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Merge remote-tracking branch 'origin/algohost' into dataflow

Browse Source 
Conflicts:
	zipline/protocol.py
This commit is contained in:
Stephen Diehl
2012-03-14 18:35:07 -04:00
parent fafbc7d3c1 98c1312f16
commit 61adcf44c2
6 changed files with 114 additions and 69 deletions
Download Patch File Download Diff File Expand all files Collapse all files
zipline/finance/performance.py
+7 -3
View File
@@ -1,6 +1,7 @@
import datetime
import pytz
import math
import pandas
from zmq.core.poll import select
@@ -123,7 +124,10 @@ class PerformanceTracker():
def update(self, event_frame):
for dt, event_series in event_frame.iteritems():
self.process_event(event_series)
data = {}
data.update(event_series)
event = zp.namedict(data)
self.process_event(event)
def process_event(self, event):
qutil.LOGGER.debug("series is " + str(event))
@@ -131,7 +135,7 @@ class PerformanceTracker():
if(event.dt >= self.market_close):
self.handle_market_close()
if event.TRANSACTION != None:
if not pandas.isnull(event.TRANSACTION):
self.txn_count += 1
self.cumulative_performance.execute_transaction(event.TRANSACTION)
self.todays_performance.execute_transaction(event.TRANSACTION)
@@ -238,7 +242,7 @@ class Position():
self.amount = self.amount + txn.amount
def currentValue(self):
return self.amount * self.last_sale
return self.amount * self.last_sale_price
def __repr__(self):
zipline/finance/trading.py
+12 -6
View File
@@ -48,6 +48,7 @@ class TradeSimulationClient(qmsg.Component):
if msg == str(zp.CONTROL_PROTOCOL.DONE):
qutil.LOGGER.info("Client is DONE!")
self.run_callbacks()
self.signal_done()
return
@@ -61,9 +62,9 @@ class TradeSimulationClient(qmsg.Component):
#mark the start time for client's processing of this event.
event_start = datetime.datetime.utcnow()
self.queue_event(event)
for cb in self.event_callbacks:
if(event.dt >= self.current_dt):
cb(self.get_frame())
if event.dt >= self.current_dt:
self.run_callbacks()
#update time based on receipt of the order
self.last_iteration_duration = datetime.datetime.utcnow() - event_start
@@ -72,6 +73,11 @@ class TradeSimulationClient(qmsg.Component):
#signal done to order source.
self.order_socket.send(str(zp.ORDER_PROTOCOL.BREAK))
def run_callbacks(self):
frame = self.get_frame()
for cb in self.event_callbacks:
cb(frame)
def connect_order(self):
return self.connect_push_socket(self.addresses['order_address'])
@@ -91,11 +97,11 @@ class TradeSimulationClient(qmsg.Component):
def queue_event(self, event):
if self.event_queue == None:
self.event_queue = {}
self.event_queue[event.dt] = event.as_series()
series = event.as_series()
self.event_queue[event.dt] = series
def get_frame(self):
sorted_dates = sorted(self.event_queue.keys())
frame = pandas.DataFrame(self.event_queue, index=sorted_dates)
frame = pandas.DataFrame(self.event_queue)
self.event_queue = None
return frame
zipline/test/client.py
+14 -10
View File
@@ -70,19 +70,23 @@ class TestAlgorithm():
def __init__(self, sid, amount, order_count, trading_client):
self.trading_client = trading_client
self.trading_client.add_event_callback(self.handle_event)
self.trading_client.add_event_callback(self.handle_frame)
self.count = order_count
self.sid = sid
self.amount = amount
self.incr = 0
self.done = False
def handle_event(self, event):
#place an order for 100 shares of sid:133
if self.incr < self.count:
if event.source_id != zp.FINANCE_COMPONENT.ORDER_SOURCE:
self.trading_client.order(self.sid, self.amount)
self.incr += 1
elif not self.done:
self.trading_client.signal_order_done()
self.done = True
def handle_frame(self, frame):
for dt, s in frame.iteritems():
data = {}
data.update(s)
event = zp.namedict(data)
#place an order for 100 shares of sid:133
if self.incr < self.count:
if event.source_id != zp.FINANCE_COMPONENT.ORDER_SOURCE:
self.trading_client.order(self.sid, self.amount)
self.incr += 1
elif not self.done:
self.trading_client.signal_order_done()
self.done = True
zipline/test/test_finance.py
+2 -2
View File
@@ -340,8 +340,8 @@ class FinanceTestCase(TestCase):
self.assertEqual(
transaction_sim.txn_count,
perf_tracker.txn_count,
"The perf tracker should handle the same number of transactions as\
as the simulator emits."
