advanced-math-trading/simulation-inference

Monte Carlo simulations generate multiple market pathways by sampling random outcomes repeatedly. This Skill creates thousands of SDE paths using Brownian and jump-diffusion processes, enabling you to stress-test strategies across a distribution of potential futures rather than single predictions.

Brownian motion models continuous price changes; jump-diffusion adds sudden discontinuous shifts to capture tail events like market gaps. This Skill supports both, letting you choose based on whether your asset exhibits sudden jumps or only continuous drift.

Discretization schemes convert continuous SDEs into discrete time steps. This Skill evaluates accuracy and stability across schemes, helping you balance computational speed against error—critical for large-scale scenario generation where precision requirements vary by use case.

Yes. Jump-diffusion processes capture heavy tails and extreme moves beyond normal distributions. This Skill generates paths with both continuous Brownian components and discrete jump events, making it suitable for assets prone to sudden price shocks.

Understanding SDEs helps, but this Skill provides modular process and discretization references to abstract complexity. You supply parameters and select process types; the Skill handles path generation and scheme evaluation, lowering the entry barrier for scenario planning.