Column value conditional on previous value in a dataframe Python

I have a dataframe "bd" that looks like this:

    Unnamed: 0  timestamp   open    high    low close   volume  close_time  quote_av    trades  tb_base_av  tb_quote_av ignore  Ticker  log
0   0   17/04/2018  0.01000 0.02500 0.01000 0.02056 10026646.20 1.524010e+12    212822.90450    14612   3080879.33  65362.06898 0.0 ADABNB  0.720762
1   1   18/04/2018  0.02061 0.02227 0.02050 0.02131 6150235.16  1.524100e+12    131540.20910    8736    2932444.56  62649.93292 0.0 ADABNB  0.033400
2   2   19/04/2018  0.02126 0.02239 0.02125 0.02182 4029868.44  1.524180e+12    87958.85789 6894    1975139.34  43153.92312 0.0 ADABNB  0.026000
3   3   20/04/2018  0.02180 0.02429 0.02171 0.02400 4082134.58  1.524270e+12    94989.57750 7674    1489298.21  34675.98730 0.0 ADABNB  0.096144
4   4   21/04/2018  0.02400 0.02494 0.02031 0.02145 6363706.18  1.524360e+12    138161.60430    7733    3469179.07  74832.05245 0.0 ADABNB  -0.112329

I want the "Next Day" column to only be equal to log(-1) so the next day's log returns, if the Ticker Column is the same for both days. I tried creating a new column like this:

bd['Next Day'] = np.where(bd['Ticker'] == bd[['Ticker'](-1)], bd['log'].shift(-1)) 

But I get an error "list" object is not callable

Thank you.