# Statistics and Data Analysis for Financial Engineering

This is a nice book that blends modern statistical techniques with practical R code that makes it easy to explore, understand, and model financial data. Readers unfamiliar with this book can see what others have said here.

To learn this material as well as possible I worked through the book's problems and exercises and wrote up my solutions and put them in book form. The R scripts used in the solutions for the various chapters are given below. The solution manual has detailed explanations of the R codes below and further explanations of the questions asked in the end of chapter exercises. Note that in this solution manual I've worked all of the problems in the most recent (2nd Edition) version of the textbook.

Originally my solutions were written in PDF (using the mathematical typesetting language LaTeX). I converted the PDF format to a format I thought more people would find more convenient. You can preview and buy a kindle version of the solution manual here. If you are interested in purchasing the PDF version please contact me below.

Simple R Code For Various Chapters:
• Chapter 2 (Returns)
• Chapter 3 (Fixed Income Securities)
• Chapter 4 (Exploratory Data Analysis)
• Chapter 5 (Modeling Univariate Distributions)
• Chapter 6 (Resampling)
• Chapter 7 (Multivariate Statistical Models)
• Chapter 8 (Copulas)
• Chapter 9 (Time Series Models: Basics)
• Chapter 10 (Time Series Models: Further Topics)
• Chapter 11 (Portfolio Theory)
• Chapter 12 (Regression Basics)
• Chapter 13 (Regression Troubleshooting)
• Chapter 14 (Regression Advanced Topics)
• Chapter 15 (Cointegration)
• Chapter 16 (The Capital Asset Pricing Model)
• Chapter 17 (Factor Models and Principal Components)
• Chapter 18 (GARCH Models)
• Chapter 19 (Risk Management)
• Chapter 20 (Bayesian Data Analysis and MCMC)
• Chapter 21 (Nonparametric Regression and Splines)
As always, I am interested in hearing about any errors that might exist in this material.

John Weatherwax