A Linear Algebra Primer for Financial Engineering: Covariance Matrices, Eigenvectors, OLS, and more (Financial Engineering Advanced Background Series)

This is my favorite book for math finance knowledge. It was never fully clear to me how matrix decompositions work until reading this book. I implemented the code and the examples were very useful to make sure there were no bugs. The linear solvers for symmetric tridiagonal matrices were incredibly insightful and I implemented the method at work. Colleagues were very impressed.You will understand the linear algebra behind least squares, Markowitz portfolio optimization, and other a lot better after reading this book. A gem!

Highly recommend!

Unarguably the best Linear Algebra primer out there for applications to finance. Broad range of topics covered with great depth. I often use it as a quick reference guide.

thank you for the book. it is in good condition

Excellent book!