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Lemuel Mwangi INVESTOR

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Any takers on this, I can use some help. I am trying to improve this algorithm to NOT buy a stock if the same stock has been sold on that same day (Technically trying to prevent day trading - am too broke to afford 25k minimum). I tried navigating my code by attempting to debug the date a symbol is sold then looping around telling the buy function not to buy any symbol that the algo had/has sold within that same market day. The ago I have so far gives an error when I attempt backtest (see attached algo). Will really appreciate any help I can get on this

from datetime import datetime

from datetime import timedelta



class BasicTemplateAlgorithm(QCAlgorithm):



    def Initialize(self):

     

        self.SetStartDate(2022,2,20)

        self.SetCash(50000000)

        self.Data_Symbol = {}

        tickers = ["SPY", #10 stocks per row

                    #Longs

                    "AAPL", "MSFT", "AMZN", 

                   

                    

                    ]

        

        

        self.SetWarmUp(30, Resolution.Daily)                

                        

        for stock in tickers:

            symbol = self.AddEquity(stock, Resolution.Minute).Symbol

            self.Data_Symbol[symbol] = SymbolData(self, symbol)

            

       

        self.Schedule.On(self.DateRules.EveryDay("SPY"), self.TimeRules.Every(timedelta(minutes=1)), self.EveryDayAfterMarketOpen)

            

    

            

    def EveryDayAfterMarketOpen(self):

        

        

        if self.IsWarmingUp: return

        

        for symbol, symbol_data in self.Data_Symbol.items():

            if not symbol_data.cci.IsReady: continue

          

        

            holdings = self.Portfolio[symbol]

            invested = holdings.Invested

            nowprice = holdings.Price

            aveprice = holdings.AveragePrice

            quantity = holdings.Quantity

            

            

            cci = symbol_data.cci.Current.Value

          

            

            

            #Buy symbol only if if CCI < 100 and that symbol was not sold today

            if not invested and not sold_today and cci < -100:

                self.MarketOrder(symbol, + mofactor)

                self.Debug (symbol)

                self.Debug (self.Time.date)

                

                what_to_buy = (symbol)

                when_to_buy = (self.Time.date)

                tobuy = what_to_buy and when_to_buy

                    

            if invested and nowprice > aveprice * 1.01:

                self.MarketOrder (symbol, (-1 * quantity))

                self.Debug (symbol)

                self.Debug (self.Time.date)

                sold_symbol = (symbol)

                when_sold = (self.Time.date)

                sold_today = sold_symbol and when_sold

                

         

class SymbolData:

    def __init__ (self,algo,symbol):

        self.algorithm = algo

        self.symbol = symbol

       

        #CCI Functions

        self.cci = algo.CCI(symbol, 14, MovingAverageType.Simple, Resolution.Daily)

Update Backtest

Lemuel Mwangi

Accepted Answer

Update Backtest

Notebook

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Adam W

3.8k Pro ,

You can just create some dictionary that indicates whether you sold the stock, then use a Scheduled Function at end of each day to reset it to False.

from datetime import datetime

from datetime import timedelta



class BasicTemplateAlgorithm(QCAlgorithm):



    def Initialize(self):

     

        self.SetStartDate(2022,2,20)

        self.SetCash(50000000)

        self.Data_Symbol = {}

        tickers = ["SPY", "AAPL", "MSFT", "AMZN", ]



        self.SetWarmUp(30, Resolution.Daily)                

                        

        for stock in tickers:

            symbol = self.AddEquity(stock, Resolution.Minute).Symbol

            self.Data_Symbol[symbol] = SymbolData(self, symbol)

            

        ## Dictionary for whether symbol was traded; we will reset this every day

        self.symbolTraded = { symbol: False for symbol in self.Data_Symbol.keys() }    

        

self.Schedule.On(self.DateRules.EveryDay("SPY"), self.TimeRules.BeforeMarketClose('SPY', 0), self.ResetSymbolTraded)

        





        self.Schedule.On(self.DateRules.EveryDay("SPY"), self.TimeRules.Every(timedelta(minutes=1)), self.EveryDayAfterMarketOpen)





        

    def EveryDayAfterMarketOpen(self):

        if self.IsWarmingUp: return

        

        for symbol, symbol_data in self.Data_Symbol.items():

            if not symbol_data.cci.IsReady: continue



            holdings = self.Portfolio[symbol]

            invested = holdings.Invested

            nowprice = holdings.Price

            aveprice = holdings.AveragePrice

            quantity = holdings.Quantity

            

            cci = symbol_data.cci.Current.Value

            

            ## Check whether the symbol was traded

            sold_today = self.symbolTraded[symbol]

            







            #Buy symbol only if if CCI < 100 and that symbol was not sold today

            if (not invested) and (not sold_today) and (cci < -100):

                self.MarketOrder(symbol, + mofactor)

                self.Debug (symbol)

                self.Debug (self.Time.date)

