|Stochastic Differential Equation (SDE) model|
|Brownian motion models|
|Constant Elasticity of Variance (CEV) models|
|Cox-Ingersoll-Ross mean-reverting square root diffusion models|
|Diffusion-rate model component|
|Drift-rate model component|
|Geometric Brownian motion model|
|Hull-White/Vasicek Gaussian Diffusion model|
|Stochastic Differential Equation (SDE) model from Drift and Diffusion components|
|SDE with Linear Drift model|
|SDE with Mean-Reverting Drift model|
|Construct SDE model from user-specified functions|
|Construct Brownian motion models|
|Construct Constant Elasticity of Variance (CEV) models|
|Construct Cox-Ingersoll-Ross mean-reverting square root diffusion models|
|Construct drift-rate model components|
|Construct diffusion-rate model components|
|Construct GBM model|
|Construct Heston model|
|Construct HWV model|
|Construct sdeddo model from Drift and Diffusion objects|
|Construct stochastic differential equation from linear drift-rate models|
|Construct stochastic differential equation from mean-reverting drift-rate models|
|Convert time series arrays to functions of time and state|
Use base SDE models to represent a univariate geometric Brownian Motion model.
SDE objects with combinations
of customized drift or diffusion functions and objects.
sdeld objects provide a parametric
alternative to the mean-reverting drift form.
Financial Toolbox™ supports several parametric models based on the SDE class hierarchy.
Model dependent financial and economic variables by performing Monte Carlo simulation of stochastic differential equations (SDEs).
The SDE class structure represents a generalization and specialization hierarchy.
Most models and utilities available with Monte Carlo Simulation of SDEs are represented as MATLAB® objects.