Jhonathan Abreu
546afd2a61
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* Changed default async to true and passed target.Tag * Make execution models place orders asynchronously if specified * Add unit tests * Execution model default to asynchronous orders. Also, minor fixes for tickets remaining fill quantity potential race conditions * Add SecurityHolding.UnrealizedQuantity property It gets the holding quantity the security will have once all open orders are filled. Added for thread safety reasons when execution models place asynchronous orders and need to calculate the actual quantity needed to reach the target of there are open orders * Some cleanup * Adjust projected holdings quantity on splits * Minor fix * More changes and cleanup * Minor fix * Improvements for thread safety * Add IOrderProvider.GetProjectedHoldings to get projected holdings atomically * Minor unit tests fix * Add ProjectedHoldings DTO class * Address peer review --------- Co-authored-by: arthiondaena <arthiondaena@gmail.com>
61 lines
3.1 KiB
Python
61 lines
3.1 KiB
Python
# QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
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# Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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from AlgorithmImports import *
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class SpreadExecutionModel(ExecutionModel):
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'''Execution model that submits orders while the current spread is tight.
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Note this execution model will not work using Resolution.DAILY since Exchange.exchange_open will be false, suggested resolution is Minute
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'''
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def __init__(self, accepting_spread_percent=0.005, asynchronous=True):
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'''Initializes a new instance of the SpreadExecutionModel class'''
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super().__init__(asynchronous)
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self.targets_collection = PortfolioTargetCollection()
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# Gets or sets the maximum spread compare to current price in percentage.
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self.accepting_spread_percent = Math.abs(accepting_spread_percent)
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def execute(self, algorithm, targets):
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'''Executes market orders if the spread percentage to price is in desirable range.
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Args:
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algorithm: The algorithm instance
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targets: The portfolio targets'''
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# update the complete set of portfolio targets with the new targets
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self.targets_collection.add_range(targets)
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# for performance we check count value, OrderByMarginImpact and ClearFulfilled are expensive to call
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if not self.targets_collection.is_empty:
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for target in self.targets_collection.order_by_margin_impact(algorithm):
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symbol = target.symbol
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# calculate remaining quantity to be ordered
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unordered_quantity = OrderSizing.get_unordered_quantity(algorithm, target)
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# check order entry conditions
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if unordered_quantity != 0:
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# get security information
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security = algorithm.securities[symbol]
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if self.spread_is_favorable(security):
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algorithm.market_order(symbol, unordered_quantity, self.asynchronous, target.tag)
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self.targets_collection.clear_fulfilled(algorithm)
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def spread_is_favorable(self, security):
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'''Determines if the spread is in desirable range.'''
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# Price has to be larger than zero to avoid zero division error, or negative price causing the spread percentage < 0 by error
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# Has to be in opening hours of exchange to avoid extreme spread in OTC period
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return security.exchange.exchange_open \
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and security.price > 0 and security.ask_price > 0 and security.bid_price > 0 \
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and (security.ask_price - security.bid_price) / security.price <= self.accepting_spread_percent
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