# Change in variance time series

I am analysing a time series (stock returns) and I am trying to check whether variance in the second half of my sample is different from the first half. I assigned a period to the observations. Here is an example (not the real data, but this is what it looks like):

Period     return        Date
1    .02784243     1/8/2010
1    .01478848     1/15/2010
1    -.04267111    1/22/2010
2    -.011348      1/29/2010
2    -.09616897    2/5/2010 

I use STATA for the Levene's test, but my question is in the first place whether I can use time series in this way/with this method.

robvar return, by(Periode)

Summary of return
Periode         Mean            Std. Dev.        Freq.

1               .0000922          .0367802        261
2               .00006544        .02613092        261

Total           .00007882        .03187241        522

W0  = 10.8059198   df(1, 520)     Pr > F    =    0.00108013

W50 =  9.6731110   df(1, 520)     Pr > F    =    0.0019724

W10 =  9.8870904   df(1, 520)     Pr > F    =    0.00175953 

I am wondering whether using the Levene's test and breaking up the data like this is a valid method for time series? Anyone around here who can help me answer this question? If it isn't, is there another method (that is not too hard for a beginner?) Thanks in advance!!