Statistics and Data Analysis for Financial Engineering 在線電子書 圖書標籤: 金融 Finance Statistics 金融工程 R 統計學 統計 Financial_Engineering
發表於2024-12-23
Statistics and Data Analysis for Financial Engineering 在線電子書 pdf 下載 txt下載 epub 下載 mobi 下載 2024
很詳細的書,現在還是做統計的比較有用哦
評分Stats 509
評分滿分不解釋。
評分康奈爾金工齣品。起點低,選題廣,cover瞭計量金融的主要問題。講的也耐心仔細,非常強調實踐,與R的結閤是最大亮點。缺點是typo比較多,理論性略不足。
評分按照 coursera的 compfina 在讀. 1,2,3,4,5,6,7,9,11,12,13 charpter;2012-11-10課程學完,
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.
想看一下,但是英文的看的挺吃力,不知道有没有翻译过来啊,很想学习一下,最近在忙着金融建模,为什么字数还不够啊AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
評分想看一下,但是英文的看的挺吃力,不知道有没有翻译过来啊,很想学习一下,最近在忙着金融建模,为什么字数还不够啊AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
評分想看一下,但是英文的看的挺吃力,不知道有没有翻译过来啊,很想学习一下,最近在忙着金融建模,为什么字数还不够啊AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
評分想看一下,但是英文的看的挺吃力,不知道有没有翻译过来啊,很想学习一下,最近在忙着金融建模,为什么字数还不够啊AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
評分想看一下,但是英文的看的挺吃力,不知道有没有翻译过来啊,很想学习一下,最近在忙着金融建模,为什么字数还不够啊AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
Statistics and Data Analysis for Financial Engineering 在線電子書 pdf 下載 txt下載 epub 下載 mobi 下載 2024