def _getBenchmarkData(self, indexID, startTimeStamp, endTimeStamp):
self.logger.info(
"Starting load benchmark {0:s} daily bar data from DX data center..."
.format(indexID))
indexIDComp = indexID.split('.')
if indexIDComp[1] == 'zicn':
indexData = api.GetIndexBarEOD(indexIDComp[0],
startDate=startTimeStamp,
endDate=endTimeStamp,
forceUpdate=self.forceUpdate)
elif indexIDComp[1] == 'ccfx' or indexIDComp[
1] == 'xzce' or indexIDComp[1] == 'xdce' or indexIDComp[
1] == 'xsge':
indexData = api.GetFutureBarEODContinuing(
indexIDComp[0],
startDate=startTimeStamp,
endDate=endTimeStamp,
forceUpdate=self.forceUpdate)
elif indexIDComp[1] == 'xshg' or indexIDComp[1] == 'xshe':
indexData = api.GetEquityBarEOD(indexIDComp[0],
startDate=startTimeStamp,
endDate=endTimeStamp,
forceUpdate=self.forceUpdate,
baseDate='end')
indexData = indexData[['closePrice']]
indexData.columns = ['close']
indexData.index = pd.to_datetime(indexData.index.date)
indexData['return'] = np.log(indexData['close'] /
indexData['close'].shift(1))
indexData = indexData.dropna()
self.benchmarkData = indexData
self.logger.info("Benchmark data loading finished!")
def get_equity_eod(instruments, start_date, end_date):
if Settings.data_source == DataSource.DXDataCenter:
data = api.GetEquityBarEOD(instrumentIDList=instruments,
startDate=start_date,
endDate=end_date,
field='closePrice',
instrumentIDasCol=True,
baseDate='end')
elif Settings.data_source == DataSource.DataYes:
import os
import tushare as ts
try:
ts.set_token(os.environ['DATAYES_TOKEN'])
except KeyError:
raise
mt = ts.Market()
res = []
for ins in instruments:
data = mt.MktEqud(ticker=ins,
beginDate=start_date.replace('-', ''),
endDate=end_date.replace('-', ''),
field='tradeDate,ticker,closePrice')
res.append(data)
data = pd.concat(res)
data['tradeDate'] = pd.to_datetime(data['tradeDate'], format='%Y-%m-%d')
data['ticker'] = data['ticker'].apply(lambda x: '{0:06d}'.format(x))
data.set_index(['tradeDate', 'ticker'], inplace=True, verify_integrity=True)
data = data.unstack(level=-1)
return data
turnOverRate.name = 'turnover_rate'
turnOverRate.index.name = 'date'
return pd.DataFrame(turnOverRate)
@plotting_context
def createAllTearSheet(positions, transcations=None, prices=None, returns=None, benchmark=None, turn_over=None, tc_cost=0., freq='M', plot=True):
perf_metric, perf_df, rollingRisk = createPerformanceTearSheet(prices=prices,
returns=returns,
benchmark=benchmark,
turn_over=turn_over,
tc_cost=tc_cost,
plot=plot)
createPostionTearSheet(positions=positions, plot=plot, freq=freq, convert='raw')
if transcations is not None or turn_over is not None:
createTranscationTearSheet(positions=positions, transactions=transcations, turn_over=turn_over, freq=freq, plot=plot)
return perf_metric, perf_df, rollingRisk
if __name__ == "__main__":
from DataAPI import api
from VisualPortfolio import Settings
from VisualPortfolio import DataSource
Settings.set_source(DataSource.DXDataCenter)
data = api.GetEquityBarEOD('600000', '2012-01-01', '2015-10-01')
createPerformanceTearSheet(data['closePrice'], benchmark='000300.zicn')
plt.show()