Statistics and Data Analysis for Financial Engineering with R exampl

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 wi

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David Ruppert David S. Matteson

Statistics and Data Analysis for Financial Engineering with R examples Second Edition

Springer Texts in Statistics Series Editors: R. DeVeaux S.E. Fienberg I. Olkin

More information about this series at http://www.springer.com/series/417

David Ruppert



David S. Matteson

Statistics and Data Analysis for Financial Engineering with R examples Second Edition

123

David Ruppert Department of Statistical Science and School of ORIE Cornell University Ithaca, NY, USA

David S. Matteson Department of Statistical Science Department of Social Statistics Cornell University Ithaca, NY, USA

ISSN 1431-875X ISSN 2197-4136 (electronic) Springer Texts in Statistics ISBN 978-1-4939-2613-8 ISBN 978-1-4939-2614-5 (eBook) DOI 10.1007/978-1-4939-2614-5 Library of Congress Control Number: 2015935333 Springer New York Heidelberg Dordrecht London © Springer Science+Business Media New York 2011, 2015 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, express or implied, with respect to the material contained herein or for any errors or omissions that may have been made. Printed on acid-free paper Springer Science+Business Media LLC New York is part of Springer Science+Business Media (www. springer.com)

To Susan David Ruppert

To my grandparents David S. Matteson

Preface

The first edition of this book has received a very warm reception. A number of instructors have adopted this work as a textbook in their courses. Moreover, both novices and seasoned professionals have been using the book for selfstudy. The enthusiastic response to the book motivated a new edition. One major change is that there are now two authors. The second edition improves the book in several ways: all known errors have been corrected and changes in R have been addressed. Considerably more R code is now included. The GARCH chapter now uses the rugarch package, and in the Bayes chapter we now use JAGS in place of OpenBUGS. The first edition was designed primarily as a textbook for use in university courses. Although there is an Instructor’s Manual with solutions to all exercises and all problems in the R labs, t

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