"The perf tracker should handle the same number of transactions \
as the simulator emits."
)
self.assertEqual(
zipline/test/test_perf_tracking.py
+68 -34
View File
@@ -2,11 +2,14 @@ import unittest
import copy
import random
import datetime
import pytz
import zipline.test.factory as factory
import zipline.util as qutil
import zipline.finance.performance as perf
import zipline.finance.risk as risk
import zipline.protocol as zp
from zipline.finance.trading import TradeSimulationClient
class PerformanceTestCase(unittest.TestCase):
def setUp(self):
@@ -34,8 +37,8 @@ class PerformanceTestCase(unittest.TestCase):
def test_long_position(self):
"""
verify that the performance period calculates properly for a \
single buy transaction
verify that the performance period calculates properly for a
single buy transaction
"""
#post some trades in the market
trades = factory.create_trade_history(
@@ -85,12 +88,12 @@ single buy transaction
)
self.assertEqual(
pp.positions[1].last_sale,
pp.positions[1].last_sale_price,
trades[-1]['price'],
"last sale should be same as last trade. \
expected {exp} actual {act}".format(
exp=trades[-1]['price'],
act=pp.positions[1].last_sale
act=pp.positions[1].last_sale_price
)
)
@@ -155,7 +158,7 @@ single short-sale transaction"""
)
self.assertEqual(
pp.positions[1].last_sale,
pp.positions[1].last_sale_price,
trades_1[-1]['price'],
"last sale should be price of last trade"
)
@@ -224,7 +227,7 @@ single short-sale transaction"""
)
self.assertEqual(
pp2.positions[1].last_sale,
pp2.positions[1].last_sale_price,
trades_2[-1].price,
"last sale should be price of last trade"
)
@@ -285,7 +288,7 @@ cost of sole txn in test"
)
self.assertEqual(
ppTotal.positions[1].last_sale,
ppTotal.positions[1].last_sale_price,
trades_2[-1].price,
"last sale should be price of last trade"
)
@@ -367,7 +370,7 @@ trade after cover"""
)
self.assertEqual(
pp.positions[1].last_sale,
pp.positions[1].last_sale_price,
trades[-1].price,
"last sale should be price of last trade"
)
@@ -415,10 +418,10 @@ shares in position"
pp.calculate_performance()
self.assertEqual(
pp.positions[1].last_sale,
pp.positions[1].last_sale_price,
trades[-1].price,
"should have a last sale of 12, got {val}".format(
val=pp.positions[1].last_sale
val=pp.positions[1].last_sale_price
)
)
@@ -456,9 +459,9 @@ shares in position"
pp2.calculate_performance()
self.assertEqual(
pp2.positions[1].last_sale,
pp2.positions[1].last_sale_price,
10,
"should have a last sale of 10, was {val}".format(val=pp2.positions[1].last_sale)
"should have a last sale of 10, was {val}".format(val=pp2.positions[1].last_sale_price)
)
self.assertEqual(
@@ -482,7 +485,7 @@ shares in position"
pp3.calculate_performance()
self.assertEqual(
pp3.positions[1].last_sale,
pp3.positions[1].last_sale_price,
10,
"should have a last sale of 10"
)
@@ -499,27 +502,58 @@ shares in position"
"should be -400 for all trades and transactions in period"
)
def dtest_daily_performance_calc(self):
hostedAlgo = factories.createAlgo("workingAlgo.py")
btRecord = BackTestRun(duration_unit="Days",duration_count=5,capital_base=25000000)
bt = BackTest(hostedAlgo,btRecord)
start = bt.periodStart
end = bt.periodEnd
#print "{start} to {end}".format(start=start, end=end)
def test_tracker(self):
trades = factories.createTradeHistory(1,[10,11,12,11],[100,100,100,100],start, self.oneday)
#createTransaction(self, sid, amount, price, dt, order_id)
bt.createTransaction(1, 100, 10.0, trades[0].dt + 30*self.onesec, None)
curPeriod = start
bt.positions = {}
dailyPeriods = []
bt.initialValue = 0.0
while (bt.mktClose) <= bt.periodEnd:
bt.updatePerformance()
dailyPeriods.append(bt.curPeriod)
bt.nextMarketDay()
trade_count = 100
sid = 133
price = [10.1] * trade_count
volume = [100] * trade_count
start_date = datetime.datetime.strptime("01/01/2011","%m/%d/%Y")
start_date = start_date.replace(tzinfo=pytz.utc)
trade_time_increment = datetime.timedelta(days=1)
trade_history = factory.create_trade_history(
sid,
price,
volume,
start_date,
trade_time_increment,
