# QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
# Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
#
# 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 AlgorithmImports import *

### <summary>
### Demonstration of using custom buying power model in backtesting.
### QuantConnect allows you to model all orders as deeply and accurately as you need.
### </summary>
### <meta name="tag" content="trading and orders" />
### <meta name="tag" content="transaction fees and slippage" />
### <meta name="tag" content="custom buying power models" />
class CustomBuyingPowerModelAlgorithm(QCAlgorithm):
 '''Demonstration of using custom buying power model in backtesting.
 QuantConnect allows you to model all orders as deeply and accurately as you need.'''

 def initialize(self):
 self.set_start_date(2013,10,1) # Set Start Date
 self.set_end_date(2013,10,31) # Set End Date
 security = self.add_equity("SPY", Resolution.HOUR)
 self.spy = security.symbol

 # set the buying power model
 security.set_buying_power_model(CustomBuyingPowerModel())

 def on_data(self, slice):
 if self.portfolio.invested:
 return

 quantity = self.calculate_order_quantity(self.spy, 1)
 if quantity % 100 != 0:
 raise AssertionError(f'CustomBuyingPowerModel only allow quantity that is multiple of 100 and {quantity} was found')

 # We normally get insufficient buying power model, but the
 # CustomBuyingPowerModel always says that there is sufficient buying power for the orders
 self.market_order(self.spy, quantity * 10)


class CustomBuyingPowerModel(BuyingPowerModel):
 def get_maximum_order_quantity_for_target_buying_power(self, parameters):
 quantity = super().get_maximum_order_quantity_for_target_buying_power(parameters).quantity
 quantity = np.floor(quantity / 100) * 100
 return GetMaximumOrderQuantityResult(quantity)

 def has_sufficient_buying_power_for_order(self, parameters):
 return HasSufficientBuyingPowerForOrderResult(True)

 # Let's always return 0 as the maintenance margin so we avoid margin call orders
 def get_maintenance_margin(self, parameters):
 return MaintenanceMargin(0)

 # Override this as well because the base implementation calls GetMaintenanceMargin (overridden)
 # because in C# it wouldn't resolve the overridden Python method
 def get_reserved_buying_power_for_position(self, parameters):
 return parameters.result_in_account_currency(0)