mirror of
https://github.com/wassname/catalyst.git
synced 2026-07-15 11:22:18 +08:00
131 lines
3.8 KiB
Python
131 lines
3.8 KiB
Python
import datetime
|
|
import pytz
|
|
import msgpack
|
|
import random
|
|
import zipline.util as qutil
|
|
import zipline.finance.risk as risk
|
|
import zipline.protocol as zp
|
|
|
|
def load_market_data():
|
|
fp_bm = open("./zipline/test/benchmark.msgpack", "rb")
|
|
bm_map = msgpack.loads(fp_bm.read())
|
|
bm_returns = []
|
|
for epoch, returns in bm_map.iteritems():
|
|
event_dt = datetime.datetime.fromtimestamp(epoch)
|
|
event_dt = event_dt.replace(
|
|
hour=0,
|
|
minute=0,
|
|
second=0,
|
|
tzinfo=pytz.utc
|
|
)
|
|
|
|
daily_return = risk.DailyReturn(date=event_dt, returns=returns)
|
|
bm_returns.append(daily_return)
|
|
bm_returns = sorted(bm_returns, key=lambda(x): x.date)
|
|
fp_tr = open("./zipline/test/treasury_curves.msgpack", "rb")
|
|
tr_map = msgpack.loads(fp_tr.read())
|
|
tr_curves = {}
|
|
for epoch, curve in tr_map.iteritems():
|
|
tr_dt = datetime.datetime.fromtimestamp(epoch)
|
|
tr_dt = tr_dt.replace(hour=0, minute=0, second=0, tzinfo=pytz.utc)
|
|
tr_curves[tr_dt] = curve
|
|
|
|
return bm_returns, tr_curves
|
|
|
|
|
|
def create_trade(sid, price, amount, datetime):
|
|
row = zp.namedict({
|
|
'source_id' : "test_factory",
|
|
'type' : zp.DATASOURCE_TYPE.TRADE,
|
|
'sid' : sid,
|
|
'dt' : datetime,
|
|
'price' : price,
|
|
'volume' : amount
|
|
})
|
|
return row
|
|
|
|
def create_trade_history(sid, prices, amounts, start_time, interval, trading_calendar):
|
|
i = 0
|
|
trades = []
|
|
current = start_time.replace(tzinfo = pytz.utc)
|
|
|
|
for price, amount in zip(prices, amounts):
|
|
|
|
if(trading_calendar.is_trading_day(current)):
|
|
trade = create_trade(sid, price, amount, current)
|
|
trades.append(trade)
|
|
|
|
current = current + interval
|
|
else:
|
|
current = current + datetime.timedelta(days=1)
|
|
|
|
return trades
|
|
|
|
def create_txn(sid, price, amount, datetime, btrid=None):
|
|
txn = zp.namedict({
|
|
'sid':sid,
|
|
'amount':amount,
|
|
'dt':datetime,
|
|
'price':price,
|
|
})
|
|
return txn
|
|
|
|
def create_txn_history(sid, priceList, amtList, startTime, interval, trading_calendar):
|
|
txns = []
|
|
current = startTime
|
|
|
|
for price, amount in zip(priceList, amtList):
|
|
|
|
if trading_calendar.is_trading_day(current):
|
|
txns.append(create_txn(sid, price, amount, current))
|
|
current = current + interval
|
|
|
|
else:
|
|
current = current + datetime.timedelta(days=1)
|
|
|
|
return txns
|
|
|
|
|
|
def create_returns(daycount, start, trading_calendar):
|
|
i = 0
|
|
test_range = []
|
|
current = start.replace(tzinfo=pytz.utc)
|
|
one_day = datetime.timedelta(days = 1)
|
|
while i < daycount:
|
|
i += 1
|
|
r = risk.DailyReturn(current, random.random())
|
|
test_range.append(r)
|
|
current = current + one_day
|
|
return [ x for x in test_range if(trading_calendar.is_trading_day(x.date)) ]
|
|
|
|
|
|
def create_returns_from_range(start, end, trading_calendar):
|
|
current = start.replace(tzinfo=pytz.utc)
|
|
end = end.replace(tzinfo=pytz.utc)
|
|
one_day = datetime.timedelta(days = 1)
|
|
test_range = []
|
|
i = 0
|
|
while current <= end:
|
|
current = current + one_day
|
|
if(not trading_calendar.is_trading_day(current)):
|
|
continue
|
|
r = risk.DailyReturn(current, random.random())
|
|
i += 1
|
|
test_range.append(r)
|
|
|
|
return test_range
|
|
|
|
def create_returns_from_list(returns, start, trading_calendar):
|
|
current = start.replace(tzinfo=pytz.utc)
|
|
one_day = datetime.timedelta(days = 1)
|
|
test_range = []
|
|
i = 0
|
|
while len(test_range) < len(returns):
|
|
if(trading_calendar.is_trading_day(current)):
|
|
r = risk.DailyReturn(current, returns[i])
|
|
i += 1
|
|
test_range.append(r)
|
|
current = current + one_day
|
|
return sorted(test_range, key=lambda(x):x.date)
|
|
|