It doesn't look like MATLAB supports generating auto-regressive models that have some lags of 0. It does support any number or combination of positive lags. If you think about it, it doesnt make much sense to perform an auto-regression without lags either.
It looks like you are trying to estimate some 3 factor model. And it looks like x(t) are your factors and r(t) is your returns. Please correct me if I am wrong. I think it would be simpler to just generate two separate models. One normal regression for r(t) and one auto-regressive one for x(t). I will show you how to generate the VAR for x(t). Of course, I am assuming that x(t) is not dependent on r(t).
MATLAB has a neat function called varm in the econometrics toolbox. To generate the auto-regressive model, you would use the following commands. (change your data to be comma separated and this should work)
data = importdata('data.txt')
data = data.data;
x = data(:, 3:5);
model = varm(3, 1);
[model, EstSE,logL,E] = estimate(model, x)
The first line generates a skeleton vector auto-regressive model that is modeling 3 time series with one lag at t-1. The second line takes that model and your training data and then populates the model. the member AR is a cell that holds a matrix for each time lag which in this case, is B. The model also contains your covariance matrix and EstSE stands for estimate standard error.
