Analyzing Financial Data and Implementing Financial Models Using R [electronic resource] /

By:

Ang, Clifford S [author.]

Contributor(s):

SpringerLink (Online service)

Material type: Text

TextSeries: Springer Texts in Business and EconomicsPublisher: Cham : Springer International Publishing : Imprint: Springer, 2021Edition: 2nd ed. 2021Description: XVI, 465 p. 63 illus., 56 illus. in color. online resourceContent type:

text

Media type:

computer

Carrier type:

online resource

ISBN:

9783030641559

Subject(s):

Additional physical formats: Printed edition:: No title; Printed edition:: No title; Printed edition:: No titleDDC classification:

658.155 23

LOC classification:

HD61

Online resources:

Click here to access online

Contents:

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.

In: Springer Nature eBookSummary: 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.

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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.

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