| Overall Statistics |
|
Total Trades 10 Average Win 0% Average Loss -0.01% Compounding Annual Return -2.513% Drawdown 0.000% Expectancy -1 Net Profit -0.033% Sharpe Ratio -2426.61 Loss Rate 100% Win Rate 0% Profit-Loss Ratio 0 Alpha -0.016 Beta -0.002 Annual Standard Deviation 0 Annual Variance 0 Information Ratio -70.456 Tracking Error 0 Treynor Ratio 10.492 Total Fees $32.53 |
# 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 clr import AddReference
AddReference("System")
AddReference("QuantConnect.Algorithm")
AddReference("QuantConnect.Common")
from System import *
from QuantConnect import *
from QuantConnect.Algorithm import *
from QuantConnect.Securities import *
from QuantConnect.Data.Market import *
from QuantConnect.Orders import *
from datetime import datetime
### <summary>
### Demonstration of the Market On Close order for US Equities.
### </summary>
### <meta name="tag" content="trading and orders" />
### <meta name="tag" content="placing orders" />
class MarketOnOpenOnCloseAlgorithm(QCAlgorithm):
def Initialize(self):
'''Initialise the data and resolution required, as well as the cash and start-end dates for your algorithm. All algorithms must initialized.'''
self.SetStartDate(2013,10,07) #Set Start Date
self.SetEndDate(2013,10,11) #Set End Date
self.SetCash(100000) #Set Strategy Cash
# Find more symbols here: http://quantconnect.com/data
self.equity = self.AddEquity("SPY", Resolution.Second, fillDataForward = True, extendedMarketHours = True)
self.__submittedMarketOnCloseToday = False
self.__last = datetime.min
def OnData(self, data):
'''OnData event is the primary entry point for your algorithm. Each new data point will be pumped in here.'''
if self.Time.date() != self.__last.date(): # each morning submit a market on open order
self.__submittedMarketOnCloseToday = False
self.SetHoldings("SPY", 1)
self.__last = self.Time
if not self.__submittedMarketOnCloseToday and self.equity.Exchange.ExchangeOpen: # once the exchange opens submit a market on close order
self.__submittedMarketOnCloseToday = True
self.SetHoldings("SPY", 0)
def OnOrderEvent(self, fill):
order = self.Transactions.GetOrderById(fill.OrderId)
self.Log("{0} - {1}:TEST: {2}".format(self.Time, order.Type, fill))