def test_close_position_equity(self):
metadata = {1: {'symbol': 'TEST',
'asset_type': 'equity',
'end_date': self.days[3]}}
self.algo = TestAlgorithm(sid=1, amount=1, order_count=1,
instant_fill=True, commission=PerShare(0),
asset_metadata=metadata)
self.data = DataPanelSource(self.panel)
# Check results
expected_positions = [1, 1, 0]
expected_pnl = [0, 1, 2]
results = self.run_algo()
self.check_algo_pnl(results, expected_pnl)
self.check_algo_positions(results, expected_positions)
def setUp(self):
days = TradingEnvironment().trading_days
self.index = [days[0], days[1], days[2]]
pan = pd.Panel({1: pd.DataFrame({
'price': [1, 2, 4], 'volume': [1e9, 0, 0],
'type': [DATASOURCE_TYPE.TRADE,
DATASOURCE_TYPE.TRADE,
DATASOURCE_TYPE.CLOSE_POSITION]},
index=self.index)
})
self.data = DataPanelSource(pan)
self.algo = TestAlgorithm(sid=1, amount=1, order_count=1,
instant_fill=True, commission=PerShare(0))
self.results = self.run_algo()
self.expected_positions = [1, 1, 0]
self.expected_pnl = [0, 1, 2]
def test_auto_close_future(self):
metadata = {1: {'symbol': 'TEST',
'asset_type': 'future',
'notice_date': self.days[3],
'expiration_date': self.days[4]}}
self.algo = TestAlgorithm(sid=1, amount=1, order_count=1,
instant_fill=True, commission=PerShare(0),
asset_metadata=metadata)
self.data = DataPanelSource(self.no_close_panel)
# Check results
results = self.run_algo()
expected_pnl = [0, 1, 2]
self.check_algo_pnl(results, expected_pnl)
expected_positions = [1, 1, 0]
self.check_algo_positions(results, expected_positions)
class TestClosePosAlgo(TestCase):
def setUp(self):
days = TradingEnvironment().trading_days
self.index = [days[0], days[1], days[2]]
pan = pd.Panel({1: pd.DataFrame({
'price': [1, 2, 4], 'volume': [1e9, 0, 0],
'type': [DATASOURCE_TYPE.TRADE,
DATASOURCE_TYPE.TRADE,
DATASOURCE_TYPE.CLOSE_POSITION]},
index=self.index)
})
self.data = DataPanelSource(pan)
self.algo = TestAlgorithm(sid=1, amount=1, order_count=1,
instant_fill=True, commission=PerShare(0))
self.results = self.run_algo()
self.expected_positions = [1, 1, 0]
self.expected_pnl = [0, 1, 2]
def run_algo(self):
results = self.algo.run(self.data)
return results
def test_algo_pnl(self):
for i, pnl in enumerate(self.results.pnl):
self.assertEqual(pnl, self.expected_pnl[i])
def test_algo_positions(self):
for i, amount in enumerate(self.results.positions):
if amount:
actual_position = amount[0]['amount']
else:
actual_position = 0
self.assertEqual(actual_position, self.expected_positions[i])
def tearDown(self):
pass
self.algo = None
trading.environment = None
def create_test_zipline(**config):
"""
:param config: A configuration object that is a dict with:
- environment - a \
:py:class:`zipline.finance.trading.TradingEnvironment`
- sid - an integer, which will be used as the security ID.
- order_count - the number of orders the test algo will place,
defaults to 100
- order_amount - the number of shares per order, defaults to 100
- trade_count - the number of trades to simulate, defaults to 101
to ensure all orders are processed.
- algorithm - optional parameter providing an algorithm. defaults
to :py:class:`zipline.test.algorithms.TestAlgorithm`
- trade_source - optional parameter to specify trades, if present.
If not present :py:class:`zipline.sources.SpecificEquityTrades`
is the source, with daily frequency in trades.
- slippage: optional parameter that configures the
:py:class:`zipline.gens.tradingsimulation.TransactionSimulator`.
