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Adds dividends to performance tracking.
Algorithm returns and the risk calculations that depend on them now include cash dividends. This commit does _not_ provide an API for user algorithms to access dividends. PerformanceTracker expects the dividend data to arrive as events, similar to the way that Trades arrive. Dividends are expected to have adjusted payment amounts that are inline with adjusted trades. PerformanceTracker maintains state of all the unpaid dividends in the position objects held in PerformancePeriod. Dividend objects contain all the relevant dates (declared, ex, payment) as well as net and gross amounts. Dividends are removed from the list as they are paid. Cash flow is not incremented until the payment day. This creates the possibility of a dividend being owed but not paid or realized before the end of a test. For example, a dividend with an ex_date of today may have a pay date 2 weeks in the future. Right now the algorithm does not receive any credit for unpaid dividends. Tests cover buying/selling around the ex_date and payment_date, and checking that the performance calculated is as expected.
This commit is contained in:
fawce
+377
-56
@@ -17,7 +17,6 @@ import collections
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import unittest
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from nose_parameterized import parameterized
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import random
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import datetime
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import pytz
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import itertools
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@@ -28,55 +27,377 @@ import zipline.finance.performance as perf
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from zipline.utils.protocol_utils import ndict
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from zipline.gens.composites import date_sorted_sources
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from zipline.finance.trading import TradingEnvironment
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from zipline.utils.factory import create_random_trading_environment
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class TestPerformance(unittest.TestCase):
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onesec = datetime.timedelta(seconds=1)
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oneday = datetime.timedelta(days=1)
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tradingday = datetime.timedelta(hours=6, minutes=30)
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class TestDividendPerformance(unittest.TestCase):
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def setUp(self):
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self.onesec = datetime.timedelta(seconds=1)
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self.oneday = datetime.timedelta(days=1)
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self.tradingday = datetime.timedelta(hours=6, minutes=30)
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self.trading_environment, self.dt, self.end_dt = self.create_env()
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self.trading_environment, self.dt, self.end_dt = \
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create_random_trading_environment()
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def create_env(self, start_dt=None):
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benchmark_returns, treasury_curves = \
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factory.load_market_data()
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self.trading_environment.capital_base = 10e3
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if not start_dt:
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for n in range(100):
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random_index = random.randint(
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0,
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len(treasury_curves)
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)
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start_dt = treasury_curves.keys()[random_index]
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end_dt = start_dt + datetime.timedelta(days=365)
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now = datetime.datetime.utcnow().replace(tzinfo=pytz.utc)
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if end_dt <= now:
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break
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else:
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end_dt = start_dt + datetime.timedelta(days=365)
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now = datetime.datetime.utcnow().replace(tzinfo=pytz.utc)
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assert end_dt <= now, """
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failed to find a date suitable daterange after 100 attempts. please double
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check treasury and benchmark data in findb, and re-run the test."""
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assert start_dt < end_dt, "start_dt must be less than end_dt"
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trading_environment = TradingEnvironment(
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benchmark_returns,
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treasury_curves,
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period_start=start_dt,
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period_end=end_dt
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def test_long_position_receives_dividend(self):
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#post some trades in the market
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events = factory.create_trade_history(
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1,
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[10, 10, 10, 10, 10],
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[100, 100, 100, 100, 100],
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oneday,
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self.trading_environment
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)
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return trading_environment, start_dt, end_dt
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dividend = factory.create_dividend(
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1,
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10.00,
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events[0].dt,
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events[1].dt,
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events[2].dt
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)
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events.insert(1, dividend)
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txn = factory.create_txn(1, 10.0, 100, self.dt+oneday)
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events[2].TRANSACTION = txn
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perf_tracker = perf.PerformanceTracker(self.trading_environment)
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transformed_events = list(perf_tracker.transform(
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((event.dt, [event]) for event in events))
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)
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#flatten the list of events
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results = []
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for te in transformed_events:
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for event in te[1]:
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for message in event.perf_messages:
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results.append(message)
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perf_messages, risk = perf_tracker.handle_simulation_end()
