Why specify intiial variance when estimating a conditional mean and variance model?

In many MATLAB examples where the estimate function is used to estimate a conditional mean and variance model, the examples usual give an initial value for the constant of the conditional variance model:

load Data_EquityIdx

nasdaq = Dataset.NASDAQ;

r = price2ret(nasdaq);

N = length(r);

model = arima('ARLags',1,'Variance',garch(1,1),... 'Distribution','t');

fit = estimate(model,r,'Variance0',{'Constant0',0.001});

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I was wondering why, if at all, this initial value is necessary?