self.trading_environment
)
trade_client = TradeSimulationClient(start_date)
start = trade_history[0].dt
end = trade_history[-1].dt
tracker = perf.PerformanceTracker(
start,
end,
1000.0,
self.trading_environment
)
for event in trade_history:
#create a transaction for all but
#one trade, to simulate None transaction
if(event.dt != start):
txn = zp.namedict({
'sid' : event.sid,
'amount' : -25,
'dt' : event.dt,
'price' : 10.0,
'commission' : 0.50
})
else:
txn = None
event[zp.TRANSFORM_TYPE.TRANSACTION] = txn
trade_client.queue_event(event)
self.assertEqual(dailyPeriods[0].pnl,0,"the first day's performance should be zero")
self.assertEqual(dailyPeriods[1].pnl,100,"the second day's pnl should be 100 but was {pnl}".format(pnl=dailyPeriods[1].pnl))
df = trade_client.get_frame()
tracker.update(df)
#we skip one trade, to test case of None transaction
txn_count = len(trade_history) - 1
self.assertEqual(tracker.txn_count, txn_count)
cumulative_pos = tracker.cumulative_performance.positions[sid]
expected_size = txn_count * -25
self.assertEqual(cumulative_pos.amount, expected_size)
zipline/test/test_risk.py
+11 -14
View File
@@ -26,7 +26,7 @@ class Risk(unittest.TestCase):
start_date = datetime.datetime(year=2006, month=1, day=1, tzinfo=pytz.utc)
self.algo_returns_06 = factory.create_returns_from_list(RETURNS, start_date, self.trading_calendar)
end_date = datetime.datetime(year=2006, month=12, day=31, tzinfo=pytz.utc)
self.metrics_06 = risk.RiskReport(self.algo_returns_06, self.benchmark_returns, self.treasury_curves, self.trading_calendar)
self.metrics_06 = risk.RiskReport(self.algo_returns_06, self.trading_calendar)
def tearDown(self):
return
@@ -48,7 +48,7 @@ class Risk(unittest.TestCase):
start_date = datetime.datetime(year=2006, month=1, day=1)
end_date = datetime.datetime(year=2006, month=12, day=31)
returns = factory.create_returns_from_range(start_date, end_date, self.trading_calendar)
metrics = risk.RiskReport(returns, self.benchmark_returns, self.treasury_curves, self.trading_calendar)
metrics = risk.RiskReport(returns, self.trading_calendar)
self.assertEqual([round(x.benchmark_period_returns, 4) for x in metrics.month_periods],
[0.0255,0.0005,0.0111,0.0122,-0.0309,0.0001,0.0051,0.0213,0.0246,0.0315,0.0165,0.0126])
self.assertEqual([round(x.benchmark_period_returns, 4) for x in metrics.three_month_periods],
@@ -61,7 +61,7 @@ class Risk(unittest.TestCase):
start_date = datetime.datetime(year=2006, month=1, day=1)
end_date = datetime.datetime(year=2006, month=12, day=31)
returns = factory.create_returns_from_range(start_date, end_date, self.trading_calendar)
metrics = risk.RiskReport(returns, self.benchmark_returns, self.treasury_curves, self.trading_calendar)
metrics = risk.RiskReport(returns, self.trading_calendar)
self.assertEqual([x.trading_days for x in metrics.year_periods],[251])
self.assertEqual([x.trading_days for x in metrics.month_periods],[20,19,23,19,22,22,20,23,20,22,21,20])
@@ -69,7 +69,7 @@ class Risk(unittest.TestCase):
start_date = datetime.datetime(year=2006, month=1, day=1)
end_date = datetime.datetime(year=2006, month=12, day=31)
returns = factory.create_returns_from_range(start_date, end_date, self.trading_calendar)
metrics = risk.RiskReport(returns, self.benchmark_returns, self.treasury_curves, self.trading_calendar)
metrics = risk.RiskReport(returns, self.trading_calendar)
self.assertEqual([round(x.benchmark_volatility, 3) for x in metrics.month_periods],
[0.031,0.026,0.024,0.025,0.037,0.047,0.039,0.022,0.023,0.021,0.025,0.019])
self.assertEqual([round(x.benchmark_volatility, 3) for x in metrics.three_month_periods],
@@ -131,7 +131,7 @@ class Risk(unittest.TestCase):
start_date = datetime.datetime(year=2008, month=1, day=1)
end_date = datetime.datetime(year=2008, month=12, day=31)
returns = factory.create_returns_from_range(start_date, end_date, self.trading_calendar)
metrics = risk.RiskReport(returns, self.benchmark_returns, self.treasury_curves, self.trading_calendar)
metrics = risk.RiskReport(returns, self.trading_calendar)
