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Great text for someone with prior background in Probability Theory and Calculus. A crisp, to-the-point text book for financial econometrics. This book broadly covers many statistical techniques applied in finance. Most likely the audience for this book is for students in Quant Finance programs learning some statistics techniques.
I guess it succeeds in that purpose.
But for researchers, statisticians, or practitioners there is not enough depth. I rated this book 2 stars rather than 1 star, because I do believe Ruppert did a good job introducing difficult topics, for example the Bayesian methods. But generally, this book and his other This book broadly covers many statistical techniques applied in finance.
But generally, this book and his other undergraduate version "Statistics and Finance" are not worth reading unless you are completely new to a topic. That being said, some of Ruppert's other books are quite nice, for example "Semiparametric Regression".
Statistics and data analysis for financial engineering : with R examples in SearchWorks catalog
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There is an appendix on probability, statistics and linear algebra. Practicing financial engineers will also find this book of interest. Generalized Linear Models for Insurance Data. Piet de Jong. Economic Forecasting and Policy. Introductory Econometrics. Humberto Barreto. The Black—Scholes Model.
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Statistics and Data Analysis for Financial Engineering
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