This advanced undergraduate/graduate textbook teaches students in finance and economics how to use R to analyse financial data and implement financial models. It demonstrates how to take publically available data and manipulate, implement models and generate outputs typical for particular analyses. A wide spectrum of timely and practical issues in financial modelling are covered including return and risk measurement, portfolio management, option pricing and fixed income analysis. This new edition updates and expands upon the existing material providing updated examples and new chapters on equities, simulation and trading strategies, including machine learnings techniques. Select data sets are available online.

Features new chapters on equities, simulation and trading strategies Provides updated discussions and revised examples Guides students step-by-step through the modeling process and reports intermediate output Instructs students to analyze financial data and implement financial models using R using real-world data

Autorentext

Clifford Ang is an Executive Vice President in the Oakland, CA and Chicago, IL offices of Compass Lexecon, where he specializes in valuing businesses & hard-to-value assets and analyzing complex financial statement issues. He has worked on hundreds of engagements involving firms across a broad-spectrum of industries concerning a wide-range of financial and economic issues, such as appraisals, complex asset pricing, solvency, lost profits, market efficiency, loss causation, and damages. Ang also teaches equity and bond valuation courses in DataCamp, an interactive learning platform for data science.

Inhalt
Chapter 1 Prices.- Chapter 2 Individual Security Returns.- Chapter 3 Portfolio Returns.- Chapter 4 Risk.- Chapter 5 Factor Models.- Chapter 6 Risk-Adjusted Portfolio Performance Measures.- Chapter 7 Markowitz Mean-Variance Optimization.- Chapter 8 Fixed Income.- Chapter 9 Options.- Appendix A Getting Started with R. Appendix B Constructing a Hypothetical Portfolio.