def __init__(self,
data_frequency,
equity_slippage=None,
future_slippage=None,
equity_commission=None,
future_commission=None,
cancel_policy=None):
# these orders are aggregated by asset
self.open_orders = defaultdict(list)
# keep a dict of orders by their own id
self.orders = {}
# holding orders that have come in since the last event.
self.new_orders = []
self.current_dt = None
self.max_shares = int(1e+11)
self.slippage_models = {
Equity: equity_slippage or VolumeShareSlippage(),
Future: future_slippage or VolumeShareSlippage(),
}
self.commission_models = {
Equity:
equity_commission or PerShare(),
Future:
future_commission
or PerTrade(cost=DEFAULT_FUTURE_COST_PER_TRADE, ),
}
self.data_frequency = data_frequency
self.cancel_policy = cancel_policy if cancel_policy else NeverCancel()
def __init__(self, data_frequency, equity_slippage=None,
future_slippage=None, equity_commission=None,
future_commission=None, cancel_policy=None, stock_exchange='NYSE'):
# these orders are aggregated by asset
self.open_orders = defaultdict(list)
# keep a dict of orders by their own id
self.orders = {}
# holding orders that have come in since the last event.
self.new_orders = []
self.current_dt = None
self.max_shares = int(1e+11)
self.slippage_models = {
Equity: equity_slippage or FixedBasisPointsSlippage(),
Future: future_slippage or VolatilityVolumeShare(
volume_limit=DEFAULT_FUTURE_VOLUME_SLIPPAGE_BAR_LIMIT,
),
}
self.commission_models = {
Equity: equity_commission or PerShare(),
Future: future_commission or PerContract(
cost=DEFAULT_PER_CONTRACT_COST,
exchange_fee=FUTURE_EXCHANGE_FEES_BY_SYMBOL,
),
}
self.data_frequency = data_frequency
self.cancel_policy = cancel_policy if cancel_policy else NeverCancel()
def __init__(self,
data_frequency,
asset_finder,
slippage_func=None,
commission=None,
cancel_policy=None):
# these orders are aggregated by sid
self.open_orders = defaultdict(list)
# keep a dict of orders by their own id
self.orders = {}
# all our legacy order management code works with integer sids.
# this lets us convert those to assets when needed. ideally, we'd just
# revamp all the legacy code to work with assets.
self.asset_finder = asset_finder
# holding orders that have come in since the last event.
self.new_orders = []
self.current_dt = None
self.max_shares = int(1e+11)
self.slippage_func = slippage_func or VolumeShareSlippage()
self.commission = commission or PerShare()
self.data_frequency = data_frequency
self.cancel_policy = cancel_policy if cancel_policy else NeverCancel()
def test_blotter_never_cancel(self):
blotter = SimulationBlotter(cancel_policy=NeverCancel())
blotter.order(self.asset_24, 100, MarketOrder())
self.assertEqual(len(blotter.new_orders), 1)
self.assertEqual(blotter.new_orders[0].status, ORDER_STATUS.OPEN)
blotter.execute_cancel_policy(BAR)
self.assertEqual(blotter.new_orders[0].status, ORDER_STATUS.OPEN)
blotter.execute_cancel_policy(SESSION_END)
self.assertEqual(blotter.new_orders[0].status, ORDER_STATUS.OPEN)
def get_blotter(self):
slippage_func = VolumeShareSlippage(
volume_limit=1,
price_impact=0
)
blotter = MyBlotter(
data_frequency=self.sim_params.data_frequency,
asset_finder=self.env.asset_finder,
slippage_func=slippage_func,
# https://github.com/quantopian/zipline/blob/3350227f44dcf36b6fe3c509dcc35fe512965183/tests/test_blotter.py#L136
cancel_policy=NeverCancel()
)
return blotter
def test_blotter_never_cancel(self):
blotter = Blotter('minute', self.env.asset_finder,
cancel_policy=NeverCancel())
blotter.order(blotter.asset_finder.retrieve_asset(24), 100,
MarketOrder())
self.assertEqual(len(blotter.new_orders), 1)
self.assertEqual(blotter.new_orders[0].status, ORDER_STATUS.OPEN)
blotter.execute_cancel_policy(BAR)
self.assertEqual(blotter.new_orders[0].status, ORDER_STATUS.OPEN)
blotter.execute_cancel_policy(DAY_END)
self.assertEqual(blotter.new_orders[0].status, ORDER_STATUS.OPEN)
def __init__(self,
data_frequency,
asset_finder,
equity_slippage=None,
future_slippage=None,
equity_commission=None,
future_commission=None,
cancel_policy=None):
# these orders are aggregated by sid
self.open_orders = defaultdict(list)
