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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 with solutions, and data.
To contribute, check the developer GitHub webpage.
Work in progress… exercises with solutions coming up in the subsequent weeks and slides will be significantly revised next semester.
Chapter 2 – Financial Data: Stylized Facts: slides, R code, Python code, exercises, solutions
Chapter 3 – Financial Data: I.I.D. Modeling: slides, R code, Python code, exercises
Chapter 4 – Financial Data: Time Series Modeling: slides, R code, Python code, exercises
Chapter 5 – Financial Data: Graphs: slides, R code, exercises
Chapter 6 – Portfolio Basics: slides, R code, Python code, exercises
Chapter 7 – Modern Portfolio Theory: slides, R code, Python code, exercises
Chapter 8 – Portfolio Backtesting: slides, R code, Python code, exercises
Chapter 9 – High-Order Portfolios: slides, R code, exercises
Chapter 10 – Portfolios with Alternative Risk Measures: slides, R code, Python code, exercises
Chapter 11 – Risk Parity Portfolios: slides, R code, Python code, exercises, solutions
Chapter 12 – Graph-Based Portfolios: slides, R code, exercises
Chapter 13 – Index Tracking Portfolios: slides, R code, Python code, exercises
Chapter 15 – Pairs Trading Portfolios: slides, R code, exercises, solutions
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
Prof. Daniel P. Palomar: Website
GitHub: https://github.com/dppalomar
LinkedIn: https://www.linkedin.com/in/daniel-palomar-8373a1b7
YouTube: https://www.youtube.com/danielpalomar
X: https://x.com/danielppalomar
Google Scholar: https://scholar.google.com/danielpalomar