David Ruppert is Andrew Schultz, Jr., Professor of Engineering and Professor of Statistical Science, School of Operations Research and Information Engineering, Cornell University, where he teaches statistics and financial engineering and is a member of the Program in Financial Engineering. His research areas include asymptotic theory, semiparametric regression, functional data analysis, biostatistics, model calibration, measurement error, and astrostatistics. 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 Electronic Journal of Statistics, former Editor of the Institute of Mathematical Statistics's Lecture Notes--Monographs Series, and former Associate Editor of several major statistics journals. Professor Ruppert has published over 100 scientific papers and four books: Transformation and Weighting in Regression, Measurement Error in Nonlinear Models, Semiparametric Regression, and Statistics and Finance: An Introduction.
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 Statistics and Finance: An Introduction, 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. The prerequisites are basic statistics and probability, matrices and linear algebra, and calculus. Some exposure to finance is helpful.
發表於2025-01-31
Statistics and Data Analysis for Financial Engineering 2025 pdf epub mobi 電子書 下載
想看一下,但是英文的看的挺吃力,不知道有沒有翻譯過來啊,很想學習一下,最近在忙著金融建模,為什麼字數還不夠啊AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
評分想看一下,但是英文的看的挺吃力,不知道有沒有翻譯過來啊,很想學習一下,最近在忙著金融建模,為什麼字數還不夠啊AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
評分想看一下,但是英文的看的挺吃力,不知道有沒有翻譯過來啊,很想學習一下,最近在忙著金融建模,為什麼字數還不夠啊AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
評分想看一下,但是英文的看的挺吃力,不知道有沒有翻譯過來啊,很想學習一下,最近在忙著金融建模,為什麼字數還不夠啊AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
評分想看一下,但是英文的看的挺吃力,不知道有沒有翻譯過來啊,很想學習一下,最近在忙著金融建模,為什麼字數還不夠啊AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
圖書標籤: 金融 Finance Statistics 金融工程 R 統計學 統計 Financial_Engineering
按照 coursera的 compfina 在讀. 1,2,3,4,5,6,7,9,11,12,13 charpter;2012-11-10課程學完,
評分這本書非常詳細,實體書拿在手裏跟字典一樣而且還是大開本印刷。最適閤這本書的人並不是需要從頭學起的人,而是那些有一定積澱現在需要跨界的人。書中涉及的專題非常之多,而且就我看過的幾章來說,嚴謹但也僅僅能夠作為導論而已。所以最適閤的讀者是希望快速瞭解一個細分方嚮的人。
評分textbook
評分滿分不解釋。
評分我覺得很贊!尤其是lab session,邊學邊練哦耶!
Statistics and Data Analysis for Financial Engineering 2025 pdf epub mobi 電子書 下載