Overall Statistics
Total Trades
26
Average Win
0.54%
Average Loss
-0.30%
Compounding Annual Return
22.059%
Drawdown
0.800%
Expectancy
0.298
Net Profit
1.151%
Sharpe Ratio
5.165
Probabilistic Sharpe Ratio
85.575%
Loss Rate
54%
Win Rate
46%
Profit-Loss Ratio
1.81
Alpha
0.214
Beta
-0.022
Annual Standard Deviation
0.041
Annual Variance
0.002
Information Ratio
0.902
Tracking Error
0.165
Treynor Ratio
-9.782
Total Fees
$26.00
Estimated Strategy Capacity
$750000.00
Lowest Capacity Asset
IPOC XFA956ZU3MUD
from datetime import datetime, date, time
from datetime import timedelta
import pandas as pd

class SymbolData:
    def __init__(self,algo,symbol):
        self.algo = algo
        self.symbol = symbol
        self.openPrice = -1   
        self.lowestPrice = -1
        self.ticket = None
        
        self.rsi1 = RelativeStrengthIndex( 14, MovingAverageType.Wilders)
        cons1 = TradeBarConsolidator(timedelta(minutes=15))
        self.algo.SubscriptionManager.AddConsolidator(symbol,cons1)
        self.algo.RegisterIndicator(symbol,self.rsi1,cons1)
        
        self.rsi2 = RelativeStrengthIndex(14, MovingAverageType.Wilders)
        cons2 = TradeBarConsolidator(timedelta(minutes=2))
        self.algo.SubscriptionManager.AddConsolidator(symbol,cons2)
        self.algo.RegisterIndicator(symbol,self.rsi2,cons2)
    def IsReady(self):
        return self.rsi1.IsReady and self.rsi2.IsReady
        
        
        
class TradeStrategyTest(QCAlgorithm):
    
   def Initialize(self):
        self.SetStartDate(2021,3, 1)  #Set Start Date
        self.SetEndDate(2021,3,21)    #Set End Date
        self.SetCash(30000)           #Set Strategy Cash
        self.SetWarmUp(210)
        
        self.expiry = self.Time
        
        
        
        # Set TimeZone
        self.SetTimeZone("America/New_York")
        
        # Add Equities
        tickers = ['OCGN', 'CLOV']

        # Add Equities from .csv file - UNDER TESTING NOT COMPLETE!!!!
        # Create a dataframe from csv
        #self.Equities = pd.read_csv('test.csv', delimiter=',')
        
       
        self.dataBySymbol = {}
        self.Equities = []
        # Set resoltuion for Equity data
        for Symbol in tickers:
            
            
            symbol = self.AddEquity(Symbol, Resolution.Second).Symbol
            self.dataBySymbol[symbol] = SymbolData(self,symbol)      
            self.Equities.append(symbol)
            
        # Set Fee Model
        for Symbol in self.Equities:
            
            
            self.Securities[Symbol].FeeModel = ConstantFeeModel(1.00)
        
   def OnData(self, data):
        if self.IsWarmingUp:return
        
        # Loop through our equities
        for Symbol in self.Equities:
          if data.ContainsKey(Symbol) and data[Symbol] is not None and self.dataBySymbol[Symbol].IsReady() :
            # Set local variables
            close = data.Bars[Symbol].Close
            quantity = self.CalculateOrderQuantity(Symbol,1*0.2)
            AskPrice = self.Securities[Symbol].AskPrice
            BidPrice = self.Securities[Symbol].BidPrice
            Spread = (AskPrice - BidPrice)
            RSI1 = self.dataBySymbol[Symbol].rsi1.Current.Value
            RSI2 = self.dataBySymbol[Symbol].rsi2.Current.Value
        
            
            
            
            # Setup Open and Close Prices and Bars
            if self.Time >= self.expiry:
                self.previous_day_close = self.Securities[Symbol].Close
                self.expiry = Expiry.EndOfDay(self.Time)
            
            self.previous_bar_close = data[Symbol].Close
            change_from_close = (((self.previous_bar_close - self.previous_day_close) / self.previous_bar_close)*100) 
      
            #Obtain Low of Day and Update 
            bar = data[Symbol]
            
            if not bar.IsFillForward and  self.dataBySymbol[Symbol].lowestPrice  < 0:
                self.dataBySymbol[Symbol].openPrice = bar.Open
                self.dataBySymbol[Symbol].lowestPrice = bar.Low
            
            if self.dataBySymbol[Symbol].lowestPrice < 0:
                return
            
            price = bar.Low
            if price < self.dataBySymbol[Symbol].lowestPrice:  # If we observe a new low
               self.dataBySymbol[Symbol].lowestPrice = price
            
         
            # IMPORTANT!!! Time variables to set open/close times and compare them to current time.
            
            # Convert times to variables (necessary for time comparison)
            currentTime = self.Time
            openTime = time(9,30)
            closeTime = time(12,0)
            
            # Convert string to format that can be compared (comparison does not work if you do not do this)
            # These comparisons are to test it works, before implementing them in the # Buy Conditions function below
            # It is OK to comment them out here, as they are just for testing. Real function below.
            #currentTime.strftime('%H%M') >= openTime.strftime('%H%M')
            #currentTime.strftime('%H%M') <= closeTime.strftime('%H%M')
            
            # Buy Conditions 
            if not self.Portfolio[Symbol].Invested and self.dataBySymbol[Symbol].ticket is None and (currentTime.strftime('%H%M') >= openTime.strftime('%H%M') and currentTime.strftime('%H%M') <= closeTime.strftime('%H%M')):
               # 
                # If buy conditions are satisfied then place MarketOrder
                if  ((RSI1 <=70 and RSI1 >=20) and (RSI2 >0 and RSI2 <=25) and (self.previous_bar_close <= self.dataBySymbol[Symbol].lowestPrice)): 
                    self.dataBySymbol[Symbol].ticket= self.MarketOrder(Symbol, quantity, tag ="Market Buy") 
    
                    # Place Profit take and Stop Loss orders then reset to None
                    self.LimitOrder(Symbol, -quantity, close * 1.03, tag = "Profit Take")
                    self.StopMarketOrder(Symbol, -quantity, close * 0.99, tag = "Stopped Out")
                    self.dataBySymbol[Symbol].ticket = None
            else:
                # Close position if open for more than 15 minutes and set ticket to None
                if  self.dataBySymbol[Symbol].ticket is not None and (self.Time > self.ticket.Time + timedelta(minutes = 15)):
                    self.Liquidate(Symbol)
                    self.dataBySymbol[Symbol].ticket = None
                    
   # Cancel remaining order if limit order or stop loss order is executed 
   def OnOrderEvent(self, orderEvent):
        order = self.Transactions.GetOrderById(orderEvent.OrderId)
        
        if order.Status == OrderStatus.Filled:
            if order.Type == OrderType.Limit or order.Type == OrderType.StopMarket:
                self.Transactions.CancelOpenOrders(order.Symbol)
                
        if order.Status == OrderStatus.Canceled:
            self.Log(str(orderEvent))
            
   #Reset Daily :Pointer
   def OnEndOfDay(self, symbol):
       for Symbol in self.Equities:
         self.dataBySymbol[Symbol].lowestPrice = -1