In [11]: df
Out[11]:
                    A    B
2000-01-01  -0.182994    0
2000-01-02   1.290203    0
2000-01-03   0.245229    0
2000-01-08  -1.230742    0
2000-01-09   0.534939    0
2000-01-10   1.324027    0

for idx,row in df.iterrows():
    if df["A"][idx]<-1:
        df["B"][idx] = -1
    elif df["A"][idx]>1:
        df["B"][idx] = 1
    else:
        df["B"][idx] = df["B"][idx-1]

In [38]: df = DataFrame(randn(10,2),columns=list('AB'))

In [39]: df['B'] = np.nan

In [40]: df.loc[df.A<-1,'B'] = -1

In [41]: df.loc[df.A>1,'B'] = 1

In [42]: df.ffill()
Out[42]:
          A  B
0 -1.186808 -1
1 -0.095587 -1
2 -1.921372 -1
3 -0.772836 -1
4  0.016883 -1
5  0.350778 -1
6  0.165055 -1
7  1.101561  1
8 -0.346786  1
9 -0.186263  1