发帖
雷达卡
Are you innately curious about dynamically inter-operating financial markets? Since the crisis of 2008, there is a need for professionals with more understanding about statistics and data analysis, who can discuss the various risk metrics, particularly those involving extreme events. By providing a resource for training students and professionals in basic and sophisticated analytics, this book meets that need. It offers both the intuition and basic vocabulary as a step towards the financial, statistical, and algorithmic knowledge required to resolve the industry problems, and it depicts a systematic way of developing analytical programs for finance in the statistical language R. Build a hands-on laboratory and run many simulations. Explore the analytical fringes of investments and risk management. Bennett and Hugen help profit-seeking investors and data science students sharpen their skills in many areas, including time-series, forecasting, portfolio selection, covariance clustering, prediction, and derivative securities.
Editorial ReviewsReview
"A very well-written text on financial analytics, focusing on developing statistical models and using simulation to better understand financial data. R is used throughout for examples, allowing the reader to use the text and code to actively engage in the financial market. It is simply the best text on this subject that I have seen. Highly recommended."
Joseph M. Hilbe, Arizona State University
Book Description
This book provides the intuition and basic vocabulary as steps towards the financial, statistical, and algorithmic knowledge needed to resolve current industry problems, while also presenting a systematic way of developing analytical programs for finance in the statistical language R. This book is a key training resource for students and professionals alike.
About the Author
Mark J. Bennett is a senior data scientist with a major investment bank and a lecturer in the University of Chicago's Master's program in analytics. He has held software positions at Argonne National Laboratory, Unisys Corporation, AT&T Bell Laboratories, Northrop Grumman, and XR Trading Securities.
Dirk L. Hugen is a graduate student in the Department of Statistics and Actuarial Science at the University of Iowa. He previously worked as a signal processing engineer.
Product Details
|
Financial Analytics with R.pdf
(11.35 MB, 需要: 15 个论坛币)
提升卡
置顶卡
沉默卡
变色卡
抢沙发
千斤顶
显身卡
京公网安备 11010802022788号
