# # Copyright 2015 Quantopian, Inc. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. from __future__ import division import abc import math from six import with_metaclass from zipline.finance.transaction import create_transaction SELL = 1 << 0 BUY = 1 << 1 STOP = 1 << 2 LIMIT = 1 << 3 class LiquidityExceeded(Exception): pass DEFAULT_VOLUME_SLIPPAGE_BAR_LIMIT = 0.025 class SlippageModel(with_metaclass(abc.ABCMeta)): """Abstract interface for defining a slippage model. """ def __init__(self): self._volume_for_bar = 0 @property def volume_for_bar(self): return self._volume_for_bar @abc.abstractproperty def process_order(self, data, order): """Process how orders get filled. Parameters ---------- data : BarData The data for the given bar. order : Order The order to simulate. Returns ------- execution_price : float The price to execute the trade at. execution_volume : int The number of shares that could be filled. This may not be all the shares ordered in which case the order will be filled over multiple bars. """ pass def simulate(self, data, asset, orders_for_asset): self._volume_for_bar = 0 volume = data.current(asset, "volume") if volume == 0: return # can use the close price, since we verified there's volume in this # bar. price = data.current(asset, "close") dt = data.current_dt for order in orders_for_asset: if order.open_amount == 0: continue order.check_triggers(price, dt) if not order.triggered: continue txn = None try: execution_price, execution_volume = \ self.process_order(data, order) if execution_price is not None: txn = create_transaction( order, data.current_dt, execution_price, execution_volume ) except LiquidityExceeded: break if txn: self._volume_for_bar += abs(txn.amount) yield order, txn def __call__(self, bar_data, asset, current_orders): return self.simulate(bar_data, asset, current_orders) class VolumeShareSlippage(SlippageModel): """Model slippage as a function of the volume of shares traded. """ def __init__(self, volume_limit=DEFAULT_VOLUME_SLIPPAGE_BAR_LIMIT, price_impact=0.1): self.volume_limit = volume_limit self.price_impact = price_impact super(VolumeShareSlippage, self).__init__() def __repr__(self): return """ {class_name}( volume_limit={volume_limit}, price_impact={price_impact}) """.strip().format(class_name=self.__class__.__name__, volume_limit=self.volume_limit, price_impact=self.price_impact) def process_order(self, data, order): volume = data.current(order.asset, "volume") max_volume = self.volume_limit * volume # price impact accounts for the total volume of transactions # created against the current minute bar remaining_volume = max_volume - self.volume_for_bar if remaining_volume < 1: # we can't fill any more transactions raise LiquidityExceeded() # the current order amount will be the min of the # volume available in the bar or the open amount. cur_volume = int(min(remaining_volume, abs(order.open_amount))) if cur_volume < 1: return None, None # tally the current amount into our total amount ordered. # total amount will be used to calculate price impact total_volume = self.volume_for_bar + cur_volume volume_share = min(total_volume / volume, self.volume_limit) price = data.current(order.asset, "close") simulated_impact = volume_share ** 2 \ * math.copysign(self.price_impact, order.direction) \ * price impacted_price = price + simulated_impact if order.limit: # this is tricky! if an order with a limit price has reached # the limit price, we will try to fill the order. do not fill # these shares if the impacted price is worse than the limit # price. return early to avoid creating the transaction. # buy order is worse if the impacted price is greater than # the limit price. sell order is worse if the impacted price # is less than the limit price if (order.direction > 0 and impacted_price > order.limit) or \ (order.direction < 0 and impacted_price < order.limit): return None, None return ( impacted_price, math.copysign(cur_volume, order.direction) ) class FixedSlippage(SlippageModel): """Model slippage as a fixed spread. Parameters ---------- spread : float, optional spread / 2 will be added to buys and subtracted from sells. """ def __init__(self, spread=0.0): self.spread = spread def process_order(self, data, order): price = data.current(order.asset, "close") return ( price + (self.spread / 2.0 * order.direction), order.amount )