wehub-resource-sync
73 lines
3.7 KiB
Python
73 lines
3.7 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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### <summary>
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### Demonstrate the usage of the BrokerageModel property to help improve backtesting
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### accuracy through simulation of a specific brokerage's rules around restrictions
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### on submitting orders as well as fee structure.
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### </summary>
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### <meta name="tag" content="trading and orders" />
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### <meta name="tag" content="brokerage models" />
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class BrokerageModelAlgorithm(QCAlgorithm):
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def initialize(self):
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self.set_cash(100000) # Set Strategy Cash
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self.set_start_date(2013,10,7) # Set Start Date
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self.set_end_date(2013,10,11) # Set End Date
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self.add_equity("SPY", Resolution.SECOND)
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# there's two ways to set your brokerage model. The easiest would be to call
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# self.set_brokerage_model( BrokerageName ) # BrokerageName is an enum
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# self.set_brokerage_model(BrokerageName.INTERACTIVE_BROKERS_BROKERAGE)
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# self.set_brokerage_model(BrokerageName.DEFAULT)
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# the other way is to call SetBrokerageModel( IBrokerageModel ) with your
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# own custom model. I've defined a simple extension to the default brokerage
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# model to take into account a requirement to maintain 500 cash in the account at all times
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self.set_brokerage_model(MinimumAccountBalanceBrokerageModel(self,500.00))
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self.last = 1
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def on_data(self, slice):
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# Simple buy and hold template
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if not self.portfolio.invested:
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self.set_holdings("SPY", self.last)
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if self.portfolio["SPY"].quantity == 0:
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# each time we fail to purchase we'll decrease our set holdings percentage
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self.debug(str(self.time) + " - Failed to purchase stock")
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self.last *= 0.95
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else:
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self.debug("{} - Purchased Stock @ SetHoldings( {} )".format(self.time, self.last))
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class MinimumAccountBalanceBrokerageModel(DefaultBrokerageModel):
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'''Custom brokerage model that requires clients to maintain a minimum cash balance'''
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def __init__(self, algorithm, minimum_account_balance):
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self.algorithm = algorithm
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self.minimum_account_balance = minimum_account_balance
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def can_submit_order(self,security, order, message):
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'''Prevent orders which would bring the account below a minimum cash balance'''
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message = None
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# we want to model brokerage requirement of minimum_account_balance cash value in account
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order_cost = order.get_value(security)
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cash = self.algorithm.portfolio.cash
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cash_after_order = cash - order_cost
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if cash_after_order < self.minimum_account_balance:
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# return a message describing why we're not allowing this order
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message = BrokerageMessageEvent(BrokerageMessageType.WARNING, "InsufficientRemainingCapital", "Account must maintain a minimum of ${0} USD at all times. Order ID: {1}".format(self.minimum_account_balance, order.id))
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self.algorithm.error(str(message))
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return False
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return True
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