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Revert "ENH Allow order_percent to work with various market values"
This reverts commit dd37a49f2f as it lead to different algo behavior we have to investigate first.
This commit is contained in:
Thomas Wiecki
+4
-134
@@ -79,7 +79,7 @@ from nose.tools import assert_raises
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from six.moves import range
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from six import itervalues
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from zipline.algorithm import TradingAlgorithm, round_shares
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from zipline.algorithm import TradingAlgorithm
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from zipline.api import FixedSlippage
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from zipline.errors import UnsupportedOrderParameters
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from zipline.finance.execution import (
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@@ -345,33 +345,6 @@ class TestTargetAlgorithm(TradingAlgorithm):
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self.order_target(0, self.target_shares)
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class TestTargetAlgorithm_NonInt(TradingAlgorithm):
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def initialize(self):
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self.target_shares = 0
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self.sale_price = None
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self.i = 0
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def handle_data(self, data):
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if self.target_shares == 0:
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assert 0 not in self.portfolio.positions
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else:
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assert self.portfolio.positions[0]['amount'] == \
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self.target_shares, "Orders not filled correctly."
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assert self.portfolio.positions[0]['last_sale_price'] == \
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data[0].price, "Orders not filled at current price."
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if self.i == 0:
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self.target_shares = 5
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self.order_target(0, 5.1)
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elif self.i == 1:
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self.target_shares = 10
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self.order_target(0, 10.1)
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elif self.i == 2:
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self.target_shares = 5
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self.order_target(0, 5.1)
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self.i += 1
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class TestOrderPercentAlgorithm(TradingAlgorithm):
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def initialize(self):
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self.target_shares = 0
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@@ -395,126 +368,23 @@ class TestOrderPercentAlgorithm(TradingAlgorithm):
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/ data[0].price)
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class TestOrderPercentAlgorithmPercentOf(TradingAlgorithm):
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def initialize(self):
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self.target_shares = dict([(i, 0) for i in range(8)])
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def handle_data(self, data):
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for sid, target_shares in self.target_shares.items():
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position = self.portfolio.positions[sid]
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assert target_shares == position.amount
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# reduce sizes due to volume limitiations
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full = 0.001
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half = 0.0005
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pos_values = {}
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for i in range(len(data.keys())):
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pos_values[i] = (
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self.portfolio.positions[i].amount
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* self.portfolio.positions[i].last_sale_price)
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port = self.portfolio.portfolio_value
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cash = self.portfolio.cash
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longs = sum(v for v in pos_values.values() if v > 0)
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shorts = sum(v for v in pos_values.values() if v < 0)
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gross = sum(abs(v) for v in pos_values.values())
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group = [0, 1, 2]
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group_val = sum(v for sid, v in pos_values.items() if sid in group)
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def expected_shares(sid, value):
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return round_shares(value / data[sid].price)
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self.order_percent(0, full, percent_of='portfolio')
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self.order_percent(1, -half, percent_of='cash')
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self.order_percent(2, half, percent_of='ex_cash')
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self.order_percent(3, half, percent_of='longs')
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self.order_percent(4, half, percent_of='longs_cash')
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self.order_percent(5, half, percent_of='shorts')
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self.order_percent(
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6, half, percent_of_fn=lambda p: p.sid in group)
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self.order_percent(7, full, percent_of='gross')
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self.target_shares[0] += expected_shares(0, full * port)
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self.target_shares[1] += expected_shares(1, -half * cash)
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self.target_shares[2] += expected_shares(2, half * (port - cash))
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self.target_shares[3] += expected_shares(3, half * longs)
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self.target_shares[4] += expected_shares(4, half * (longs + cash))
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self.target_shares[5] += expected_shares(5, half * shorts)
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self.target_shares[6] += expected_shares(6, half * group_val)
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self.target_shares[7] += expected_shares(7, full * gross)
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class TestTargetPercentAlgorithm(TradingAlgorithm):
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def initialize(self):
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self.target_shares = 0
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self.sale_price = None
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self.exp_value = 0
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def handle_data(self, data):
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if self.target_shares == 0:
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assert 0 not in self.portfolio.positions
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self.target_shares = 1
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else:
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value = self.portfolio.positions[0]['amount'] * self.sale_price
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assert abs(value - self.exp_value) <= self.sale_price, \
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assert np.round(self.portfolio.portfolio_value * 0.002) == \
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self.portfolio.positions[0]['amount'] * self.sale_price, \
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"Orders not filled correctly."
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assert self.portfolio.positions[0]['last_sale_price'] == \
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data[0].price, "Orders not filled at current price."
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self.sale_price = data[0].price
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self.order_target_percent(0, .002)
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self.exp_value = self.portfolio.portfolio_value * 0.002
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class TestTargetPercentAlgorithmPercentOf(TradingAlgorithm):
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def initialize(self):
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self.target_shares = dict([(i, 0) for i in range(8)])
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def handle_data(self, data):
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for sid, target_shares in self.target_shares.items():
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position = self.portfolio.positions[sid]
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assert target_shares == position.amount
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# reduce sizes due to volume limitiations
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full = 0.001
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half = 0.0005
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pos_values = {}
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for i in range(len(data.keys())):
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pos_values[i] = (
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self.portfolio.positions[i].amount
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* self.portfolio.positions[i].last_sale_price)
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port = self.portfolio.portfolio_value
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cash = self.portfolio.cash
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longs = sum(v for v in pos_values.values() if v > 0)
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shorts = sum(v for v in pos_values.values() if v < 0)
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gross = sum(abs(v) for v in pos_values.values())
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group = [0, 1, 2]
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group_val = sum(v for sid, v in pos_values.items() if sid in group)
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def expected_shares(sid, value):
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return round_shares(value / data[sid].price)
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self.order_target_percent(0, full, percent_of='portfolio')
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self.order_target_percent(1, -half, percent_of='cash')
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self.order_target_percent(2, half, percent_of='ex_cash')
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self.order_target_percent(3, half, percent_of='longs')
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self.order_target_percent(4, half, percent_of='longs_cash')
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self.order_target_percent(5, half, percent_of='shorts')
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self.order_target_percent(
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6, half, percent_of_fn=lambda p: p.sid in group)
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self.order_target_percent(5, full, percent_of='gross')
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self.target_shares[0] = expected_shares(0, full * port)
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self.target_shares[1] = expected_shares(1, -half * cash)
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self.target_shares[2] = expected_shares(2, half * (port - cash))
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self.target_shares[3] = expected_shares(3, half * longs)
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self.target_shares[4] = expected_shares(4, half * (longs + cash))
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self.target_shares[5] = expected_shares(5, half * shorts)
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self.target_shares[6] = expected_shares(6, half * group_val)
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self.target_shares[7] = expected_shares(7, full * gross)
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class TestTargetValueAlgorithm(TradingAlgorithm):
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@@ -536,7 +406,7 @@ class TestTargetValueAlgorithm(TradingAlgorithm):
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data[0].price, "Orders not filled at current price."
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self.order_target_value(0, 20)
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self.target_shares = round_shares(20 / data[0].price)
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self.target_shares = np.round(20 / data[0].price)
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############################
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