ISBN: 9781493951734 - statistics and data analysis for financial engineering: with r examples (springer texts in statistics) (3 Ergebnisse)

Sprache: Englisch
Verlag: Springer (edition Softcover reprint of the original 2nd ed. 2015), 2016
- Softcover
Anbieter: BooksRun, Philadelphia, PA, USABooksRun
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Paperback. Zustand: Very Good. It's a well-cared-for item that has seen limited use. The item may show minor signs of wear. All the text is legible, with all pages included. It may have slight markings and/or highlighting. Softcover reprint of the original 2nd ed. 2015.

Sprache: Englisch
Verlag: Springer, 2016
- Softcover
Anbieter: preigu, Osnabrück, Deutschlandpreigu
Verkäufer/-in kontaktierenVerkäufer/-in mit 5 SternenZustand: Neu
EUR 95,25
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Taschenbuch. Zustand: Neu. Statistics and Data Analysis for Financial Engineering | with R examples | David Ruppert (u. a.) | Taschenbuch | Springer Texts in Statistics | xxvi | Englisch | 2016 | Springer | EAN 9781493951734 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu. …

Sprache: Englisch
Verlag: Springer, 2016
- Softcover
Anbieter: AHA-BUCH GmbH, Einbeck, DeutschlandAHA-BUCH GmbH
Verkäufer/-in kontaktierenVerkäufer/-in mit 5 SternenZustand: Neu
EUR 121,81
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Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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.…