Expects an object with a simulate mehod, such as
:py:class:`zipline.gens.tradingsimulation.FixedSlippage`.
:py:mod:`zipline.finance.trading`
- transforms: optional parameter that provides a list
of StatefulTransform objects.
"""
assert isinstance(config, dict)
sid_list = config.get('sid_list')
if not sid_list:
sid = config.get('sid')
sid_list = [sid]
concurrent_trades = config.get('concurrent_trades', False)
#--------------------
# Trading Environment
#--------------------
if 'environment' in config:
trading_environment = config['environment']
else:
trading_environment = factory.create_trading_environment()
if 'order_count' in config:
order_count = config['order_count']
else:
order_count = 100
if 'order_amount' in config:
order_amount = config['order_amount']
else:
order_amount = 100
if 'trade_count' in config:
trade_count = config['trade_count']
else:
# to ensure all orders are filled, we provide one more
# trade than order
trade_count = 101
#-------------------
# Create the Algo
#-------------------
if 'algorithm' in config:
test_algo = config['algorithm']
else:
test_algo = TestAlgorithm(
sid,
order_amount,
order_count
)
#-------------------
# Trade Source
#-------------------
if 'trade_source' in config:
trade_source = config['trade_source']
else:
trade_source = factory.create_daily_trade_source(
sid_list,
trade_count,
trading_environment,
concurrent=concurrent_trades
)
test_algo.set_sources([trade_source])
#-------------------
# Transforms
#-------------------
transforms = config.get('transforms', None)
if transforms is not None:
test_algo.set_transforms(transforms)
#-------------------
# Slippage
# ------------------
slippage = config.get('slippage', None)
if slippage is not None:
test_algo.set_slippage(slippage)
# ------------------
# generator/simulator
sim = test_algo.get_generator(trading_environment)
return sim
def create_test_zipline(**config):
"""
:param config: A configuration object that is a dict with:
- sid - an integer, which will be used as the asset ID.
- order_count - the number of orders the test algo will place,
defaults to 100
- order_amount - the number of shares per order, defaults to 100
- trade_count - the number of trades to simulate, defaults to 101
to ensure all orders are processed.
- algorithm - optional parameter providing an algorithm. defaults
to :py:class:`zipline.test.algorithms.TestAlgorithm`
- trade_source - optional parameter to specify trades, if present.
If not present :py:class:`zipline.sources.SpecificEquityTrades`
is the source, with daily frequency in trades.
- slippage: optional parameter that configures the
:py:class:`zipline.gens.tradingsimulation.TransactionSimulator`.
Expects an object with a simulate mehod, such as
:py:class:`zipline.gens.tradingsimulation.FixedSlippage`.
:py:mod:`zipline.finance.trading`
"""
assert isinstance(config, dict)
try:
sid_list = config['sid_list']
except KeyError:
try:
sid_list = [config['sid']]
except KeyError:
raise Exception("simfactory create_test_zipline() requires "
"argument 'sid_list' or 'sid'")
concurrent_trades = config.get('concurrent_trades', False)
if 'order_count' in config:
order_count = config['order_count']
else:
order_count = 100
if 'order_amount' in config:
order_amount = config['order_amount']
else:
order_amount = 100
# -------------------
# Create the Algo
# -------------------
if 'algorithm' in config:
test_algo = config['algorithm']
else:
test_algo = TestAlgorithm(sid_list[0],
order_amount,
order_count,
sim_params=config.get(
'sim_params',
factory.create_simulation_parameters()),
slippage=config.get('slippage'),
identifiers=sid_list)
# -------------------
# Trade Source
# -------------------
if 'trade_source' in config:
trade_source = config['trade_source']
else:
trade_source = factory.create_daily_trade_source(
sid_list, test_algo.sim_params, concurrent=concurrent_trades)
if trade_source:
test_algo.set_sources([trade_source])
# -------------------
# Benchmark source
# -------------------
test_algo.benchmark_return_source = config.get('benchmark_source', None)
# ------------------
# generator/simulator
sim = test_algo.get_generator()
return sim
def create_test_zipline(**config):
"""
:param config: A configuration object that is a dict with:
- sid - an integer, which will be used as the asset ID.
