def strategy_bollinger(d_data, ldt_timestamps):
ls_symbols = list(d_data['close'].keys())
df_index_bollinger = BollingerBands.bollinger_bands(d_data['close'], ldt_timestamps,
ls_symbols=ls_symbols)
mkt_benchmark = Analyze.get_mktBenchmark(ldt_timestamps)
mkt_bollinger = BollingerBands.bollinger_bands(mkt_benchmark, ldt_timestamps)
df_events = copy.deepcopy(df_index_bollinger) * np.NAN
for i in range(1,len(ldt_timestamps)):
boll_today = df_index_bollinger.ix[ldt_timestamps[i]]
boll_yest = df_index_bollinger.ix[ldt_timestamps[i-1]]
for c_sym in ls_symbols:
if boll_today[c_sym] <= -2.0 and boll_yest[c_sym] > -2.0 and \
mkt_bollinger['$SPX'].ix[ldt_timestamps[i]] >= 1.0:
df_events[c_sym].ix[ldt_timestamps[i]] =1
return df_events
