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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.

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Product type Paperback
Published in Nov 2013
Publisher Packt
ISBN-13 9781783280933
Length 164 pages
Edition 1st Edition
Languages
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Toc

Table of Contents (17) Chapters Close

Introduction to R for Quantitative Finance
Credits
About the Authors
About the Reviewers
www.PacktPub.com
Preface
1. Time Series Analysis 2. Portfolio Optimization FREE CHAPTER 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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