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Mastering R for Quantitative Finance

You're reading from   Mastering R for Quantitative Finance Use R to optimize your trading strategy and build up your own risk management system

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Product type Paperback
Published in Mar 2015
Publisher
ISBN-13 9781783552078
Length 362 pages
Edition 1st Edition
Languages
Tools
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Toc

Table of Contents (15) Chapters Close

Preface 1. Time Series Analysis FREE CHAPTER 2. Factor Models 3. Forecasting Volume 4. Big Data – Advanced Analytics 5. FX Derivatives 6. Interest Rate Derivatives and Models 7. Exotic Options 8. Optimal Hedging 9. Fundamental Analysis 10. Technical Analysis, Neural Networks, and Logoptimal Portfolios 11. Asset and Liability Management 12. Capital Adequacy 13. Systemic Risks Index

Summary

In this chapter, we saw how a multifactor model can be built and implemented. As a result of a principal component analysis, we identified five independent factors that explained asset returns, but they seemed to be insufficient, given that they explained only 30 percent of the variance. For illustration, we also reproduced the famous Fama-French model on real market data, where, apart from the market factor, two additional firm-specific factors (SMB and HML) were also used. We used built-in functions for principal component analysis and factor analysis, and we have shown how to use a general linear model for regression analysis.

We found that the three factors were significant. Hence, we can conclude that on a more recent sample, the Fama-French factors have explanatory power. We encourage you to develop and test new multifactor pricing formulas that work as the classical ones, or even better.

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