INNER CODE UNIT · Python

longs

dmarienko/QuantTradingResearch · models/helpers.py:137

    shorts, longs = z >= Z_entry, z <= -Z_entry
    shorts_exits, longs_exits = ((z <= -Z_exit) & (z > -Z_entry)), ((z >= Z_exit) & (z < Z_entry))
    
    # we need to normalize portfolio weights
    b_a_w = kfm.model.b.div(kfm.model.b.sum(axis=1), axis=0)
    
    signals = pd.concat((
         -b_a_w[longs],  b_a_w[longs_exits] * 0, 
          b_a_w[shorts], b_a_w[shorts_exits] * 0,
    ), axis=0).sort_index()

    # take opposite position on Index
    signals['^RUI'] = 0
    signals.loc[longs, '^RUI'] = +1
    signals.loc[shorts, '^RUI'] = -1
    
    # we will trade 1000 shares per stock and execute on daily close
    signals = shift_signals(np.floor(traded_size * signals), hours=15, minutes=59)

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