Statistical Analysis of Financial Data: With Examples In R by James Gentle (George Mason University)
- Hands-on analysis of actual financial data
- Accessible coverage of statistical methods
- Exercises to reinforce concepts
Statistical Analysis of Financial Data
Statistical Analysis of Financial Data
Summary
The book is about financial data - security prices and prices of derivatives, and the statistical methods for analyzing such data. It covers statistical models of branching processes, linear discrete time series models, and continuous-time stochastic models, all at an intermediate level (advanced undergraduate or beginning graduate).
Statistical Analysis of Financial Data Summary
Statistical Analysis of Financial Data Reviews
The book is very well written, and fills an important need for an up-to-date textbook about statistical techniques applied to finance. The book explains the theory behind the statistical techniques very well, with good detail. The mathematical notation is appealing and elegant.
~Jerzy Pawlowski, New York University Tandon School of Engineering
I thoroughly enjoyed reading the first two chapters of the book. Often, the first couple of chapters of a book provide a boilerplate discussion of the characteristics of the data and R. Here, the first two chapters are very well developed, to the point that they provide a good general resource to readers approaching the analysis of financial data from several different perspectives. For example, students in statistics usually approach the entire analysis of time series having in mind the potential application to the analysis of financial data, but they know nothing about the characteristics of the data and the financial markets...Just like the previous chapters, I broadly enjoyed reading this chapter. Prof. Gentle explains the topics clearly and often uses simulations to convey the intuition. That's also the way I like to teach these concepts and I think it enhances understanding among economics and finance students. I also commend the way he discusses the lag and difference operators and how they are implemented in R. He devotes quite some space to them, and I believe that is good as many texts go over these concepts too quickly for many students. Likewise, the discussion of the AR(I)MA models is very detailed and clear.
~Jan Annaert, University of Antwerp and Antwerp Management School
The book is very well written, and fills an important need for an up-to-date textbook about statistical techniques applied to finance. The book explains the theory behind the statistical techniques very well, with good detail. The mathematical notation is appealing and elegant.
~Jerzy Pawlowski, New York University Tandon School of Engineering
I thoroughly enjoyed reading the first two chapters of the book. Often, the first couple of chapters of a book provide a boilerplate discussion of the characteristics of the data and R. Here, the first two chapters are very well developed, to the point that they provide a good general resource to readers approaching the analysis of financial data from several different perspectives. For example, students in statistics usually approach the entire analysis of time series having in mind the potential application to the analysis of financial data, but they know nothing about the characteristics of the data and the financial markets...Just like the previous chapters, I broadly enjoyed reading this chapter. Prof. Gentle explains the topics clearly and often uses simulations to convey the intuition. That's also the way I like to teach these concepts and I think it enhances understanding among economics and finance students. I also commend the way he discusses the lag and difference operators and how they are implemented in R. He devotes quite some space to them, and I believe that is good as many texts go over these concepts too quickly for many students. Likewise, the discussion of the AR(I)MA models is very detailed and clear.
~Jan Annaert, University of Antwerp and Antwerp Management School
Overall, I believe the book is perfect for readers with limited statistical and financial knowledge interested in having a first look both at financial data creation and at the statistical methods that could be used to analyse financial data; traders and financial analysts would suffer for the limited real-life examples, but they will benefit for the extensive and detailed introduction to the statistical tools for financial data analysis.
- Massimiliano Caporin, Journal of the Royal Statistical Society, Vol 185, Issue 1, 2022
About James Gentle (George Mason University)
James E. Gentle is University Professor Emeritus at George Mason University. He is a Fellow of the American Statistical Association (ASA) and of the American Association for the Advancement of Science. He is author of Random Number Generation and Monte Carlo Methods and Matrix Algebra.
Table of Contents
1. The Nature of Financial Data. 2. Sources of Financial Data and Software to Work with It. 3. Statistical Analysis of Financial Data. 4. Time Series Analysis. 5. Nonparametric Smoothing and Pattern Recognition. 6. Portfolios of Assets 7. Futures and Derivatives.
Additional information
NPB9781138599499
9781138599499
1138599492
Statistical Analysis of Financial Data: With Examples In R by James Gentle (George Mason University)
New
Hardback
Taylor & Francis Ltd
2020-03-11
666
N/A
Book picture is for illustrative purposes only, actual binding, cover or edition may vary.
This is a new book - be the first to read this copy. With untouched pages and a perfect binding, your brand new copy is ready to be opened for the first time