- order_count - the number of orders the test algo will place,
defaults to 100
- order_amount - the number of shares per order, defaults to 100
- trade_count - the number of trades to simulate, defaults to 101
to ensure all orders are processed.
- algorithm - optional parameter providing an algorithm. defaults
to :py:class:`zipline.test.algorithms.TestAlgorithm`
- trade_source - optional parameter to specify trades, if present.
If not present :py:class:`zipline.sources.SpecificEquityTrades`
is the source, with daily frequency in trades.
- slippage: optional parameter that configures the
:py:class:`zipline.gens.tradingsimulation.TransactionSimulator`.
Expects an object with a simulate mehod, such as
:py:class:`zipline.gens.tradingsimulation.FixedSlippage`.
:py:mod:`zipline.finance.trading`
"""
assert isinstance(config, dict)
try:
sid_list = config['sid_list']
except KeyError:
try:
sid_list = [config['sid']]
except KeyError:
raise Exception("simfactory create_test_zipline() requires "
"argument 'sid_list' or 'sid'")
concurrent_trades = config.get('concurrent_trades', False)
if 'order_count' in config:
order_count = config['order_count']
else:
order_count = 100
if 'order_amount' in config:
order_amount = config['order_amount']
else:
order_amount = 100
# -------------------
# Create the Algo
# -------------------
if 'algorithm' in config:
test_algo = config['algorithm']
else:
test_algo = TestAlgorithm(
sid_list[0],
order_amount,
order_count,
sim_params=config.get('sim_params',
factory.create_simulation_parameters()),
slippage=config.get('slippage'),
identifiers=sid_list
)
# -------------------
# Trade Source
# -------------------
if 'trade_source' in config:
trade_source = config['trade_source']
else:
trade_source = factory.create_daily_trade_source(
sid_list,
test_algo.sim_params,
test_algo.trading_environment,
concurrent=concurrent_trades,
)
if trade_source:
test_algo.set_sources([trade_source])
# -------------------
# Benchmark source
# -------------------
test_algo.benchmark_return_source = config.get('benchmark_source', None)
# ------------------
# generator/simulator
sim = test_algo.get_generator()
return sim
class TestClosePosAlgo(TestCase):
def setUp(self):
self.days = TradingEnvironment().trading_days
self.index = [self.days[0], self.days[1], self.days[2]]
self.panel = pd.Panel({
1:
pd.DataFrame(
{
'price': [1, 2, 4],
'volume': [1e9, 0, 0],
'type': [
DATASOURCE_TYPE.TRADE, DATASOURCE_TYPE.TRADE,
DATASOURCE_TYPE.CLOSE_POSITION
]
},
index=self.index)
})
def test_close_position_equity(self):
metadata = {
1: {
'symbol': 'TEST',
'asset_type': 'equity',
'end_date': self.days[3]
}
}
self.algo = TestAlgorithm(sid=1,
amount=1,
order_count=1,
instant_fill=True,
commission=PerShare(0),
asset_metadata=metadata)
self.data = DataPanelSource(self.panel)
# Check results
expected_positions = [1, 1, 0]
expected_pnl = [0, 1, 2]
results = self.run_algo()
self.check_algo_pnl(results, expected_pnl)
self.check_algo_positions(results, expected_positions)
def test_close_position_future(self):
metadata = {
1: {
'symbol': 'TEST',
'asset_type': 'future',
'notice_date': self.days[2],
'expiration_date': self.days[3]
}
}
self.algo = TestAlgorithm(sid=1,
amount=1,
order_count=1,
instant_fill=True,
commission=PerShare(0),
asset_metadata=metadata)
self.data = DataPanelSource(self.panel)
# Check results
expected_positions = [1, 1, 0]
expected_pnl = [0, 1, 2]
results = self.run_algo()
self.check_algo_pnl(results, expected_pnl)
self.check_algo_positions(results, expected_positions)
def run_algo(self):
results = self.algo.run(self.data)
return results
def check_algo_pnl(self, results, expected_pnl):
for i, pnl in enumerate(results.pnl):
self.assertEqual(pnl, expected_pnl[i])
def check_algo_positions(self, results, expected_positions):
for i, amount in enumerate(results.positions):
if amount:
actual_position = amount[0]['amount']
else:
actual_position = 0
self.assertEqual(actual_position, expected_positions[i])
def create_test_zipline(**config):
"""
:param config: A configuration object that is a dict with:
- sid - an integer, which will be used as the security ID.