                

                what_to_buy = (symbol)

                when_to_buy = (self.Time.date)

                tobuy = what_to_buy and when_to_buy

                    

            if invested and (nowprice > aveprice * 1.01):

                self.MarketOrder (symbol, (-1 * quantity))

                self.Debug (symbol)

                self.Debug (self.Time.date)

                #sold_symbol = (symbol)

                when_sold = (self.Time.date)

                #sold_today = sold_symbol and when_sold

                

                ## Note: Assuming if this triggers you want to stop the buy signal?

                ## Then add a `self.symbolTraded[symbol] = True` here

        



    

    def ResetSymbolTraded(self):

        ## We reset this to False at end of each day

        self.symbolTraded = { symbol: False for symbol in self.Data_Symbol.keys() }    

         

class SymbolData:

    def __init__ (self,algo,symbol):

        self.algorithm = algo

        self.symbol = symbol

       

        #CCI Functions

        self.cci = algo.CCI(symbol, 14, MovingAverageType.Simple, Resolution.Daily)

Lemuel Mwangi

2.3k Pro ,

@Adam, when I run the back test on your edit, the algo is re-buying the symbols 1-2 minutes after selling them. I tried playing around the False/True flag, but doesn't see to figure how to prevent the someday rebuying after selling

Lemuel Mwangi

2.3k Pro ,

See backtest below

Newoptionz

2.2k Pro ,

Lemuel Mwangi this code solves the ‘don’t buy the same day if you have sold that day' problem. It does though still initiate a buy-on open for the next day. Quite impressive 100% win rate, but this is negated by the fact that there is no stop-loss.

Thanks

Vladimir

94.7k Pro ,

Lemuel Mwangi

→ I am trying to improve this algorithm to NOT buy a stock if the same stock has been sold on that same day.

You can use self.Schedule.On() to trade once a day like in “Oversold CCI portfolio with Take Profit and Stop Loss”.

If you are satisfied with my answer, please accept it and don't forget to like it

Adam W

3.8k Pro ,

Lemuel Mwangi

Try this instead. I'm running a backtest so can't check if this works, but it should.

from datetime import datetime

from datetime import timedelta



class BasicTemplateAlgorithm(QCAlgorithm):



    def Initialize(self):

     

        self.SetStartDate(2022,2,20)

        self.SetCash(50000000)

        self.Data_Symbol = {}

        tickers = ["SPY", "AAPL", "MSFT", "AMZN", ]



        self.SetWarmUp(30, Resolution.Daily)                

                        

        for stock in tickers:

            symbol = self.AddEquity(stock, Resolution.Minute).Symbol

            self.Data_Symbol[symbol] = SymbolData(self, symbol)

            

        ## Dictionary for whether we can trade this symbol; we will reset this at end of each day

        self.canTradeSymbol = { symbol: True for symbol in self.Data_Symbol.keys() }    

        

        self.Schedule.On(self.DateRules.EveryDay("SPY"), 

                         self.TimeRules.BeforeMarketClose('SPY', 0), 

                         self.canTradeSymbols)

 

        self.Schedule.On(self.DateRules.EveryDay("SPY"), 

                         self.TimeRules.Every(timedelta(minutes=1)), 

                         self.EveryDayAfterMarketOpen)





        

    def EveryDayAfterMarketOpen(self):

        if self.IsWarmingUp: return

        

        for symbol, symbol_data in self.Data_Symbol.items():

            if not symbol_data.cci.IsReady: continue



            holdings = self.Portfolio[symbol]

            invested = holdings.Invested

            nowprice = holdings.Price

            aveprice = holdings.AveragePrice

            quantity = holdings.Quantity

            

            cci = symbol_data.cci.Current.Value

            

            # Check whether we can trade this symbol

            can_trade = self.canTradeSymbol[symbol]

            if not can_trade:

                continue

                

            #Buy symbol if CCI < 100

            if (not invested) and (cci < -100):

                self.MarketOrder(symbol, 1)

                self.Debug(f'Bought {symbol} at {self.Time}')

                

            # Sell symbol        

            if invested and (nowprice > aveprice * 1.01):

                self.MarketOrder (symbol, (-1 * quantity))

                self.Debug(f'Liquidated {symbol} at {self.Time}.')

                

                # Now after a buy/sell, we prevent future buys for the rest of the day

                self.canTradeSymbol[symbol] = False



    def ResetSymbolTraded(self):

        ## We reset this to Trade at end of each day

        self.canTradeSymbol = { symbol: True for symbol in self.Data_Symbol.keys() }    

         

class SymbolData:

    def __init__ (self,algo,symbol):

        self.algorithm = algo

        self.symbol = symbol

       

        #CCI Functions

        self.cci = algo.CCI(symbol, 14, MovingAverageType.Simple, Resolution.Daily)

Lemuel Mwangi INVESTOR

Update Backtest

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