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Analyzing financial data and impleme...

Ang, Clifford S.

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Analyzing financial data and implementing financial models using R

Record Type:	Electronic resources : Monograph/item
Title/Author:	Analyzing financial data and implementing financial models using R/ by Clifford S. Ang.
Author:	Ang, Clifford S.
Published:	Cham :Springer International Publishing : : 2021.,
Description:	xvi, 465 p. :ill., digital ;24 cm.
[NT 15003449]:	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.
Contained By:	Springer Nature eBook
Subject:	Finance - Mathematical models. -
Online resource:	https://doi.org/10.1007/978-3-030-64155-9
ISBN:	9783030641559

Analyzing financial data and implementing financial models using R
Ang, Clifford S.

Analyzing financial data and implementing financial models using R[electronic resource] /by Clifford S. Ang. - Second edition. - Cham :Springer International Publishing :2021. - xvi, 465 p. :ill., digital ;24 cm. - Springer texts in business and economics,2192-4333. - Springer texts in business and economics..

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.

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.

ISBN: 9783030641559

Standard No.: 10.1007/978-3-030-64155-9doiSubjects--Topical Terms:

578740
Finance
--Mathematical models.

LC Class. No.: HG106 / .A53 2021

Dewey Class. No.: 332

Analyzing financial data and implementing financial models using R
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245 1 0 $a Analyzing financial data and implementing financial models using R $h [electronic resource] / $c by Clifford S. Ang.
250 $a Second edition.
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2021.
300 $a xvi, 465 p. : $b ill., digital ; $c 24 cm.
490 1 $a Springer texts in business and economics, $x 2192-4333
505 0 $a 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.
520 $a 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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650 0 $a R (Computer program language) $3 784593
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