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Introduction to R for Quantitative Finance

You're reading from Introduction to R for Quantitative Finance R is a statistical computing language that's ideal for answering quantitative finance questions. This book gives you both theory and practice, all in clear language with stacks of real-world examples. Ideal for R beginners or expert alike.

Product type Paperback

Published in Nov 2013

Publisher Packt

ISBN-13 9781783280933

Length 164 pages

Edition 1st Edition

Languages

R

Concepts

Financial Technology

Table of Contents (17) Chapters

Introduction to R for Quantitative Finance

Credits

About the Authors

About the Reviewers

www.PacktPub.com

Preface

1. Time Series Analysis FREE CHAPTER

2. Portfolio Optimization

3. Asset Pricing Models

4. Fixed Income Securities

5. Estimating the Term Structure of Interest Rates

6. Derivatives Pricing

7. Credit Risk Management

8. Extreme Value Theory

9. Financial Networks

References

Index

Time series analysis

G. E. P. Box and G. M. Jenkins (1976), Time Series Analysis: Forecasting and Control. Holden-Day, San Francisco.
R. F. Engle (1982), Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of U.K. Inflation, Econometrica 50, 987-1007.
C. W. J. Granger (1981), Some Properties of Time Series Data and Their Use in Econometric Model Specification, Journal of Econometrics 16, 121-130.
R. F. Engle and C. W. J. Granger (1987), Co-Integration and Error Correction: Representation, Estimation, and Testing, Econometrica 55, No. 2, 251-276.
R. F. Engle and B. S. Yoo (1987), Forecasting and Testing in Co-Integrated Systems, Journal of Econometrics 35, 143-159.

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