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results.append(perf_messages[0])
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self.assertEqual(results[0]['daily_perf']['period_open'], events[0].dt)
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self.assertEqual(
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results[-1]['daily_perf']['period_open'],
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events[-1].dt
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)
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self.assertEqual(len(results), 5)
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cumulative_returns = \
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[event['cumulative_perf']['returns'] for event in results]
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self.assertEqual(cumulative_returns, [0.0, 0.0, 0.1, 0.1, 0.1])
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daily_returns = [event['daily_perf']['returns'] for event in results]
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self.assertEqual(daily_returns, [0.0, 0.0, 0.10, 0.0, 0.0])
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cash_flows = [event['daily_perf']['capital_used'] for event in results]
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self.assertEqual(cash_flows, [0, -1000, 1000, 0, 0])
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cumulative_cash_flows = \
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[event['cumulative_perf']['capital_used'] for event in results]
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self.assertEqual(cumulative_cash_flows, [0, -1000, 0, 0, 0])
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def test_post_ex_long_position_receives_no_dividend(self):
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#post some trades in the market
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events = factory.create_trade_history(
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1,
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[10, 10, 10, 10, 10],
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[100, 100, 100, 100, 100],
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oneday,
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self.trading_environment
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)
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dividend = factory.create_dividend(
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1,
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10.00,
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events[0].dt,
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events[1].dt,
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events[2].dt
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)
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events.insert(1, dividend)
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txn = factory.create_txn(1, 10.0, 100, events[3].dt)
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events[3].TRANSACTION = txn
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perf_tracker = perf.PerformanceTracker(self.trading_environment)
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transformed_events = list(perf_tracker.transform(
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((event.dt, [event]) for event in events))
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)
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#flatten the list of events
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results = []
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for te in transformed_events:
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for event in te[1]:
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for message in event.perf_messages:
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results.append(message)
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perf_messages, risk = perf_tracker.handle_simulation_end()
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results.append(perf_messages[0])
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self.assertEqual(len(results), 5)
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cumulative_returns = \
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[event['cumulative_perf']['returns'] for event in results]
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self.assertEqual(cumulative_returns, [0, 0, 0, 0, 0])
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daily_returns = [event['daily_perf']['returns'] for event in results]
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self.assertEqual(daily_returns, [0, 0, 0, 0, 0])
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cash_flows = [event['daily_perf']['capital_used'] for event in results]
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self.assertEqual(cash_flows, [0, 0, -1000, 0, 0])
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cumulative_cash_flows = \
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[event['cumulative_perf']['capital_used'] for event in results]
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self.assertEqual(cumulative_cash_flows, [0, 0, -1000, -1000, -1000])
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def test_selling_before_dividend_payment_still_gets_paid(self):
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#post some trades in the market
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events = factory.create_trade_history(
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1,
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[10, 10, 10, 10, 10],
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[100, 100, 100, 100, 100],
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oneday,
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self.trading_environment
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)
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dividend = factory.create_dividend(
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1,
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10.00,
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events[0].dt,
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events[1].dt,
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events[3].dt
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)
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buy_txn = factory.create_txn(1, 10.0, 100, events[1].dt)
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events[1].TRANSACTION = buy_txn
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sell_txn = factory.create_txn(1, 10.0, -100, events[2].dt)
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events[2].TRANSACTION = sell_txn
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events.insert(1, dividend)
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perf_tracker = perf.PerformanceTracker(self.trading_environment)
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transformed_events = list(perf_tracker.transform(
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((event.dt, [event]) for event in events))
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)
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#flatten the list of events
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results = []
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for te in transformed_events:
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for event in te[1]:
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for message in event.perf_messages:
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results.append(message)
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perf_messages, risk = perf_tracker.handle_simulation_end()
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results.append(perf_messages[0])
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self.assertEqual(len(results), 5)
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cumulative_returns = \
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[event['cumulative_perf']['returns'] for event in results]
