Ch 1/2: Uni- and multi-variate statistics, see here
Ch 3: Quest for Invariance, see here
Ch 3: Projection of invariants to investment horizon, see here
Ch 3: Pricing of individual securities, see here
Ch 3: Linear factor models (PCA, time series,…), see here
Ch 3: Swaps modeling using Principal Component Analysis, see here
Ch 4: Multivariate estimation (non-parametric, MLE, shrinkage, robust,…), see here
Ch 5: Risk evaluation (stochastic dominance, expected utility, VaR, CVaR, spectral measures,…), see here
Ch 6: Portfolio optimization (mean-variance, cone programming, benchmark allocation,…), see here
Ch 7: Bayesian estimation, see here
Ch 8: Estimation risk evaluation, see here
Ch 9: Estimation risk and allocation optimization (Bayes, Black-Litterman, robust,…), see here
App A: Linear Algebra, see here
App B: Functional Analysis, see here
Tedious proofs and technical results, see here.
MATLAB code for advanced risk and portfolio management, see here.
Challenges, pitfalls and step-by-step solutions with MATLAB code, see ARPM here.