Numerical Methods for Quants: The Master Field Manual
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About this resource
What you get A comprehensive, desk-oriented field manual for quantitative researchers, developers, and risk professionals. Spanning 93 pages with custom TikZ vector diagrams, practitioner insights, novel quant tricks, and 50 curated interview Q&As, this book is designed specifically to help you master options pricing, calibration, finite differences, finite elements, and machine learning in computational finance.
Included in the download 93-page PDF: Numerical Methods for Quants: The Master Field Manual Complete mathematical derivations and proofs (Newton-Raphson quadratic convergence, Crank-Nicolson stability, Dupire's local volatility, and weak formulations) Detailed, runnable Python/PyTorch implementations for SABR calibration, Leisen-Reimer trees with Peizer-Pratt inversion, COS method option pricing, Crank-Nicolson barrier option pricing, Deep BSDE solvers, and Physics-Informed Neural Networks (PINNs) Boxed "Equation Shortcuts" under complex formulas for rapid desk problem solving Custom visual TikZ diagrams in every single module for intuitive comprehension A dedicated "Novel Quant Trick" section in each module outlining production hacks used on real option desks A dedicated "Proportional Scaling Relationship" box in each module to quickly grasp how errors and grids scale 50 high-yield, interview-style questions with detailed, context-rich answers What's covered (high-level) 1.
Root Finding & Optimization: Bisection, Newton-Raphson, Secant, Nelder-Mead simplex, and SABR volatility calibration 2. Yield Curve Interpolation & Surface Construction: Linear, log-linear, cubic splines, B-splines, Hagan-West Monotone Convex yield curves, and Gatheral's SVI volatility parameterizations 3.
Finite Difference Methods: Theta schemes, Crank-Nicolson, boundary conditions, Rannacher smoothing, and ADI splitting (Douglas-Rachford, Craig-Sneyd) for Heston 4. Monte Carlo Methods: SDE discretization (Euler-Maruyama, Milstein), Heston QE scheme, variance reduction (Antithetic, Control Variates), Sobol sequences, and Brownian Bridge barrier correction 5.
Tree & Lattice Methods: CRR binomial trees, Leisen-Reimer trees with Peizer-Pratt inversion, trinomial trees, and transition probabilities 6. Fourier & Spectral Methods: Characteristic functions, Carr-Madan FFT pricing, the COS method, and kurtosis-adaptive domain truncation 7.
Volatility Surface Construction: Dupire's local volatility derivation, SVI calibration, and local vol vs stochastic vol smile dynamics (Sticky Strike vs Sticky Delta) 8. Convergence, Stability & Performance: Von Neumann stability analysis, CFL conditions, double-precision precision limits, and Numba JIT compilation 9.
What you get
- Instant digital delivery by email after purchase
- Written by a practising quantitative risk modeller
- Desk-focused material, not textbook theory
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