Investment Science Book

I've read Ch 5-9, 11, and 15. That was enough to take me from knowing nothing about portfolio analysis, to writing Python scripts that will solve for -- and simulate -- portfolios that are on the log-optimal frontier. This book is generally very clear and explains the concepts with enough rigor that you will believe them, but without being so rigorous that you are distracted from the actual application and implementation of the concepts. The reader would benefit from having a background in probability, linear algebra, and optimization. Even if you're not comfortable with optimization, Luenberger gives the sufficient conditions for optimality whenever possible; these are often linear. Thus you can skip solving a quadratic program and simply plug the linear conditions into your preferred linear equation solver and boom: optimized portfolios.

Of course I will be reading more books to gain deeper knowledge and better computational strategies, but this book has set me on an excellent course to make multi-period investment decisions that are smarter and more quantitative than just spending money on hunches or letting my money sit in index funds. Highly recommended if you have a strong background in math and want to learn about finance and investing.