691 pages; Quantitative and Qualitative Treatments to Capital Markets; Notes on Abstract Linear Algebra (PART VI)
Preview of Notes
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Toc:
We have already kicked off our programming series with a start on data structures for formulaic alpha encoding:
and implemented it in Python:
Last week, we conducted an investigation of complex and real vector spaces, and covered important topics such as Jordan forms, characteristic polynomials, eigendecomposition, right/left inverses, pseudo-inverse and so on.
In this post, we round up the abstract linear algebra series with our notes on matrix trace and determinants, which are very important properties of matrices and operators. Readers should be equipped with knowledge of a fair amount of linear algebra at this point, and we will add on more advanced concepts in the future, as well as use what we learnt extensively.
The next few posts will cover our classical alpha report, programming of the required traversal algorithms and recursion exercises for the alpha tree, as well as new topics in convex optimization.
Full notes, 691 pages (paid):