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The textbook is an introduction to data science/data analysis applied to finance, using R and its most recent and freely available extension libraries. The target audience are undergrad data science, finance and graduate students, and practitioners or professionals who need a desk reference.
List of contents
1. Your Working Environment 2. Reading Data in R 3. Financial Data 4. Introduction to R 5. Functions 6. Data Transformation 7. Merging Data Sets 8. Graphing Using Ggplot 9. Returns and Returns-based Statistics 10. Portfolios 11. Modeling Returns and Simulations 12. Linear and Polynomial Regression 13. Fixed Income 14. Principal Component Analysis 15. Options 16. Value at Risk 17. Time Series Analysis 18. Machine Learning 19. Presenting the Results of Your Analyses 20. Appendix: Main Packages Seen in this Book
About the author
Jean-Francois Collard holds a PhD in Computer Science from the University of Paris and a Habilitation from the University of Versailles, France. He was a scientist at the National Center for Scientific Research (CNRS) in Versailles then at HP Labs in Palo Alto, California, and an engineer at Intel in Santa Clara, California. He then had various quantitative roles at Citigroup, Santander and currently in the Investment Consulting Group of New York Life Investment Management. He is also an Adjunct Associate Professor at Baruch College in New York, USA.
Summary
The textbook is an introduction to data science/data analysis applied to finance, using R and its most recent and freely available extension libraries. The target audience are undergrad data science, finance and graduate students, and practitioners or professionals who need a desk reference.