- order_count - the number of orders the test algo will place,
defaults to 100
- order_amount - the number of shares per order, defaults to 100
- trade_count - the number of trades to simulate, defaults to 101
to ensure all orders are processed.
- algorithm - optional parameter providing an algorithm. defaults
to :py:class:`zipline.test.algorithms.TestAlgorithm`
- trade_source - optional parameter to specify trades, if present.
If not present :py:class:`zipline.sources.SpecificEquityTrades`
is the source, with daily frequency in trades.
- slippage: optional parameter that configures the
:py:class:`zipline.gens.tradingsimulation.TransactionSimulator`.
Expects an object with a simulate mehod, such as
:py:class:`zipline.gens.tradingsimulation.FixedSlippage`.
:py:mod:`zipline.finance.trading`
- transforms: optional parameter that provides a list
of StatefulTransform objects.
"""
assert isinstance(config, dict)
sid_list = config.get('sid_list')
if not sid_list:
sid = config.get('sid')
sid_list = [sid]
concurrent_trades = config.get('concurrent_trades', False)
if 'order_count' in config:
order_count = config['order_count']
else:
order_count = 100
if 'order_amount' in config:
order_amount = config['order_amount']
else:
order_amount = 100
if 'trade_count' in config:
trade_count = config['trade_count']
else:
# to ensure all orders are filled, we provide one more
# trade than order
trade_count = 101
#-------------------
# Create the Algo
#-------------------
if 'algorithm' in config:
test_algo = config['algorithm']
else:
test_algo = TestAlgorithm(sid,
order_amount,
order_count,
sim_params=config.get(
'sim_params',
factory.create_simulation_parameters()))
#-------------------
# Trade Source
#-------------------
if 'trade_source' in config:
trade_source = config['trade_source']
else:
trade_source = factory.create_daily_trade_source(
sid_list,
trade_count,
test_algo.sim_params,
concurrent=concurrent_trades)
if trade_source:
test_algo.set_sources([trade_source])
#-------------------
# Benchmark source
#-------------------
test_algo.benchmark_return_source = config.get('benchmark_source', None)
#-------------------
# Transforms
#-------------------
transforms = config.get('transforms', None)
if transforms is not None:
test_algo.set_transforms(transforms)
#-------------------
# Slippage
# ------------------
slippage = config.get('slippage', None)
if slippage is not None:
test_algo.set_slippage(slippage)
# ------------------
# generator/simulator
sim = test_algo.get_generator()
return sim
class TestClosePosAlgo(TestCase):
def setUp(self):
self.days = TradingEnvironment().trading_days
self.index = [self.days[0], self.days[1], self.days[2]]
self.panel = pd.Panel({1: pd.DataFrame({
'price': [1, 2, 4], 'volume': [1e9, 0, 0],
'type': [DATASOURCE_TYPE.TRADE,
DATASOURCE_TYPE.TRADE,
DATASOURCE_TYPE.CLOSE_POSITION]},
index=self.index)
})
def test_close_position_equity(self):
metadata = {1: {'symbol': 'TEST',
'asset_type': 'equity',
'end_date': self.days[3]}}
self.algo = TestAlgorithm(sid=1, amount=1, order_count=1,
instant_fill=True, commission=PerShare(0),
asset_metadata=metadata)
self.data = DataPanelSource(self.panel)
# Check results
expected_positions = [1, 1, 0]
expected_pnl = [0, 1, 2]
results = self.run_algo()
self.check_algo_pnl(results, expected_pnl)
self.check_algo_positions(results, expected_positions)
def test_close_position_future(self):
metadata = {1: {'symbol': 'TEST',
'asset_type': 'future',
'notice_date': self.days[2],
