Books and Tools for Practical Portfolio Optimization
Summary
The document responds to a request for rigorous resources that connect portfolio-optimization theory with practical implementation. It points readers to several books using R, Matlab, or S, and briefly compares their audiences and coverage. Topics mentioned include modern portfolio theory, optimization fundamentals, risk, and extensions such as Black-Litterman and other portfolio approaches.
The recommendations range from advanced treatments aimed at quantitative researchers and portfolio managers to introductory, coding-focused material built around R packages. A Matlab-based text is described as especially comprehensive on optimization basics, while an older S-based book offers material that readers may be able to translate into R. The question also asks about dynamic optimization with constraints that change over time, but the answer does not directly identify a specific dynamic-optimization reference or explain a method for handling time-varying constraints. The document is therefore useful as a starting bibliography rather than a complete treatment or comparative evaluation of the books.
Key ideas
- Portfolio-optimization references vary in their balance of theory, code, and implementation detail.
- Some recommended books use R or Matlab examples to teach optimization concepts.
- The cited material ranges from introductory package-oriented guides to advanced treatments.
- The recommendations cover topics such as risk and extensions to classical portfolio theory.
- The response does not directly resolve the question about changing constraints over time.
Tags
Full text
# reference question about portfolio optimization # reference question about portfolio optimization I know the "classical" modern portfolio theory. However I have quite a lot of different sources. It seems that there is not a book which cover this topic in a rigorous way: - theory - application - examples in c++ / R / matlab / ... Are there any books, which cover these points? Recently, we discussed in class a dynamic portfolio optimization problem. Now I would like to know if there is any good literature about this topic? With dynamic portfolio optimization I mean changing constraints over time. Many thanks for sharing your experiences. ## Answer by Alexander Didenko (score 5, accepted) https://quant.stackexchange.com/a/14139 There are plenty of books on portfolio issues built according to formula "some theory + some R code (or Matlab, or S - which is very similar to R)". See for example - Pfaff B. Financial Risk Modelling and Portfolio Optimization with R.// 2013. - Best M.J. Portfolio Optimization. Chapman & Hall, 2010. - Würtz D. et al. Portfolio Optimization with R/Rmetrics. // Rmetrics, 2009. - Sherer B, Martin R.D. Introduction to Modern Portfolio Optimization With NUOPT and S-PLUS. // 2006. [1] is with examples from many R packages, and covers not only MPT but risk issues and MPT+ things like Black-Litterman and Meucci's approaches. [2] is based on Matlab examples, have very comprehensive optimization basics, and is more like quant-student-oriented book (unlike [1] which is more quant-PhD-advanced-portfolio-managers-oriented). [3] is entirely dedicated to Rmetrics R packages for optimizatioin, with some very basic theory. More like introductory thing, suitable for everyone from for bachelor student to somebody looking for a good coding-oriented start in the field. [4] is the oldest book, based on S, but all examples are easily translatable to R. Hence, no packages are introduced + the reader is supposed to be able to cope with some difficulties when translating from S to R. But still there are a few interesting advanced things in the book.
Shown in full with attribution under the source's licence. Licence: CC BY-SA 4.0 (Stack Exchange)
This summary was written by Stratmill's research agent from the original; it is not a copy of the source.