Portfolio Optimization Book
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Portfolio Optimization: Theory and Application |
Book available here: pdf and online html
For purchase here: Cambridge University Press, Amazon, Barnes & Noble, Bookshop.org, Hive, Indigo, Hatchards, Hugendubel
This is the homepage for the Portfolio Optimization Book. It contains slides, code examples (R and Python), exercises, and data.
To contribute, check the developer GitHub webpage.
Chapters
Work in progress, Python code coming up in the subsequent weeks…
- Chapter 1 - Introduction: slides
Part I - Financial Data
Chapter 2 - Financial Data: Stylized Facts: slides , R code , Python code
Chapter 3 - Financial Data: I.I.D. Modeling: slides , R code , Python code
Chapter 4 - Financial Data: Time Series Modeling: slides , R code , Python code
Part II - Portfolio Optimization
Chapter 6 - Portfolio Basics: slides , R code , Python code
Chapter 7 - Modern Portfolio Theory: slides , R code , Python code
Chapter 8 - Portfolio Backtesting: slides , R code , Python code
Chapter 10 - Portfolios with Alternative Risk Measures: slides , R code , Python code
Chapter 11 - Risk Parity Portfolios: slides , R code , Python code
Chapter 13 - Index Tracking Portfolios: slides , R code , Python code
Chapter 16 - Deep Learning Portfolios: slides
Appendices
Miscellanea
Sample slide title page with customizable course info on a textbox.
Stock and crypto data used in the sample code can be conveniently found at https://github.com/dppalomar/pob
Resources for R: Primer on R for Finance, Solvers in R
Resources for Python: Primer on Python for Finance, Solvers in Python