Overall Statistics
Total Trades
1
Average Win
0%
Average Loss
0%
Compounding Annual Return
4.407%
Drawdown
20.200%
Expectancy
0
Net Profit
5.535%
Sharpe Ratio
0.343
Loss Rate
0%
Win Rate
0%
Profit-Loss Ratio
0
Alpha
0.234
Beta
-8.841
Annual Standard Deviation
0.166
Annual Variance
0.028
Information Ratio
0.223
Tracking Error
0.166
Treynor Ratio
-0.006
Total Fees
$1.84
from clr import AddReference
AddReference("System")
AddReference("QuantConnect.Algorithm")
AddReference("QuantConnect.Common")

from System import *
from QuantConnect import *
from QuantConnect.Algorithm import *

import numpy as np
import decimal as d
from datetime import timedelta, datetime

class CustomChartingAlgorithm(QCAlgorithm):
    def Initialize(self):
        self.SetStartDate(2018,1,1)
        self.SetEndDate(2019,4,1)
        self.SetCash(100000)
        self.AddEquity("SPY", Resolution.Daily)

        # In your initialize method:
        # Chart - Master Container for the Chart:
        stockPlot = Chart("Trade Plot")
        
        # On the Trade Plotter Chart we want 3 series: trades and price:
        stockPlot.AddSeries(Series("Buy", SeriesType.Scatter, 0))
        stockPlot.AddSeries(Series("Sell", SeriesType.Scatter, 0))
        stockPlot.AddSeries(Series("Price", SeriesType.Line, 0))
        self.AddChart(stockPlot)

        self.fastMA = 0
        self.slowMA = 0
        self.lastPrice = 0
        self.resample = datetime.min
        self.resamplePeriod = (self.EndDate - self.StartDate) / 2000

    def OnData(self, slice):
        if slice["SPY"] is None: return

        self.lastPrice = slice["SPY"].Close
        if self.fastMA == 0: self.fastMA = self.lastPrice
        if self.slowMA == 0: self.slowMA = self.lastPrice
        self.fastMA = (0.01 * self.lastPrice) + (0.99 * self.fastMA)
        self.slowMA = (0.001 * self.lastPrice) + (0.999 * self.slowMA)


        if self.Time > self.resample:
            self.resample = self.Time  + self.resamplePeriod
           
        # On the 5th days when not invested buy:
        if not self.Portfolio.Invested and self.Time.day % 13 == 0:
            self.Order("SPY", (int)(self.Portfolio.MarginRemaining / self.lastPrice))
            self.Plot("Trade Plot", "Buy", self.lastPrice)
        elif self.Time.day % 21 == 0 and self.Portfolio.Invested:
            self.Plot("Trade Plot", "Sell", self.lastPrice)
            self.Liquidate()

    def OnEndOfDay(self):
       #Log the end of day prices:
       self.Plot("Trade Plot", "Price", self.lastPrice)
# same error as degue!!!
# should write to QC for checking!!!


from clr import AddReference
AddReference("System")
AddReference("QuantConnect.Algorithm")
AddReference("QuantConnect.Common")

from System import *
from QuantConnect import *
from QuantConnect.Algorithm import *
from QuantConnect.Indicators import *
from QuantConnect.Data.Market import TradeBar

class RollingWindowAlgorithm(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(2018,1,1)  #Set Start Date
        self.SetEndDate(2019,4,1)    #Set End Date
        self.SetCash(100000)           #Set Strategy Cash
        # Find more symbols here: http://quantconnect.com/data
        self.AddEquity("SPY", Resolution.Daily)

        # Creates a Rolling Window indicator to keep the 2 TradeBar
        self.window = RollingWindow[TradeBar](2)    # For other security types, use QuoteBar

        # Creates an indicator and adds to a rolling window when it is updated
        self.sma = self.SMA("SPY", 5)
        self.sma.Updated += self.SmaUpdated
        self.smaWin = RollingWindow[IndicatorDataPoint](5)

        # zc add on
        stockPlot = Chart("Trade Plot")
        stockPlot.AddSeries(Series("Price", SeriesType.Line, 0))
        self.AddChart(stockPlot)
        self.lastPrice = 0
        
    def SmaUpdated(self, sender, updated):
        '''Adds updated values to rolling window'''
        self.smaWin.Add(updated)


    def OnData(self, data):
        '''OnData event is the primary entry point for your algorithm. Each new data point will be pumped in here.'''

        # Add SPY TradeBar in rollling window
        self.window.Add(data["SPY"])

        # Wait for windows to be ready.
        if not (self.window.IsReady and self.smaWin.IsReady): return

        currBar = self.window[0]                     # Current bar had index zero.
        pastBar = self.window[1]                     # Past bar has index one.
        self.Log("Price: {0} -> {1} ... {2} -> {3}".format(pastBar.Time, pastBar.Close, currBar.Time, currBar.Close))
        
        # zc add on
        self.lastPrice = currBar.Close
        self.Plot("Trade Plot", "Price", self.lastPrice)

        currSma = self.smaWin[0]                     # Current SMA had index zero.
        pastSma = self.smaWin[self.smaWin.Count-1]   # Oldest SMA has index of window count minus 1.
        self.Log("SMA:   {0} -> {1} ... {2} -> {3}".format(pastSma.Time, pastSma.Value, currSma.Time, currSma.Value))

        if not self.Portfolio.Invested and currSma.Value > pastSma.Value:
            self.SetHoldings("SPY", 1)