An Introduction to Analysis of Financial Data with R

Ruey S. Tsay

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English

John Wiley & Sons Inc
07 December 2012

Economic statistics; Finance; Probability & statistics

Series: Wiley Series in Probability and Statistics

A complete set of statistical tools for beginning financial analysts from a leading authority

Written by one of the leading experts on the topic, An Introduction to Analysis of Financial Data with R explores basic concepts of visualization of financial data. Through a fundamental balance between theory and applications, the book supplies readers with an accessible approach to financial econometric models and their applications to real-world empirical research.

The author supplies a hands-on introduction to the analysis of financial data using the freely available R software package and case studies to illustrate actual implementations of the discussed methods. The book begins with the basics of financial data, discussing their summary statistics and related visualization methods. Subsequent chapters explore basic time series analysis and simple econometric models for business, finance, and economics as well as related topics including:

Linear time series analysis, with coverage of exponential smoothing for forecasting and methods for model comparison Different approaches to calculating asset volatility and various volatility models High-frequency financial data and simple models for price changes, trading intensity, and realized volatility Quantitative methods for risk management, including value at risk and conditional value at risk Econometric and statistical methods for risk assessment based on extreme value theory and quantile regression

Throughout the book, the visual nature of the topic is showcased through graphical representations in R, and two detailed case studies demonstrate the relevance of statistics in finance. A related website features additional data sets and R scripts so readers can create their own simulations and test their comprehension of the presented techniques.

An Introduction to Analysis of Financial Data with R is an excellent book for introductory courses on time series and business statistics at the upper-undergraduate and graduate level. The book is also an excellent resource for researchers and practitioners in the fields of business, finance, and economics who would like to enhance their understanding of financial data and today's financial markets.

By: Ruey S. Tsay
Imprint: John Wiley & Sons Inc
Country of Publication: United States
Dimensions: Height: 234mm, Width: 165mm, Spine: 28mm
Weight: 726g
ISBN: 9780470890813
ISBN 10: 0470890819
Series: Wiley Series in Probability and Statistics
Pages: 416
Publication Date: 07 December 2012
Audience: Professional and scholarly , Undergraduate
Format: Hardback
Publisher's Status: Active

RUEY S. TSAY, PhD, is H.G.B. Alexander Professor of Econometrics and Statistics at The University of Chicago Booth School of Business. Dr. Tsay has written over 100 published articles in the areas of business and economic forecasting, data analysis, risk management, and process control. A Fellow of the American Statistical Association, the Institute of Mathematical Statistics, and Academia Sinica, Dr. Tsay is author of Analysis of Financial Time Series, Third Edition and coauthor of A Course in Time Series Analysis.

Reviews for An Introduction to Analysis of Financial Data with R

I found this book highly informative and interesting toread. The proper mix of theory and hands-on programming examplesmakes it recommended reading for both R programmers interested infinance and financial analysts with a basic programming background.Well written and following a clear and defined logical layout, theauthor has written a current reference text on using a powerfulopen-source programming language for typical financialanalysis. (Computing Reviews, 25 March2014) All in all, this book is a good and useful introductionto financial time series with many real-world examples. It issuitable for use both as a textbook and for self-study, withexercises provided at the end of each chapter. (International Statistical Review, 14 June 2013)