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self.assertEqual(cumulative_returns, [0, 0, 0, 0.1, 0.1])
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daily_returns = [event['daily_perf']['returns'] for event in results]
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self.assertEqual(daily_returns, [0, 0, 0, 0.1, 0])
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cash_flows = [event['daily_perf']['capital_used'] for event in results]
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self.assertEqual(cash_flows, [0, -1000, 1000, 1000, 0])
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cumulative_cash_flows = \
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[event['cumulative_perf']['capital_used'] for event in results]
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self.assertEqual(cumulative_cash_flows, [0, -1000, 0, 1000, 1000])
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def test_buy_and_sell_before_ex(self):
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#post some trades in the market
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events = factory.create_trade_history(
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1,
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[10, 10, 10, 10, 10, 10],
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[100, 100, 100, 100, 100, 100],
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oneday,
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self.trading_environment
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)
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dividend = factory.create_dividend(
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1,
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10.00,
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events[3].dt,
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events[4].dt,
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events[5].dt
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)
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buy_txn = factory.create_txn(1, 10.0, 100, events[1].dt)
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events[1].TRANSACTION = buy_txn
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sell_txn = factory.create_txn(1, 10.0, -100, events[2].dt)
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events[2].TRANSACTION = sell_txn
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events.insert(1, dividend)
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perf_tracker = perf.PerformanceTracker(self.trading_environment)
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transformed_events = list(perf_tracker.transform(
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((event.dt, [event]) for event in events))
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)
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#flatten the list of events
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results = []
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for te in transformed_events:
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for event in te[1]:
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for message in event.perf_messages:
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results.append(message)
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perf_messages, risk = perf_tracker.handle_simulation_end()
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results.append(perf_messages[0])
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self.assertEqual(len(results), 6)
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cumulative_returns = \
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[event['cumulative_perf']['returns'] for event in results]
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self.assertEqual(cumulative_returns, [0, 0, 0, 0, 0, 0])
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daily_returns = [event['daily_perf']['returns'] for event in results]
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self.assertEqual(daily_returns, [0, 0, 0, 0, 0, 0])
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cash_flows = [event['daily_perf']['capital_used'] for event in results]
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self.assertEqual(cash_flows, [0, -1000, 1000, 0, 0, 0])
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cumulative_cash_flows = \
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[event['cumulative_perf']['capital_used'] for event in results]
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self.assertEqual(cumulative_cash_flows, [0, -1000, 0, 0, 0, 0])
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def test_ending_before_pay_date(self):
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#post some trades in the market
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events = factory.create_trade_history(
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1,
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[10, 10, 10, 10, 10],
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[100, 100, 100, 100, 100],
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oneday,
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self.trading_environment
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)
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dividend = factory.create_dividend(
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1,
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10.00,
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events[0].dt,
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events[1].dt,
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events[-1].dt + 10*oneday
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)
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buy_txn = factory.create_txn(1, 10.0, 100, events[1].dt)
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events[1].TRANSACTION = buy_txn
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events.insert(1, dividend)
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perf_tracker = perf.PerformanceTracker(self.trading_environment)
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transformed_events = list(perf_tracker.transform(
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((event.dt, [event]) for event in events))
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)
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#flatten the list of events
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results = []
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for te in transformed_events:
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for event in te[1]:
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for message in event.perf_messages:
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results.append(message)
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perf_messages, risk = perf_tracker.handle_simulation_end()
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results.append(perf_messages[0])
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self.assertEqual(len(results), 5)
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cumulative_returns = \
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[event['cumulative_perf']['returns'] for event in results]
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self.assertEqual(cumulative_returns, [0, 0, 0, 0.0, 0.0])
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daily_returns = [event['daily_perf']['returns'] for event in results]
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self.assertEqual(daily_returns, [0, 0, 0, 0, 0])
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cash_flows = [event['daily_perf']['capital_used'] for event in results]
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self.assertEqual(cash_flows, [0, -1000, 0, 0, 0])
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cumulative_cash_flows = \
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[event['cumulative_perf']['capital_used'] for event in results]
