# 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>
### Demonstrate the usage of the BrokerageModel property to help improve backtesting
### accuracy through simulation of a specific brokerage's rules around restrictions
### on submitting orders as well as fee structure.
### </summary>
### <meta name="tag" content="trading and orders" />
### <meta name="tag" content="brokerage models" />
class BrokerageModelAlgorithm(QCAlgorithm):
 def initialize(self):

 self.set_cash(100000) # Set Strategy Cash
 self.set_start_date(2013,10,7) # Set Start Date
 self.set_end_date(2013,10,11) # Set End Date
 self.add_equity("SPY", Resolution.SECOND)
 
 # there's two ways to set your brokerage model. The easiest would be to call
 # self.set_brokerage_model( BrokerageName ) # BrokerageName is an enum
 # self.set_brokerage_model(BrokerageName.INTERACTIVE_BROKERS_BROKERAGE)
 # self.set_brokerage_model(BrokerageName.DEFAULT)

 # the other way is to call SetBrokerageModel( IBrokerageModel ) with your
 # own custom model. I've defined a simple extension to the default brokerage
 # model to take into account a requirement to maintain 500 cash in the account at all times
 self.set_brokerage_model(MinimumAccountBalanceBrokerageModel(self,500.00))
 self.last = 1 
 
 def on_data(self, slice):
 # Simple buy and hold template
 if not self.portfolio.invested:
 self.set_holdings("SPY", self.last)
 if self.portfolio["SPY"].quantity == 0:
 # each time we fail to purchase we'll decrease our set holdings percentage
 self.debug(str(self.time) + " - Failed to purchase stock")
 self.last *= 0.95
 else:
 self.debug("{} - Purchased Stock @ SetHoldings( {} )".format(self.time, self.last))


class MinimumAccountBalanceBrokerageModel(DefaultBrokerageModel):
 '''Custom brokerage model that requires clients to maintain a minimum cash balance'''
 def __init__(self, algorithm, minimum_account_balance):
 self.algorithm = algorithm
 self.minimum_account_balance = minimum_account_balance
 
 def can_submit_order(self,security, order, message):
 '''Prevent orders which would bring the account below a minimum cash balance'''
 message = None
 # we want to model brokerage requirement of minimum_account_balance cash value in account
 order_cost = order.get_value(security)
 cash = self.algorithm.portfolio.cash
 cash_after_order = cash - order_cost
 if cash_after_order < self.minimum_account_balance:
 # return a message describing why we're not allowing this order
 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))
 self.algorithm.error(str(message))
 return False
 return True