def evaluate(strategy, type, files):
strategy.clear()
data = MarketData()
ts = TradingSystem()
for instrument, file in files.items():
ts.createBook(instrument)
ts.subscribe(instrument, strategy)
if type == MarketData.TICK:
data.loadBBGTick(file, instrument)
elif type == MarketData.HIST:
data.loadYAHOOHist(file, instrument)
elif type == MarketData.INTR:
data.loadBBGIntr(file, instrument)
data.run(ts)
ts.submit(strategy.id, strategy.close())
return strategy.summary()
def evaluateMult(strategies, instruments_list, var):
#print('types: ', types)
#print('files: ', files)
#print('strategies: ', strategies)
if (len(strategies) != len(instruments_list)):
return (
"ERROR! - evaluateMult arguments require the same number of items")
for s in strategies:
s.clear()
data = MarketData()
ts = TradingSystem()
ts.createRisk(var)
for i in range(0, len(strategies)):
for instrument in instruments_list[i]:
ts.createBook(instrument)
ts.subscribe(instrument, strategies[i])
'''
if(types[i] == MarketData.TICK):
data.loadBBGTick(file, instrument)
if(types[i] == MarketData.HIST):
data.loadYAHOOHist(file, instrument)
if(types[i] == MarketData.INTR):
data.loadBBGIntr(file, instrument)
'''
#data.loadBBGTick('2018-03-07.csv', "PETR4")
data.loadFTP()
data.run(ts)
summary = []
for strategy in strategies:
print("strategy")
ts.submit(strategy.id, strategy.close())
summary.append(strategy.summary(name=strategy.name))
return summary
def evaluate(strategy, type, files, *, has_config=False):
strategy.clear()
data = MarketData()
ts = TradingSystem()
for instrument, file_data in files.items():
ts.createBook(instrument)
ts.subscribe(instrument, strategy)
if type == MarketData.TICK:
data.loadBBGTick(file_data, instrument)
elif type == MarketData.HIST:
data.loadYAHOOHist(file_data, instrument)
elif type == MarketData.INTR:
if has_config:
data.loadBBGIntr(file_data[0],
instrument,
separator=file_data[1],
date_format=file_data[2])
else:
data.loadBBGIntr(file_data, instrument)
data.run(ts)
ts.submit(strategy.id, strategy.close())
return strategy.summary()
},
'close': {
'type': 'float'
},
'volume': {
'type': 'float'
},
'product_id': {
'type': 'keyword'
}
}
}
}
es.indices.create(index=index, body=es_settings)
md = MarketData(exchange)
products = ['BTC-USD']
granularities = md.available_granularity().values
start = datetime.datetime(year=2019, month=1, day=1)
end = datetime.datetime(year=2019, month=6, day=1)
for granularity in granularities:
slices = TimeSlice.time_slice(start, end, granularity)
for product_id in products:
for _start, _end in slices:
try:
Elasticsearch.bulk(
es,
md.es_candle_generator(index, product_id, _start, _end,
granularity))
except InvalidArgument as err: