mirror of
https://github.com/wassname/catalyst.git
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abstract eventwindow and trading calendar utility
This commit is contained in:
scottsanderson
@@ -249,9 +249,11 @@ def compare_by_dt_source_id(x,y):
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return -1
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elif x.source_id > y.source_id:
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return 1
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else:
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return 0
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#Alias for ease of use
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comp = compare_by_dt_source_id
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def to_dt(msg):
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return ndict({'dt': msg})
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+51
-27
@@ -5,9 +5,12 @@ from unittest2 import TestCase
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from zipline.utils.test_utils import setup_logger, teardown_logger
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import zipline.utils.factory as factory
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from zipline.finance.vwap import DailyVWAP, VWAPTransform
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from zipline.gens.tradegens import SpecificEquityTrades
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from zipline.gens.transform import StatefulTransform
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from zipline.gens.vwap import VWAP
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from zipline.gens.mavg import MovingAverage
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from zipline.finance.returns import ReturnsFromPriorClose
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from zipline.finance.movingaverage import MovingAverage
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from zipline.lines import SimulatedTrading
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from zipline.core.devsimulator import AddressAllocator
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@@ -25,7 +28,7 @@ class ZiplineWithTransformsTestCase(TestCase):
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'sid' : 133,
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'devel' : True
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}
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setup_logger(self, '/var/log/qexec/qexed.log')
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setup_logger(self, '/var/log/qexec/qexec.log')
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def tearDown(self):
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teardown_logger(self)
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@@ -48,25 +51,34 @@ class FinanceTransformsTestCase(TestCase):
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self.trading_environment = factory.create_trading_environment()
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setup_logger(self, '/var/log/qexec/qexec.log')
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def tearDown(self):
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self.log_handler.pop_application()
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def test_vwap(self):
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trade_history = factory.create_trade_history(
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133,
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[10.0, 10.0, 10.0, 11.0],
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[10.0, 10.0, 11.0, 11.0],
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[100, 100, 100, 300],
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timedelta(days=1),
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self.trading_environment
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)
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self.source = SpecificEquityTrades(event_list=trade_history)
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vwap = DailyVWAP(days=2)
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for trade in trade_history:
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vwap.update(trade)
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def tearDown(self):
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self.log_handler.pop_application()
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self.assertEqual(vwap.vwap, 10.75)
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def test_vwap(self):
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vwap = StatefulTransform(VWAP, timedelta(days = 2))
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transformed = list(vwap.transform(self.source))
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# Output values
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tnfm_vals = [message.tnfm_value for message in transformed]
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# "Hand calculated" values.
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expected = [(10.0 * 100) / 100.0,
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((10.0 * 100) + (10.0 * 100)) / (200.0),
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((10.0 * 100) + (10.0 * 100) + (11.0 * 100)) / (300.0),
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# First event should get droppped here.
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((10.0 * 100) + (11.0 * 100) + (11.0 * 300)) / (500.0)]
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# Output should match the expected.
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assert tnfm_vals == expected
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def test_returns(self):
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trade_history = factory.create_trade_history(
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@@ -86,17 +98,29 @@ class FinanceTransformsTestCase(TestCase):
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def test_moving_average(self):
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trade_history = factory.create_trade_history(
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133,
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[10.0, 10.0, 10.0, 11.0],
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[100, 100, 100, 300],
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timedelta(days=1),
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self.trading_environment
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)
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ma = MovingAverage(days=2)
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for trade in trade_history:
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ma.update(trade)
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self.assertEqual(ma.average, 10.5)
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mavg = StatefulTransform(
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MovingAverage,
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timedelta(days = 2),
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['price', 'volume']
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)
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transformed = list(mavg.transform(self.source))
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# Output values.
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tnfm_prices = [message.tnfm_value.price for message in transformed]
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tnfm_volumes = [message.tnfm_value.volume for message in transformed]
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# "Hand-calculated" values
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expected_prices = [((10.0) / 1.0),
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((10.0 + 10.0) / 2.0),
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((10.0 + 10.0 + 11.0) / 3.0),
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# First event should get dropped here.
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((10.0 + 11.0 + 11.0) / 3.0)]
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expected_volumes = [((100.0) / 1.0),
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((100.0 + 100.0) / 2.0),
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((100.0 + 100.0 + 100.0) / 3.0),
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# First event should get dropped here.
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((100.0 + 100.0 + 300.0) / 3.0)]
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assert tnfm_prices == expected_prices
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assert tnfm_volumes == expected_volumes
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+16
-18
@@ -1,26 +1,24 @@
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from collections import defaultdict
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from zipline.transforms.base import BaseTransform
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class ReturnsTransform(BaseTransform):
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def init(self, name):
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self.state = {}
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self.state['name'] = name
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self.by_sid = defaultdict(self._create)
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@property
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def get_id(self):
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return self.state['name']
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def transform(self, event):
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cur = self.by_sid[event.sid]
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cur.update(event)
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self.state['value'] = cur.returns
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return self.state
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class Returns(object):
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"""
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Class that maintains a dictionary from sids to the event
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representing the most recent closing price.
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"""
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def __init__(self, days == 1):
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self.days = days
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self.mapping = defaultdict(self._create)
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def update(self, event):
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"""
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Update and return the calculated returns for this event's sid.
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"""
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sid_returns = self.mapping[event.sid].update(event)
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return sid_returns
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def _create(self):
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return ReturnsFromPriorClose()
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return ReturnsFromPriorClose(days)
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class ReturnsFromPriorClose(object):
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"""
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@@ -3,13 +3,15 @@ Tools to generate trade events without a backing store. Useful for testing
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and zipline development
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"""
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import random
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import pytz
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from itertools import chain, cycle, ifilter, izip
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from datetime import datetime, timedelta
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from zipline.utils.factory import create_trade
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from zipline.gens.utils import hash_args
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def date_gen(start = datetime(2006, 6, 6, 12),
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def date_gen(start = datetime(2006, 6, 6, 12, tzinfo=pytz.utc),
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delta = timedelta(minutes = 1),
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count = 100):
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"""
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@@ -71,7 +73,7 @@ class SpecificEquityTrades(object):
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# Unpack config dictionary with default values.
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self.count = kwargs.get('count', 500)
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self.sids = kwargs.get('sids', [1, 2])
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self.start = kwargs.get('start', datetime(2012, 6, 6, 0))
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self.start = kwargs.get('start', datetime(2008, 6, 6, 15, tzinfo = pytz.utc))
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self.delta = kwargs.get('delta', timedelta(minutes = 1))
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# Default to None for event_list and filter.
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@@ -10,6 +10,7 @@ from numbers import Number
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from abc import ABCMeta, abstractmethod
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from zipline import ndict
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from zipline.utils.tradingcalendar import trading_days_between
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from zipline.gens.utils import assert_sort_unframe_protocol, \
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assert_transform_protocol, hash_args
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+1
-13
@@ -59,7 +59,7 @@ class VWAPEventWindow(EventWindow):
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Return the calculated vwap for this sid.
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"""
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# By convention, vwap is None if we have no events.
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if len(self.ticks) == 0
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if len(self.ticks) == 0:
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return None
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else:
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return (self.flux / self.totalvolume)
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@@ -68,15 +68,3 @@ class VWAPEventWindow(EventWindow):
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def assert_required_fields(self, event):
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assert isinstance(event.price, Number)
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assert isinstance(event.volume, Number)
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if __name__ == "__main__":
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from zipline.gens.tradegens import SpecificEquityTrades
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from zipline.gens.transform import StatefulTransform
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source = SpecificEquityTrades()
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vwap = StatefulTransform(VWAP, timedelta(minutes = 10))
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out = vwap.transform(source)
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@@ -95,7 +95,7 @@ HOLIDAYS = {
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'july_4th' : datetime(2008 , 7 , 4 ),
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'labor_day' : datetime(2008 , 9 , 1 ),
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'tgiving' : datetime(2008 , 11 , 27),
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'christmas' : datetime(2008 , 5 , 25),
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'christmas' : datetime(2008 , 12 , 25),
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}
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# Create a rule to recur every weekday starting today
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@@ -0,0 +1,333 @@
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import pytz
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from datetime import datetime, timedelta
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from dateutil import rrule
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from zipline.utils.date_utils import utcnow
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def market_opens(start, end, inclusive=False):
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"""
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Returns all market opens between the start date and the end date.
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Must use utc-stamped datetimes.
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"""
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return opens.between(start, end, inc=inclusive)
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def market_closes(start, end, inclusive=False):
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"""
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Returns all market closes between the start date and the end date.
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Must use utc-stamped datetimes.
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"""
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return closes.between(start, end, inc=inclusive)
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def trading_days_between(start, end):
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"""
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Calculate the number of "complete" trading days between two
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events. We define this as the number of market opens that
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occurred between start and end, with the caveat that we subtract 1
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from this total if end falls on the same day as the last market
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open and end occurs earlier in its own day than start. This
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reflects the fact that we haven't completed a full day
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corresponding to the last market open.
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Examples:
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1.)
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start = Tuesday, Aug 7, 2012, 1:00 pm
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end = Wednesday, Aug 8, 2012, 1:30 pm
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There is one market open between these dates, on the morning of
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Wednesday the 8th. This falls on the same calendar day as end,
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but end is later in the day than start, so we count this as a full
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day. The correct output is 1.
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2.)
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start = Tuesday, Aug 7, 2012, 1:30 pm
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end = Wednesday, Aug 8, 2012, 1:00 pm
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There is one market open between these dayes, on the morning of
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Wednesday the 8th. This falls on the same calendar day as end,
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and end is earlier in the day than start, so we do not count this
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day as completed. The correct output is 0.
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3.)
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start = Tuesday, Aug 7, 2012, 1:00 pm
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end = Saturday, Aug 11, 2012, 1:30 pm
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There are 3 market opens between these dates, occurring on
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Wednesday, Thursday, and Friday. The last open is not on
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the same day as end, so we simply return 3
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4.)
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start = Tuesday, Aug 7, 2012, 1:30 pm
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end = Monday, Aug, 13, 2012, 1:00 pm
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There are 4 market opens between these dates, occurring on
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Wednesday, Thursday, Friday, and the following Monday. The
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last open occurs on the same calendar day as end, and end
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is earlier in the day than start, so we do not count the
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last market day as completed. The correct output is 3 days.
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"""
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# Calculate the number of opens between the events.
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opens = (market_opens(start, end))
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days_between = len(opens)
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if days_between == 0:
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return days_between
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# If end falls on the same day as an open, subtract 1 from the
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# total if end is earlier in its respective day than start.
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last_open = opens[-1]
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if last_open.date() == end.date() and earlier_in_day(end, start):
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days_between -=1
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return days_between
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def earlier_in_day(d1, d2):
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"""
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Return true if d1 falls earlier in its own day than d2.
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"""
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d1 = d1.replace(year = d2.year, day = d2.day)
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return d1 < d2
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WEEKDAYS = [rrule.MO, rrule.TU, rrule.WE, rrule.TH, rrule.FR]
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# Recurrence rule that generates all market opens since Jan 1, 1970.
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# This does not exclude holidays.
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market_opens_with_holidays = rrule.rrule(
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rrule.DAILY,
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byweekday=WEEKDAYS,
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byhour = 14,
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byminute = 30,
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cache = True,
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dtstart=datetime(1970, 1, 1, tzinfo = pytz.utc),
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)
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# Recurrence rule that generates all market closes since Jan 1, 1970.
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# This does not exclude holidays.
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market_closes_with_holidays = rrule.rrule(
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rrule.DAILY,
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byweekday=WEEKDAYS,
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byhour = 21,
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byminute = 0,
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cache = True,
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dtstart=datetime(1970, 1, 1, tzinfo = pytz.utc),
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)
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# Recurrence rules for excluding the market open/close on new years.
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new_years_opens = rrule.rrule(
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rrule.MONTHLY,
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byyearday = 1,
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byhour = 14,
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byminute = 30,
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cache = True,
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dtstart = datetime(1970, 1,1,tzinfo = pytz.utc)
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)
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new_years_closes = rrule.rrule(
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rrule.MONTHLY,
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byyearday = 1,
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byhour = 21,
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byminute = 0,
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cache = True,
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dtstart = datetime(1970, 1,1,tzinfo = pytz.utc)
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)
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# Recurrence rules for excluding MLK day. It is always the third
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# monday in January.
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mlk_opens = rrule.rrule(
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rrule.MONTHLY,
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bymonth = 1,
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byweekday = (rrule.MO(3)),
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byhour = 14,
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byminute = 30,
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cache = True,
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dtstart = datetime(1970, 1,1,tzinfo = pytz.utc)
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)
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mlk_closes = rrule.rrule(
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rrule.MONTHLY,
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bymonth = 1,
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byweekday = (rrule.MO(+3)),
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byhour = 21,
|
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byminute = 0,
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||||
cache = True,
|
||||
dtstart = datetime(1970, 1,1,tzinfo = pytz.utc)
|
||||
)
|
||||
|
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# Recurrence rules for generating the market open/close for
|
||||
# presidents' day. Presidents' day always occurs on the third monday
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# of February.
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presidents_day_opens = rrule.rrule(
|
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rrule.MONTHLY,
|
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bymonth = 2,
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byweekday = (rrule.MO(3)),
|
||||
byhour = 14,
|
||||
byminute = 30,
|
||||
cache = True,
|
||||
dtstart = datetime(1970, 1,1,tzinfo = pytz.utc)
|
||||
)
|
||||
presidents_day_closes = rrule.rrule(
|
||||
rrule.MONTHLY,
|
||||
bymonth = 2,
|
||||
byweekday = (rrule.MO(3)),
|
||||
byhour = 21,
|
||||
byminute = 0,
|
||||
cache = True,
|
||||
dtstart = datetime(1970, 1,1,tzinfo = pytz.utc)
|
||||
)
|
||||
|
||||
# Recurrence rules for generating the market open/close for good
|
||||
# friday. Good friday always falls 2 days before easter, which
|
||||
# thankfully is a built-in refernce in this module.
|
||||
good_friday_opens = rrule.rrule(
|
||||
rrule.DAILY,
|
||||
byeaster = -2,
|
||||
byhour = 14,
|
||||
byminute = 30,
|
||||
cache = True,
|
||||
dtstart = datetime(1970, 1,1,tzinfo = pytz.utc)
|
||||
)
|
||||
good_friday_closes = rrule.rrule(
|
||||
rrule.DAILY,
|
||||
byeaster = -2,
|
||||
byhour = 21,
|
||||
byminute = 0,
|
||||
cache = True,
|
||||
dtstart = datetime(1970, 1,1,tzinfo = pytz.utc)
|
||||
)
|
||||
|
||||
# Recurrence rules for generating the market open/close for memorial
|
||||
# day. Memorial day always occurs on the last monday of May.
|
||||
memorial_day_opens = rrule.rrule(
|
||||
rrule.MONTHLY,
|
||||
bymonth = 5,
|
||||
byweekday = (rrule.MO(-1)),
|
||||
byhour = 14,
|
||||
byminute = 30,
|
||||
cache = True,
|
||||
dtstart = datetime(1970, 1,1,tzinfo = pytz.utc)
|
||||
)
|
||||
memorial_day_closes = rrule.rrule(
|
||||
rrule.MONTHLY,
|
||||
bymonth = 5,
|
||||
byweekday = (rrule.MO(-1)),
|
||||
byhour = 21,
|
||||
byminute = 0,
|
||||
cache = True,
|
||||
dtstart = datetime(1970, 1,1,tzinfo = pytz.utc)
|
||||
)
|
||||
|
||||
# Recurrence rules for generating the market open/close for July 4th.
|
||||
july_4th_opens = rrule.rrule(
|
||||
rrule.MONTHLY,
|
||||
bymonth = 6,
|
||||
bymonthday = 4,
|
||||
byhour = 14,
|
||||
byminute = 30,
|
||||
cache = True,
|
||||
dtstart = datetime(1970, 1,1,tzinfo = pytz.utc)
|
||||
)
|
||||
july_4th_closes = rrule.rrule(
|
||||
rrule.MONTHLY,
|
||||
bymonth = 6,
|
||||
bymonthday = 4,
|
||||
byhour = 21,
|
||||
byminute = 0,
|
||||
cache = True,
|
||||
dtstart = datetime(1970, 1,1,tzinfo = pytz.utc)
|
||||
)
