ABSTRACT

Taking a data-driven approach, A Course on Statistics for Finance presents statistical methods for financial investment analysis. The author introduces regression analysis, time series analysis, and multivariate analysis step by step using models and methods from finance.

The book begins with a review of basic statistics, including descriptive statistics, kinds of variables, and types of data sets. It then discusses regression analysis in general terms and in terms of financial investment models, such as the capital asset pricing model and the Fama/French model. It also describes mean-variance portfolio analysis and concludes with a focus on time series analysis.

Providing the connection between elementary statistics courses and quantitative finance courses, this text helps both existing and future quants improve their data analysis skills and better understand the modeling process.

part |60 pages

Introductory Concepts and Definitions

chapter |35 pages

Review of Basic Statistics

chapter |14 pages

Stock Price Series and Rates of Return

part |49 pages

Regression

chapter |27 pages

Simple Linear Regression; CAPM and Beta

chapter 5|19 pages

Multiple Regression and Market Models

part |37 pages

Portfolio Analysis

chapter 6|27 pages

Mean-Variance Portfolio Analysis

chapter 7|7 pages

Utility-Based Portfolio Analysis

part |66 pages

Time Series Analysis

chapter 8|47 pages

Introduction to Time Series Analysis

chapter |16 pages

Regime Switching Models