'expiration_date': self.days[3]}}
self.algo = TestAlgorithm(sid=1, amount=1, order_count=1,
instant_fill=True, commission=PerShare(0),
asset_metadata=metadata)
self.data = DataPanelSource(self.panel)
# Check results
expected_positions = [1, 1, 0]
expected_pnl = [0, 1, 2]
results = self.run_algo()
self.check_algo_pnl(results, expected_pnl)
self.check_algo_positions(results, expected_positions)
def run_algo(self):
results = self.algo.run(self.data)
return results
def check_algo_pnl(self, results, expected_pnl):
for i, pnl in enumerate(results.pnl):
self.assertEqual(pnl, expected_pnl[i])
def check_algo_positions(self, results, expected_positions):
for i, amount in enumerate(results.positions):
if amount:
actual_position = amount[0]['amount']
else:
actual_position = 0
self.assertEqual(actual_position, expected_positions[i])
def create_test_zipline(**config):
"""
:param config: A configuration object that is a dict with:
- sid - an integer, which will be used as the asset ID.
- order_count - the number of orders the test algo will place,
defaults to 100
- order_amount - the number of shares per order, defaults to 100
- trade_count - the number of trades to simulate, defaults to 101
to ensure all orders are processed.
- algorithm - optional parameter providing an algorithm. defaults
to :py:class:`zipline.test.algorithms.TestAlgorithm`
- trade_source - optional parameter to specify trades, if present.
If not present :py:class:`zipline.sources.SpecificEquityTrades`
is the source, with daily frequency in trades.
- slippage: optional parameter that configures the
:py:class:`zipline.gens.tradingsimulation.TransactionSimulator`.
Expects an object with a simulate mehod, such as
:py:class:`zipline.gens.tradingsimulation.FixedSlippage`.
:py:mod:`zipline.finance.trading`
"""
assert isinstance(config, dict)
try:
sid_list = config['sid_list']
except KeyError:
try:
sid_list = [config['sid']]
except KeyError:
raise Exception("simfactory create_test_zipline() requires "
"argument 'sid_list' or 'sid'")
concurrent_trades = config.get('concurrent_trades', False)
order_count = config.get('order_count', 100)
order_amount = config.get('order_amount', 100)
# # 更改为A股交易日历
trading_calendar = config.get('trading_calendar', get_calendar())
# -------------------
# Create the Algo
# -------------------
if 'algorithm' in config:
test_algo = config['algorithm']
else:
test_algo = TestAlgorithm(sid_list[0],
order_amount,
order_count,
sim_params=config.get(
'sim_params',
factory.create_simulation_parameters()),
trading_calendar=trading_calendar,
slippage=config.get('slippage'),
identifiers=sid_list)
# -------------------
# Trade Source
# -------------------
if 'skip_data' not in config:
if 'trade_source' in config:
trade_source = config['trade_source']
else:
trade_source = factory.create_daily_trade_source(
sid_list,
test_algo.sim_params,
test_algo.trading_environment,
trading_calendar,
concurrent=concurrent_trades,
)
trades_by_sid = {}
for trade in trade_source:
if trade.sid not in trades_by_sid:
trades_by_sid[trade.sid] = []
trades_by_sid[trade.sid].append(trade)
data_portal = create_data_portal_from_trade_history(
config['env'].asset_finder, trading_calendar, config['tempdir'],
config['sim_params'], trades_by_sid)
test_algo.data_portal = data_portal
# -------------------
# Benchmark source
# -------------------
test_algo.benchmark_return_source = config.get('benchmark_source', None)
# ------------------
# generator/simulator
sim = test_algo.get_generator()
return sim
