Roadmaps

The theory line: from calculus and analysis through measure-theoretic probability to stochastic volatility, jumps, and credit — everything derived.

1. 1Calculus for Quants
2. 2Linear Algebra & Optimization for Quants
3. 3Mathematical Foundations of Quantitative Finance
4. 4Real Analysis for Quants
5. 5Measure-Theoretic Probability
6. 6Stochastic Volatility & Measure Change
7. 7From Diffusion to Jumps: Lévy Models in Finance
8. 8BSDE, XVA & Credit Risk
9. 9AI & Machine Learning for Finance
10. 10Portfolio Optimization & Risk

Math, C++ / HPC, systems, microstructure, risk.

1. 1Calculus for Quants
2. 2Linear Algebra & Optimization for Quants
3. 3Mathematical Foundations of Quantitative Finance
4. 4C++ & HPC for Quants
5. 5Quant Systems Design for Quant Engineers
6. 6Hawkes Processes & Market Microstructure
7. 7AI & Machine Learning for Finance
8. 8Portfolio Optimization & Risk

The allocator line: probability, linear algebra, optimization, covariance estimation, constraints, and portfolio audit work.

1. 1Mathematical Foundations of Quantitative Finance
2. 2Linear Algebra & Optimization for Quants
3. 3Measure-Theoretic Probability
4. 4Portfolio Optimization & Risk
5. 5AI & Machine Learning for Finance
6. 6BSDE, XVA & Credit Risk