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self.assertEqual(
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cumulative_cash_flows,
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[0, -1000, -1000, -1000, -1000]
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)
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def test_short_position_receives_no_dividend(self):
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#post some trades in the market
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events = factory.create_trade_history(
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1,
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[10, 10, 10, 10, 10],
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[100, 100, 100, 100, 100],
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oneday,
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self.trading_environment
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)
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dividend = factory.create_dividend(
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1,
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10.00,
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events[0].dt,
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events[1].dt,
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events[2].dt
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)
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events.insert(1, dividend)
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txn = factory.create_txn(1, 10.0, -100, self.dt+oneday)
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events[2].TRANSACTION = txn
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perf_tracker = perf.PerformanceTracker(self.trading_environment)
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transformed_events = list(perf_tracker.transform(
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((event.dt, [event]) for event in events))
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)
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#flatten the list of events
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results = []
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for te in transformed_events:
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for event in te[1]:
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for message in event.perf_messages:
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results.append(message)
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perf_messages, risk = perf_tracker.handle_simulation_end()
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results.append(perf_messages[0])
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self.assertEqual(len(results), 5)
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cumulative_returns = \
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[event['cumulative_perf']['returns'] for event in results]
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self.assertEqual(cumulative_returns, [0.0, 0.0, 0.0, 0.0, 0.0])
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daily_returns = [event['daily_perf']['returns'] for event in results]
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self.assertEqual(daily_returns, [0.0, 0.0, 0.0, 0.0, 0.0])
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cash_flows = [event['daily_perf']['capital_used'] for event in results]
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self.assertEqual(cash_flows, [0, 1000, 0, 0, 0])
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cumulative_cash_flows = \
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[event['cumulative_perf']['capital_used'] for event in results]
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self.assertEqual(cumulative_cash_flows, [0, 1000, 1000, 1000, 1000])
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def test_no_position_receives_no_dividend(self):
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#post some trades in the market
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events = factory.create_trade_history(
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1,
|
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[10, 10, 10, 10, 10],
|
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[100, 100, 100, 100, 100],
|
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oneday,
|
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self.trading_environment
|
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)
|
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|
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dividend = factory.create_dividend(
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1,
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10.00,
|
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events[0].dt,
|
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events[1].dt,
|
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events[2].dt
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)
|
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|
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events.insert(1, dividend)
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perf_tracker = perf.PerformanceTracker(self.trading_environment)
|
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transformed_events = list(perf_tracker.transform(
|
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((event.dt, [event]) for event in events))
|
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)
|
||||
|
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#flatten the list of events
|
||||
results = []
|
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for te in transformed_events:
|
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for event in te[1]:
|
||||
for message in event.perf_messages:
|
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results.append(message)
|
||||
|
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perf_messages, risk = perf_tracker.handle_simulation_end()
|
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results.append(perf_messages[0])
|
||||
|
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self.assertEqual(len(results), 5)
|
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cumulative_returns = \
|
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[event['cumulative_perf']['returns'] for event in results]
|
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self.assertEqual(cumulative_returns, [0.0, 0.0, 0.0, 0.0, 0.0])
|
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daily_returns = [event['daily_perf']['returns'] for event in results]
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self.assertEqual(daily_returns, [0.0, 0.0, 0.0, 0.0, 0.0])
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cash_flows = [event['daily_perf']['capital_used'] for event in results]
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self.assertEqual(cash_flows, [0, 0, 0, 0, 0])
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cumulative_cash_flows = \
|
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[event['cumulative_perf']['capital_used'] for event in results]
|
||||
self.assertEqual(cumulative_cash_flows, [0, 0, 0, 0, 0])
|
||||
|
||||
|
||||
class TestPositionPerformance(unittest.TestCase):
|
||||
|
||||
def setUp(self):
|
||||
self.trading_environment, self.dt, self.end_dt = \
|
||||
create_random_trading_environment()
|
||||
|
||||
def test_long_position(self):
|
||||
"""
|
||||
@@ -88,11 +409,11 @@ check treasury and benchmark data in findb, and re-run the test."""
|
||||
1,
|
||||
[10, 10, 10, 11],
|
||||
[100, 100, 100, 100],
|
||||
self.onesec,
|
||||
onesec,
|
||||
self.trading_environment
|
||||
)
|
||||
|
||||
txn = factory.create_txn(1, 10.0, 100, self.dt + self.onesec)
|
||||
txn = factory.create_txn(1, 10.0, 100, self.dt + onesec)
|
||||
pp = perf.PerformancePeriod(1000.0)
|
||||
|
||||
pp.execute_transaction(txn)
|
||||
@@ -102,7 +423,7 @@ check treasury and benchmark data in findb, and re-run the test."""
