of the Institute of Mathematical Statistics's Lecture Notes?Monographs. Professor Ruppert has published over 125 scientific papers and four books: Transformation and Weighting in Regression, Measurement Error in Nonlinear Models, Semiparametric Regression, and Statistics and Finance: An Introduction. David S. Matteson is Assistant Professor of Statistical Science at Cornell University, where he is a member of the ILR School, Center for Applied Mathematics, Field of Operations Research, and the Program in Financial Engineering, and teaches statistics and financial engineering. Professor Matteson received his PhD in Statistics at the University of Chicago. He received a CAREER Award from the National Science Foundation and won Best Academic Paper Awards from the annual R/Finance conference. He is an Associate Editor of the Journal of the American Statistical Association-Theory and Methods, Biometrics, and Statistica Sinica. He is also an Officer for the Business and Economic Statistics Section of the American Statistical Association, and a member of the Institute of Mathematical Statistics and the International Biometric Society.

ACQUISITION INFORMATION NOTE

Source for Acquisition/Subscription Address
Springer Nature
Stock Number
com.springer.onix. 9781493926145

OTHER EDITION IN ANOTHER MEDIUM

International Standard Book Number
9781493926138

TOPICAL NAME USED AS SUBJECT

Finance-- Statistical methods.
Financial engineering-- Statistical methods.
Business & Economics-- Finance.
Business & Economics-- Statistics.
Finance & accounting.
Finance-- Statistical methods.
Finance.
Financial Engineering
Mathematics-- Applied.
Mathematics-- Probability & Statistics-- General.
Probability & statistics.
Statistik
Statistische Analyse

(SUBJECT CATEGORY (Provisional

BUS061000
K
K
PBT
PBT

DEWEY DECIMAL CLASSIFICATION

Number
658
.
15
Edition
23

LIBRARY OF CONGRESS CLASSIFICATION

Class number
HG176
.
7
Book number
.
R86
2015eb

PERSONAL NAME - PRIMARY RESPONSIBILITY

Ruppert, David,1948-

PERSONAL NAME - ALTERNATIVE RESPONSIBILITY

Matteson, David S.

ORIGINATING SOURCE

Date of Transaction
20201221082845.0
Cataloguing Rules (Descriptive Conventions))
pn

ELECTRONIC LOCATION AND ACCESS

Electronic name
 مطالعه متن کتاب 

[Book]
270410

Y

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