52 weeks high/low stock filtering problem by Vidal boreal

Vidal boreal INVESTOR

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class TrialHighalgorithm(QCAlgorithm):



    def Initialize(self):

        self.SetStartDate(2020, 11, 1)

        #self.SetEndDate(2020, 11, 11)

        self.SetCash(10000) 

        self.numberOfSymbols = 200

        self.numberOfSymbolsFine = 10

        self.res = Resolution.Minute

        self.averages = {}

        self.symbols = []

        self.sma = {}

        self.selectedSymbols = []

        self.SPY = self.AddEquity('SPY', self.res).Symbol

        self.Securities["SPY"].SetDataNormalizationMode(DataNormalizationMode.Raw)

        self.SetTimeZone(TimeZones.HongKong)

        self.SetBrokerageModel(BrokerageName.InteractiveBrokersBrokerage, AccountType.Margin)

        

        self.AddUniverse(self.CoarseSelectionFunction, self.FineSelectionFunction)



    def CoarseSelectionFunction(self, coarse):



        filtered = [ x for x in coarse if (x.HasFundamentalData) & (x.Price > 1) & ( x.Volume > 500000) ]

        filtered.sort(key=lambda x: x.DollarVolume, reverse=True)

        self.symbols = [ x.Symbol for x in filtered[:self.numberOfSymbols] ]



        return self.symbols

        

    def FineSelectionFunction(self, fine):

        symbols = [x.Symbol for x in fine]

        history = self.History(symbols, 252, Resolution.Daily)

        

        for symbol in symbols:

            if str(symbol) in history.index.get_level_values(0):

                symbolHistory = history.loc[str(symbol)]

                if not symbolHistory.empty:

                    symbolSMA = SimpleMovingAverage(200)



                for tuple in symbolHistory.itertuples():

                    bar = TradeBar(tuple.Index, symbol, tuple.open, tuple.high, tuple.low, tuple.close, tuple.volume)

                    symbolSMA.Update(tuple.Index, tuple.close)

             

                self.sma[symbol] = symbolSMA

            else:

                symbols.pop(symbols.index(symbol))



        self.selectedSymbols = [ x for x in symbols if (max(history.loc[str(x)]['high'][:-1]) < history.loc[str(x)]['high'][-1]) & (history.loc[str(x)]['close'][-1] > history.loc[str(x)]['open'][-1])]

        return self.selectedSymbols

    

    def OnData(self, data):

        if self.selectedSymbols is None: return

        for x in self.selectedSymbols:

            self.SetHoldings(x, 0.01)

I want to filter 52 weeks high stocks and make sure they close above open yesterday. I know my coding is bad. Is there any easy way to do it in the same way? It is a bit slow.

sometimes it got : max() arg is an empty sequence

Could someone help me, please? Thanks

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Vidal boreal

Accepted Answer

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AK M

75.1k Pro ,

Hey Vidal,

There are a couple issues with your algorithm. The algorithm is slow for several reasons. First, the algorithm resolution is set to Minute, however it does not seem that anything significant is being done minutely that cannot be done at a coarser resolution. When the resolution is minutely, your OnData() function is called every minute. Changing to Resolution.Daily may better suite your needs.

Second, it seems like you are calling the FineSelection function unnecessarily. Fine universe selection is used when you want to want to use fundamental data to filter your universe, data such as EPS, Revenue Growth, EBIDTA, Debt, etc. It seems what you require does not require fundamental data at the moment, so moving the logic to the CoarseSelection function is better.

However, the biggest bottleneck is the history call. History calls are slow and in your code, the calls are being made every day (as CoarseSelection is called daily at midnight). A better way to manage historical data would be to cache old values for symbols and update as necessary.

There are some minor things too, like using ‘and’ instead of ‘&’ to short-circuit conditions.

It may be difficult to make all these changes, so I have rewritten your algorithm with them in mind. It may not be perfectly what you want, but hopefully it is a good starting point for you. I've attached it below.

Vidal boreal INVESTOR

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