Predictability_of_E​xchange_final code

The code snippet defines a new GARCH(1,1) model (Mdl) with specific properties. The model has an offset of NaN, one GARCH lag, and one

he code begins by simulating paths for the GARCH(1,1) model and plotting the conditional variances and returns. It then loads financial data, calculates the returns, and estimates the GARCH(1,1) model using the obtained returns.

Next, the code generates a forecast for the conditional variance based on the estimated model and calculates the theoretical conditional variance using the model parameters. The results are plotted, comparing the forecasted and theoretical conditional variances.

Lastly, a new GARCH(1,1) model is defined with specific properties, including an offset, one GARCH lag, and one ARCH lag. The model uses a Gaussian distribution for the data.

This code snippet provides a starting point for GARCH modeling in MATLAB, allowing users to estimate and forecast volatility in financial time series. It can be customized and expanded to suit specific requirements, such as incorporating different distributions or adjusting model parameters.

MATLAB offers comprehensive functionalities and tools for financial modeling and analysis, making it a powerful platform for working with financial data and implementing sophisticated econometric models.