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Stochastic Differential Equation (SDE) Models

Parametric models, such as Geometric Brownian Motion (GBM) and Heston Volatility

A stochastic differential equation (SDE) is a differential equation where one or more of the terms is a stochastic process, resulting in a solution, which is itself a stochastic process. SDEs are used to model phenomena such as fluctuating stock prices and interest rates. This toolbox provides a collection of SDE tools to build and evaluate stochastic models using Monte Carlo and quasi-Monte Carlo simulations. Quasi-Monte Carlo simulation is a Monte Carlo simulation that uses quasi-random sequences instead of pseudo random numbers. You can develop models to capture detailed information about unlikely or worst-case scenarios or to obtain approximate solutions to problems that are otherwise intractable or time-consuming to analyze with traditional analytical techniques.


  • Specification
    Create SDE models
  • Simulation
    Generate standard Monte Carlo and Quasi-Monte Carlo simulations from SDE models