# keep a dict of orders by their own id
self.orders = {}
# all our legacy order management code works with integer sids.
# this lets us convert those to assets when needed. ideally, we'd just
# revamp all the legacy code to work with assets.
self.asset_finder = asset_finder
# holding orders that have come in since the last event.
self.new_orders = []
self.current_dt = None
self.max_shares = int(1e+11)
self.slippage_models = {
Equity: equity_slippage or VolumeShareSlippage(),
Future: future_slippage or VolumeShareSlippage(),
}
self.commission_models = {
Equity:
equity_commission or PerShare(),
Future:
future_commission
or PerTrade(cost=DEFAULT_FUTURE_COST_PER_TRADE, ),
}
self.data_frequency = data_frequency
self.cancel_policy = cancel_policy if cancel_policy else NeverCancel()
def test_never_cancel(self):
cancel_policy = NeverCancel()
self.assertFalse(cancel_policy.should_cancel(DAY_END))
self.assertFalse(cancel_policy.should_cancel(BAR))
def __init__(self, cancel_policy=None):
self.cancel_policy = cancel_policy if cancel_policy else NeverCancel()
self.current_dt = None
def __init__(self, cancel_policy=None):
self.cancel_policy = cancel_policy if cancel_policy else NeverCancel()
self.current_dt = None
self.metrics_tracker = None
def test_never_cancel(self):
cancel_policy = NeverCancel()
self.assertFalse(cancel_policy.should_cancel(SESSION_END))
self.assertFalse(cancel_policy.should_cancel(BAR))
return bm, tr
def analyze(context=None, results=None):
ax1 = plt.subplot(211)
results.portfolio_value.plot(ax=ax1)
ax1.set_ylabel('Portfolio value (USD)')
ax2 = plt.subplot(212, sharex=ax1)
results.AAPL.plot(ax=ax2)
ax2.set_ylabel('AAPL price (USD)')
plt.gcf().set_size_inches(18, 8)
plt.show()
cal = SHSZExchangeCalendar()
cancel_policy = NeverCancel()
blotter = SimulationBlotter(cancel_policy=cancel_policy)
trading_environment = TradingEnvironment(load=load_t,
bm_symbol='^HSI',
exchange_tz='Asia/Shanghai',
trading_calendar=cal)
sim_params = create_simulation_parameters(
start=pd.to_datetime("2016-01-01 00:00:00").tz_localize("Asia/Shanghai"),
end=pd.to_datetime("2016-09-21 00:00:00").tz_localize("Asia/Shanghai"),
data_frequency="daily",
emission_rate="daily",
trading_calendar=cal)
algor_obj = TradingAlgorithm(initialize=initialize,
handle_data=handle_data,
sim_params=sim_params,
def __init__(self, data_frequency, cancel_policy=None):
self.data_frequency = data_frequency
self.cancel_policy = cancel_policy if cancel_policy else NeverCancel()
self.current_dt = None
def test_never_cancel(test_input):
cancel_policy = NeverCancel()
assert not cancel_policy.should_cancel(test_input)
def __init__(self, sim_params, cancel_policy=None):
self.cancel_policy = cancel_policy if cancel_policy else NeverCancel()
self.current_dt = None
self.sim_params = sim_params
