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