Portfolio · Modeling tools

A white panda building modeling tools.

I build numerical solvers and visual diagnostics for PDEs and option pricing. Explore the heat equation and Black-Scholes models, then run live experiments with the solvers below.

Try the solvers See projects

Focus Finite differences, stability, accuracy

Tools Python, NumPy, SciPy, Matplotlib

Featured Toolkit

Heat equation + Black-Scholes solvers with implicit, explicit, and CN schemes.

Interactive parameter entry
Matplotlib surface plots
Analytical comparison toggles

What I care about

Tradeoffs: accuracy vs. stability, and where oscillations appear.

Read the background notes →

Projects

Current work plus room for what is next.

Numerical approximations for the Black-Scholes PDE with stability diagnostics, plus 1D heat equation solvers across explicit, implicit, and Crank-Nicolson schemes.

Finite Differences Rannacher stepping Matplotlib

Run the models

Space reserved for upcoming modeling tools and research experiments.

Live Solver

Enter parameters and generate the Matplotlib surface plots on demand.

Method Method notes

f(x, t) u(x, 0) u(a, t) u(b, t) a (left endpoint) b (right endpoint) l (time horizon) n (space steps) m (time steps)

Method Model notes

Show comparison with analytical solution

K (strike price) T (maturity) r (% per year) sigma (% per year) n (space steps) m (time steps)

Results

Plots appear here after you run a solver.