self.assertEqual([round(x.benchmark_period_returns, 3) for x in metrics.month_periods],
[-0.061,-0.035,-0.006,0.048,0.011,-0.086,-0.01,0.012,-0.091,-0.169,-0.075,0.008])
self.assertEqual([round(x.benchmark_period_returns, 3) for x in metrics.three_month_periods],
@@ -144,7 +144,7 @@ class Risk(unittest.TestCase):
start_date = datetime.datetime(year=2008, month=1, day=1)
end_date = datetime.datetime(year=2008, month=12, day=31)
returns = factory.create_returns_from_range(start_date, end_date, self.trading_calendar)
metrics = risk.RiskReport(returns, self.benchmark_returns, self.treasury_curves, self.trading_calendar)
metrics = risk.RiskReport(returns, self.trading_calendar)
self.assertEqual([x.trading_days for x in metrics.year_periods],[253])
self.assertEqual([x.trading_days for x in metrics.month_periods],[21,20,20,22,21,21,22,21,21,23,19,22])
@@ -152,7 +152,7 @@ class Risk(unittest.TestCase):
start_date = datetime.datetime(year=2008, month=1, day=1)
end_date = datetime.datetime(year=2008, month=12, day=31)
returns = factory.create_returns_from_range(start_date, end_date, self.trading_calendar)
metrics = risk.RiskReport(returns, self.benchmark_returns, self.treasury_curves, self.trading_calendar)
metrics = risk.RiskReport(returns, self.trading_calendar)
self.assertEqual([round(x.benchmark_volatility, 3) for x in metrics.month_periods],
[0.07,0.058,0.082,0.054,0.041,0.057,0.068,0.06,0.157,0.244,0.195,0.145])
self.assertEqual([round(x.benchmark_volatility, 3) for x in metrics.three_month_periods],
@@ -166,7 +166,7 @@ class Risk(unittest.TestCase):
start_date = datetime.datetime(year=2006, month=1, day=1)
end_date = datetime.datetime(year=2006, month=12, day=31)
returns = factory.create_returns_from_range(start_date, end_date, self.trading_calendar)
metrics = risk.RiskReport(returns, self.benchmark_returns, self.treasury_curves, self.trading_calendar)
metrics = risk.RiskReport(returns, self.trading_calendar)
self.assertEqual([round(x.treasury_period_return, 4) for x in metrics.month_periods],
[0.0037,0.0034,0.0039,0.0038,0.0040,0.0037,0.0043,0.0043,0.0038,0.0044,0.0043,0.0041])
self.assertEqual([round(x.treasury_period_return, 4) for x in metrics.three_month_periods],
@@ -183,7 +183,7 @@ class Risk(unittest.TestCase):
start_date = datetime.datetime(year=1991, month=1, day=1)
returns = factory.create_returns(365 * 5 + 2, start_date, self.trading_calendar) #1992 and 1996 were leap years
returns = returns[:-10] #truncate the returns series to end mid-month
metrics = risk.RiskReport(returns, self.benchmark_returns, self.treasury_curves, self.trading_calendar)
metrics = risk.RiskReport(returns, self.trading_calendar)
total_months = 60
self.check_metrics(metrics, total_months, start_date)
@@ -194,7 +194,7 @@ class Risk(unittest.TestCase):
#because we may catch the leap of the last year, and i think this func is [start,end)
ld = calendar.leapdays(start_date.year, start_date.year + years + 1)
returns = factory.create_returns(365 * years + ld, start_date, self.trading_calendar)
metrics = risk.RiskReport(returns, self.benchmark_returns, self.treasury_curves, self.trading_calendar)
metrics = risk.RiskReport(returns, self.trading_calendar)
total_months = years * 12
self.check_metrics(metrics, total_months, start_date)
@@ -202,10 +202,7 @@ class Risk(unittest.TestCase):
self.assert_range_length(metrics.month_periods, total_months, 1, start_date)
self.assert_range_length(metrics.three_month_periods, total_months, 3, start_date)
self.assert_range_length(metrics.six_month_periods, total_months, 6, start_date)
self.assert_range_length(metrics.year_periods, total_months, 12, start_date)
self.assert_range_length(metrics.three_year_periods, total_months, 36, start_date)
self.assert_range_length(metrics.five_year_periods, total_months, 60, start_date)
self.assert_range_length(metrics.year_periods, total_months, 12, start_date)
def assert_last_day(self, period_end):
#30 days has september, april, june and november
if(period_end.month in [9,4,6,11]):