| Overall Statistics |
|
Total Trades 30 Average Win 0.21% Average Loss -0.01% Compounding Annual Return 107.719% Drawdown 0% Expectancy 9.151 Net Profit 1.615% Sharpe Ratio 12.26 Loss Rate 33% Win Rate 67% Profit-Loss Ratio 14.23 Alpha 0.343 Beta 0.581 Annual Standard Deviation 0.047 Annual Variance 0.002 Information Ratio 4.661 Tracking Error 0.037 Treynor Ratio 0.995 Total Fees $39.98 |
# 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(2019,2,15)
self.SetEndDate(2019,2,22)
self.backtestSymbolsPerDay = {}
self.current_universe = []
self.UniverseSettings.Resolution = Resolution.Daily
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/ad2mliixbniuz4y/lean_test1.csv?dl=1")
# if we have a file for today, return symbols, else leave universe unchanged
self.current_universe = str.rstrip(',').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/ad2mliixbniuz4y/lean_test1.csv?dl=1", headers)
for line in str.splitlines():
data = line.split(',')
self.Log("data = {0}".format(data))
if len(data[2]) == 0:
data = data[:2]
self.backtestSymbolsPerDay[data[0]] = data[1:]
index = date.strftime("%Y%m%d")
self.current_universe = self.backtestSymbolsPerDay.get(index, self.current_universe)
self.Log("universe {0}".format(self.current_universe))
return self.current_universe
def OnData(self, slice):
if slice.Bars.Count == 0: return
if self.changes is None: return
# start fresh
self.Liquidate()
percentage = 1 / slice.Bars.Count
for tradeBar in slice.Bars.Values:
self.Log("trade bar {0}".format(tradeBar))
self.SetHoldings(tradeBar.Symbol, percentage)
# reset changes
self.changes = None
def OnSecuritiesChanged(self, changes):
self.changes = changes