Analyzing Financial Data and Implementing Financial Models Using R
2nd Edition
Published on 25. June 2022
Book
Paperback/Softback
XVI, 465 pages
978-3-030-64157-3 (ISBN)
Description
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.
More details
Product info
Book
Series
Edition
2nd ed. 2021
Language
English
Place of publication
Cham
Switzerland
Publishing group
Springer International Publishing
Target group
Professional and scholarly
Edition type
Revised edition
Illustrations
7
56 farbige Abbildungen, 7 s/w Abbildungen
XVI, 465 p. 63 illus., 56 illus. in color.
Dimensions
Height: 235 mm
Width: 155 mm
Thickness: 27 mm
Weight
727 gr
ISBN-13
978-3-030-64157-3 (9783030641573)
DOI
10.1007/978-3-030-64155-9
Schweitzer Classification
Other editions
Additional editions
Book
06/2021
2nd Edition
Springer
€117.69
Shipment within 7-9 days
Person
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.
Content
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.