| Overall Statistics |
|
Total Trades 2785 Average Win 1.81% Average Loss -1.42% Compounding Annual Return 4.887% Drawdown 46.400% Expectancy 0.045 Net Profit 61.482% Sharpe Ratio 0.28 Loss Rate 54% Win Rate 46% Profit-Loss Ratio 1.27 Alpha 0.082 Beta -0.055 Annual Standard Deviation 0.268 Annual Variance 0.072 Information Ratio -0.156 Tracking Error 0.304 Treynor Ratio -1.353 Total Fees $122654.21 |
# 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 QCAlgorithm
from QuantConnect.Data.UniverseSelection import *
import base64
### <summary>
### In this algortihm we show how you can easily use the universe selection feature to fetch symbols
### to be traded using the BaseData custom data system in combination with the AddUniverse{T} method.
### AddUniverse{T} requires a function that will return the symbols to be traded.
### </summary>
### <meta name="tag" content="using data" />
### <meta name="tag" content="universes" />
### <meta name="tag" content="custom universes" />
class DropboxUniverseSelectionAlgorithm(QCAlgorithm):
def Initialize(self):
self.SetStartDate(2009,7,2)
self.SetEndDate(2019,7,15)
self.SetCash(100000)
self.SetBenchmark("SPY")
self.backtestSymbolsPerDay = {}
self.current_universe = []
self.UniverseSettings.Resolution = Resolution.Minute
self.UniverseSettings.Leverage = 2
self.UniverseSettings.DataNormalizationMode = DataNormalizationMode.Raw
self.AddUniverse("my-dropbox-universe", self.selector)
def selector(self, date):
# handle live mode file format
if self.LiveMode:
# fetch the file from dropbox
str = self.Download("https://www.dropbox.com/s/9w8zdr7qs1s7tu7/lean_export.csv?dl=1")
# if we have a file for today, return symbols, else leave universe unchanged
self.current_universe = str.split(',') if len(str) > 0 else self.current_universe
return self.current_universe
# backtest - first cache the entire file
if len(self.backtestSymbolsPerDay) == 0:
# No need for headers for authorization with dropbox, these two lines are for example purposes
byteKey = base64.b64encode("UserName:Password".encode('ASCII'))
# The headers must be passed to the Download method as dictionary
headers = { 'Authorization' : f'Basic ({byteKey.decode("ASCII")})' }
str = self.Download("https://www.dropbox.com/s/9w8zdr7qs1s7tu7/lean_export.csv?dl=1", headers)
for line in str.splitlines():
data = line.split(',')
self.backtestSymbolsPerDay[data[0]] = data[1:]
index = date.strftime("%Y%m%d")
self.current_universe = self.backtestSymbolsPerDay.get(index, self.current_universe)
return self.current_universe
def OnData(self, slice):
if self.changes is None: return
for tradeBar in slice.Bars.Values:
self.Log('{0}'.format(tradeBar.Symbol))
if self.Securities[tradeBar.Symbol].Invested == False:
self.SetHoldings(tradeBar.Symbol, -2)
invested = [x.Key for x in self.Portfolio if x.Value.Invested]
for symbol in invested:
security_holding = self.Portfolio[symbol]
quantity = security_holding.Quantity
#self.Log('{0}'.format(quantity))
self.MarketOnCloseOrder(symbol, -quantity)
# reset changes
self.changes = None
def OnSecuritiesChanged(self, changes):
self.changes = changes