Hi Todd,
I understand that you want to simulate a GARCH model forecast to create a probability distribution.
To simulate a GARCH (Generalized Autoregressive Conditional Heteroskedasticity) model forecast and create a probability distribution using MathWorks products, you can use the Econometrics Toolbox in MATLAB. Here's a step-by-step guide:
- Load the necessary data: Prepare your time series data that you want to model using the GARCH model.
- Specify a GARCH model. For example:
Mdl = garch('Constant',0.01,'GARCH',0.7,'ARCH',0.25)
- To simulate future returns based on the GARCH model, you can use the ‘simulate’ function. You may choose to simulate from the model with or without using presample data.
rng default;
[Vw,Yw] = simulate(Mdl,100,'NumPaths',5,...
'E0',0.05,'V0',0.001);
Vw(1,:)
- You can create a probability distribution from the simulated returns using the ‘fitdist’ function. This function fits a parametric distribution to the data and returns an object that represents the estimated distribution. You can choose a distribution that best fits your data based on statistical criteria
pd = fitdist(Vw, 'Normal');
To learn more about simulating GARCH models, please refer to the below documentation:
I hope this helps!
