THE ARCHIVE

Notes

Technical notes on quantitative finance, econometrics, machine learning, and controls, plus the derivations and definitions that hold them together.

Factor models, portfolio construction, covariance estimation, and the linear algebra behind them.

Regression, inference, asymptotics, and the assumptions behind causal claims.

Model selection, loss functions, generalization, neural networks, and reinforcement learning.

Least-squares filtering, matrix norms, projections, and signal-processing foundations.

Short definitions and standalone derivations that support the longer notes.

The complete archive. Filter by subject or browse every note in one place.

START HERE

New to the archive? Begin with The Geometry of Ordinary Least Squares for the intuition behind regression, Factor Models 101 for portfolio construction, or The Gram Matrix and Normal Equations for the linear algebra.