Need help coding a monte carlo simulation.

I need to have a "random walk" data generated process. Then fit an ols regress of yt-yt-1 on yt-1, saving the t-statistic from the ols. I have the code for step one and two, I am having a hard time simulation all of this 10,000 times, while saving all 10,000 t-statistics, the code I have for the dgp and the ols are below:

 time=49;
 y=NaN*ones(time,1);
 y(1)=normrnd(0,1);
 sigma=1
 phi=1
 for t=1:time
   y(t+1)=phi*y(t)+normrnd(0,1);
end
yt=diff(y);
yt_1=y(1:time);
mdl = fitlm(yt_1,yt,'Intercept',false)