© 2015

Analyzing Financial Data and Implementing Financial Models Using R


Part of the Springer Texts in Business and Economics book series (STBE)

Table of contents

  1. Front Matter
    Pages i-xvi
  2. Clifford S. Ang
    Pages 1-53
  3. Clifford S. Ang
    Pages 55-78
  4. Clifford S. Ang
    Pages 79-113
  5. Clifford S. Ang
    Pages 115-159
  6. Clifford S. Ang
    Pages 161-191
  7. Clifford S. Ang
    Pages 193-208
  8. Clifford S. Ang
    Pages 209-240
  9. Clifford S. Ang
    Pages 241-302
  10. Clifford S. Ang
    Pages 303-331
  11. Back Matter
    Pages 333-351

About this book


This book is a comprehensive introduction to financial modeling that teaches advanced undergraduate and graduate students in finance and economics how to use R to analyze financial data and implement financial models. This text will show students how to obtain publicly available data, manipulate such data, implement the models, and generate typical output expected for a particular analysis.

This text aims to overcome several common obstacles in teaching financial modeling. First, most texts do not provide students with enough information to allow them to implement models from start to finish. In this book, we walk through each step in relatively more detail and show intermediate R output to help students make sure they are implementing the analyses correctly. Second, most books deal with sanitized or clean data that have been organized to suit a particular analysis. Consequently, many students do not know how to deal with real-world data or know how to apply simple data manipulation techniques to get the real-world data into a usable form. This book will expose students to the notion of data checking and make them aware of problems that exist when using real-world data. Third, most classes or texts use expensive commercial software or toolboxes. In this text, we use R to analyze financial data and implement models. R and the accompanying packages used in the text are freely available; therefore, any code or models we implement do not require any additional expenditure on the part of the student.

Demonstrating rigorous techniques applied to real-world data, this text covers a wide spectrum of timely and practical issues in financial modeling, including return and risk measurement, portfolio management, options pricing, and fixed income analysis.


Data Analysis Financial Analysis Financial Modeling Investment Analysis R package

Authors and affiliations

  1. 1.Compass LexeconChicagoUSA

About the authors

Clifford S. Ang, CFA is a Vice President at Compass Lexecon in Chicago.  He specializes in valuation, corporate finance, and damages, and has worked on hundreds of engagements involving companies across a broad spectrum of industries.  Ang has held teaching appointments at DePaul University, the University of the Philippines, and Ateneo de Manila University, where he has taught courses in investments, investment management, corporate finance, and international finance.  He is a CFA Charterholder and holds an MS in Finance from the University of the Philippines.  Ang also holds a BSBA majoring in finance and accounting from Washington University in St. Louis, where he subsequently completed doctoral coursework in finance, economics, and econometrics.  He also presented at the 2012 R in Finance Conference a method to estimate the market value of illiquid debt.

Bibliographic information

Industry Sectors
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Finance, Business & Banking
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“This book is aimed at students in finance and economics who are beginners to the R statistical programming language. … We recommend the book for its intended audience, plus perhaps personal investors who want to experiment in R with portfolio optimization and simulation studies of likely ranges of securities.” (Lauren Burr and Tom Burr, Technometrics, Vol. 58 (2), April, 2016)