|
||||
pp.calculate_performance()
|
||||
|
||||
self.assertEqual(
|
||||
pp.period_capital_used,
|
||||
pp.period_cash_flow,
|
||||
-1 * txn.price * txn.amount,
|
||||
"capital used should be equal to the opposite of the transaction \
|
||||
cost of sole txn in test"
|
||||
@@ -157,13 +478,13 @@ single short-sale transaction"""
|
||||
1,
|
||||
[10, 10, 10, 11, 10, 9],
|
||||
[100, 100, 100, 100, 100, 100],
|
||||
self.onesec,
|
||||
onesec,
|
||||
self.trading_environment
|
||||
)
|
||||
|
||||
trades_1 = trades[:-2]
|
||||
|
||||
txn = factory.create_txn(1, 10.0, -100, self.dt + self.onesec)
|
||||
txn = factory.create_txn(1, 10.0, -100, self.dt + onesec)
|
||||
pp = perf.PerformancePeriod(1000.0)
|
||||
|
||||
pp.execute_transaction(txn)
|
||||
@@ -173,7 +494,7 @@ single short-sale transaction"""
|
||||
pp.calculate_performance()
|
||||
|
||||
self.assertEqual(
|
||||
pp.period_capital_used,
|
||||
pp.period_cash_flow,
|
||||
-1 * txn.price * txn.amount,
|
||||
"capital used should be equal to the opposite of the transaction\
|
||||
cost of sole txn in test"
|
||||
@@ -230,7 +551,7 @@ single short-sale transaction"""
|
||||
pp.calculate_performance()
|
||||
|
||||
self.assertEqual(
|
||||
pp.period_capital_used,
|
||||
pp.period_cash_flow,
|
||||
0,
|
||||
"capital used should be zero, there were no transactions in \
|
||||
performance period"
|
||||
@@ -292,7 +613,7 @@ single short-sale transaction"""
|
||||
ppTotal.calculate_performance()
|
||||
|
||||
self.assertEqual(
|
||||
ppTotal.period_capital_used,
|
||||
ppTotal.period_cash_flow,
|
||||
-1 * txn.price * txn.amount,
|
||||
"capital used should be equal to the opposite of the transaction \
|
||||
cost of sole txn in test"
|
||||
@@ -347,7 +668,7 @@ trade after cover"""
|
||||
1,
|
||||
[10, 10, 10, 11, 9, 8, 7, 8, 9, 10],
|
||||
[100, 100, 100, 100, 100, 100, 100, 100, 100, 100],
|
||||
self.onesec,
|
||||
onesec,
|
||||
self.trading_environment
|
||||
)
|
||||
|
||||
@@ -355,10 +676,10 @@ trade after cover"""
|
||||
1,
|
||||
10.0,
|
||||
-100,
|
||||
self.dt + self.onesec
|
||||
self.dt + onesec
|
||||
)
|
||||
|
||||
cover_txn = factory.create_txn(1, 7.0, 100, self.dt + self.onesec * 6)
|
||||
cover_txn = factory.create_txn(1, 7.0, 100, self.dt + onesec * 6)
|
||||
pp = perf.PerformancePeriod(1000.0)
|
||||
|
||||
pp.execute_transaction(short_txn)
|
||||
@@ -373,7 +694,7 @@ trade after cover"""
|
||||
cover_txn_cost = cover_txn.price * cover_txn.amount
|
||||
|
||||
self.assertEqual(
|
||||
pp.period_capital_used,
|
||||
pp.period_cash_flow,
|
||||
-1 * short_txn_cost - cover_txn_cost,
|
||||
"capital used should be equal to the net transaction costs"
|
||||
)
|
||||
@@ -426,7 +747,7 @@ shares in position"
|
||||
1,
|
||||
[10, 11, 11, 12],
|
||||
[100, 100, 100, 100],
|
||||
self.onesec,
|
||||
onesec,
|
||||
self.trading_environment
|
||||
)
|
||||
|
||||
@@ -434,7 +755,7 @@ shares in position"
|
||||
1,
|
||||
[10, 11, 11, 12],
|
||||
[100, 100, 100, 100],
|
||||
self.onesec,
|
||||
onesec,
|
||||
self.trading_environment
|
||||
)
|
||||
|
||||
@@ -470,13 +791,13 @@ shares in position"
|
||||
1,
|
||||
10.0,
|
||||
-100,
|
||||
self.dt + self.onesec * 4)
|
||||
self.dt + onesec * 4)
|
||||
|
||||
down_tick = factory.create_trade(
|
||||
1,
|
||||
10.0,
|
||||
100,
|
||||
trades[-1].dt + self.onesec)
|
||||
trades[-1].dt + onesec)
|
||||
|
||||
pp.rollover()
|
||||
|
||||
|
||||
Reference in New Issue
Block a user