The past decade has seen a rapid development of regularization techniques such as ridge regression,LASSO,SCAD,LARS and their extensions.However,these techniques have been developed mainly for circumstances where the observations are independent.In practice,many classes of interesting problems such as financial time series involve dependent data.In this talk,we describe extensions of the results of penalized methods for independent data to stationary multivariate time series.