Statistics and Data Analysis for Financial Engineering

Specificaties
Paperback, 638 blz. | Engels
Springer New York | 2011e druk, 2012
ISBN13: 9781461427490
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Springer New York 2011e druk, 2012 9781461427490
Onderdeel van serie Springer Texts in Statistics
Verwachte levertijd ongeveer 9 werkdagen

Samenvatting

<div style="MARGIN: 0in 0in 0pt; LINE-HEIGHT: normal">Financial engineers have access to enormous quantities of data but need powerful methods for extracting quantitative information, particularly about volatility and risks. Key features of this textbook are: illustration of concepts with financial markets and economic data, R Labs with real-data exercises, and integration of graphical and analytic methods for modeling and diagnosing modeling errors. Despite some overlap with the author's undergraduate textbook <em>Statistics and Finance: An Introduction</em>, this book differs from that earlier volume in several important aspects: it is graduate-level; computations and graphics are done in R; and many advanced topics are covered, for example, multivariate distributions, copulas, Bayesian computations, VaR and expected shortfall, and cointegration. </div>
<div style="MARGIN: 0in 0in 0pt; LINE-HEIGHT: normal">The prerequisites are basic statistics and probability, matrices and linear algebra, and calculus.</div>
<div style="MARGIN: 0in 0in 0pt; LINE-HEIGHT: normal">Some exposure to finance is helpful.</div>

Specificaties

ISBN13:9781461427490
Taal:Engels
Bindwijze:paperback
Aantal pagina's:638
Uitgever:Springer New York
Druk:2011

Inhoudsopgave

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.

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        Statistics and Data Analysis for Financial Engineering