0

Can you please explain what the next GARCH results mean? where in these results can i know how well does the model forecast?

garch

user36632
  • 3

1 Answers1

0

ARCH is for Autoregressive Conditional Heteroskedasticity. The model fitted the mean autoregressive process AR(q=1) and the explanatory variables (X1-X8). Then the error term was squared and regressed on a constant and 1 lagged value ARCH(1) with the T statistic which needs to be compared to the critical value of Chi-square distribution with q degrees of freedom. If the statistic exceeds the critical value, then the variance in the error term is the function of the square of one step lagged error value and the number in Value column is its coefficient.

Germaniawerks
  • 1,077