|
||||
|
||||
# Recurrence rule for generating the market open/close for labor day.
|
||||
# Labor day is always the first monday of September.
|
||||
labor_day_opens = rrule.rrule(
|
||||
rrule.MONTHLY,
|
||||
bymonth = 9,
|
||||
byweekday = (rrule.MO(1)),
|
||||
byhour = 14,
|
||||
byminute = 30,
|
||||
cache = True,
|
||||
dtstart = datetime(1970, 1,1,tzinfo = pytz.utc)
|
||||
)
|
||||
labor_day_closes = rrule.rrule(
|
||||
rrule.MONTHLY,
|
||||
bymonth = 9,
|
||||
byweekday = (rrule.MO(1)),
|
||||
byhour = 21,
|
||||
byminute = 0,
|
||||
cache = True,
|
||||
dtstart = datetime(1970, 1,1,tzinfo = pytz.utc)
|
||||
)
|
||||
|
||||
# Recurrence rule for generating the market open/close for
|
||||
# thanksgiving. Thanksgiving always falls on the fourth thursday in
|
||||
# November. (Who decides how these holidays work!?!)
|
||||
thanksgiving_opens = rrule.rrule(
|
||||
rrule.MONTHLY,
|
||||
bymonth = 11,
|
||||
byweekday = (rrule.TH(-1)),
|
||||
byhour = 14,
|
||||
byminute = 30,
|
||||
cache = True,
|
||||
dtstart = datetime(1970, 1,1,tzinfo = pytz.utc)
|
||||
)
|
||||
thanksgiving_closes = rrule.rrule(
|
||||
rrule.MONTHLY,
|
||||
bymonth = 11,
|
||||
byweekday = (rrule.TH(-1)),
|
||||
byhour = 21,
|
||||
byminute = 0,
|
||||
cache = True,
|
||||
dtstart = datetime(1970, 1,1,tzinfo = pytz.utc)
|
||||
)
|
||||
|
||||
# Recurrence relation for generating the market open/close for
|
||||
# christmas. Christmas always occurs on december 25th.
|
||||
|
||||
christmas_opens = rrule.rrule(
|
||||
rrule.MONTHLY,
|
||||
bymonth = 12,
|
||||
bymonthday = 25,
|
||||
byhour = 14,
|
||||
byminute = 30,
|
||||
cache = True,
|
||||
dtstart = datetime(1970, 1,1,tzinfo = pytz.utc)
|
||||
)
|
||||
christmas_closes = rrule.rrule(
|
||||
rrule.MONTHLY,
|
||||
bymonth = 12,
|
||||
bymonthday = 25,
|
||||
byhour = 21,
|
||||
byminute = 0,
|
||||
cache = True,
|
||||
dtstart = datetime(1970, 1,1,tzinfo = pytz.utc)
|
||||
)
|
||||
# All NYSE observed holidays.
|
||||
holiday_opens = [
|
||||
new_years_opens,
|
||||
mlk_opens,
|
||||
presidents_day_opens,
|
||||
good_friday_opens,
|
||||
memorial_day_opens,
|
||||
july_4th_opens,
|
||||
labor_day_opens,
|
||||
thanksgiving_opens,
|
||||
christmas_opens
|
||||
]
|
||||
holiday_closes = [
|
||||
new_years_closes,
|
||||
mlk_closes,
|
||||
presidents_day_closes,
|
||||
good_friday_closes,
|
||||
memorial_day_closes,
|
||||
july_4th_closes,
|
||||
labor_day_closes,
|
||||
thanksgiving_closes,
|
||||
christmas_closes
|
||||
]
|
||||
|
||||
# Valid market opens are given by all market opens minus holidays.
|
||||
opens = rrule.rruleset()
|
||||
opens.rrule(market_opens_with_holidays)
|
||||
for holiday_rule in holiday_opens:
|
||||
opens.exrule(holiday_rule)
|
||||
|
||||
closes = rrule.rruleset()
|
||||
closes.rrule(market_closes_with_holidays)
|
||||
for holiday_rule in holiday_closes:
|
||||
closes.exrule(holiday_rule)
|
||||
Reference in New Issue
Block a user