Hello my beloved community, 

I need serious help that may be easy for someone moderately well endowed in Python to help me out with. I am a beginner who is new to universe selection and doesn't understand classes very well. 

Questions - I have no idea to how to make OnData, Consolidated functions, Scheduled events, inclusive to my universe that is changing every day with a different amount of symbols potentially each day. I am very new 

Strategy - I want this algorithm to filter by volume, and then by which of those stocks have had earnings report recently, then some sort of buy logic. 

Buy Logic - The buy logic contains a consolidated data function where two variables are assigned every day.  The OnData method is going to check price every minute relative to the two variables declared shortly after market open

Here is the code just in case it does not show up without a backtest attached. 

  1. #region imports
  2. from AlgorithmImports import *
  3. #endregion
  4. class EarningsORB(QCAlgorithm):
  6.     def Initialize(self):
  7.         self.SetStartDate(2023, 2, 2)
  8.         self.SetEndDate(2023, 2, 5)
  9.         self.SetCash(100000) 
  11.         # Scheduled events 
  12.         self.Schedule.On(self.DateRules.EveryDay(),self.TimeRules.AfterMarketOpen(60), self.RangeToggle)
  13.         self.Schedule.On(self.DateRules.EveryDay(), self.TimeRules.AfterMarketOpen(), self.UpdateUniverse)
  15.         # Universe Selection
  16.         self.AddUniverse(self.MyCoarseFilterFunction)
  17.         self.volumeBySymbol = {}
  18.         self.symbols = []
  20.         # Toggles 
  21.         self.range_toggle = False
  23.         # Consolidated data  
  24.             # Sixty Min Bars
  25.         sixty_min_consolidator = TradeBarConsolidator(timedelta(minutes=60))
  26.         self.SubscriptionManager.AddConsolidator(self.symbol.Symbol, sixty_min_consolidator)
  27.         sixty_min_consolidator.DataConsolidated += self.OnSixtyMinBar
  28.         self.sixtyMinBarWindow = RollingWindow[TradeBar](1)
  30.     def MyCoarseFilterFunction(self, coarse):
  31.         # Price above 10 and dollar volume above 10mil
  32.         filtered = [ x for x in coarse if x.Price > 10 and x.DollarVolume > 10000000 ]
  34.         # Adds to VolumeBySymbol Dictionary
  35.         for x in filtered:
  36.             if x.Symbol not in self.volumeBySymbol:
  37.                 self.volumeBySymbol[x.Symbol] = SymbolData(x.Symbol, self)
  38.             self.volumeBySymbol[x.Symbol].Update(x.EndTime, x.Volume) 
  40.         # Filter based on recent earnings report - This is where the filter logic would go, this is example code, it is not correct
  41.         # Maybe this is where the 'estimize' code is supposed to go? 
  42.         self.symbols = []
  43.         for symbol in self.volumeBySymbol.keys():
  44.             last_report_date = self.Fundamentals.GetLastReport(symbol).ReportDate
  45.             if (self.Time - last_report_date).days <= 1: # Only include symbols with earnings report in the last day
  46.                 self.symbols.append(symbol)
  48.         # Log
  49.         symbol_strings = [str(symbol.Value) for symbol in self.symbols]
  50.         self.Log(f"Symbols with recent earnings reports: {symbol_strings}")
  52.         return self.symbols
  53.     
  54.     # Scheduled events 
  55.     def UpdateUniverse(self):
  56.         # Refresh universe
  57.         self.RemoveSecurity(self.symbols)
  58.         self.AddUniverse(self.MyCoarseFilterFunction)
  59.     
  60.     def RangeToggle(self):
  61.         self.range_toggle = True
  63.     # Consolidated Data
  64.     def OnSixtyMinBar(self, sender, bar):
  65.         self.sixtyMinBarWindow.Add(bar)
  66.         if not self.sixtyMinBarWindow.IsReady:
  67.             return
  68.         
  69.         # VARIABLES - HIGHS - LOWS
  70.         trigger_bar = self.sixtyMinBarWindow[0]
  72.         if self.range:
  73.             self.trigger_sixty_min_open = trigger_bar.Open
  74.             self.trigger_sixty_min_close = trigger_bar.Close
  76.             self.range = False
  78.     # Buy Logic
  79.     def OnData(self, data):
  80.         # Check buy criteria every minute
  81.         for symbol in self.symbols:
  82.             # Enter long when it crosses sixty min high
  83.             if self.Securities[symbol].Price > self.trigger_sixty_min_close[symbol]: # am i supposed to add [symbol] there? Do i add [symbol] anywhere else? Like in the consolidated data function? 
  84.                 self.SetHoldings(symbol, 1 / len(self.symbols))
  86. # Symbol Data class
  87. class SymbolData:
  88.     def __init__(self, symbol, algo):
  89.         self.algo = algo
  90.         self.symbol = symbol
  91.         self.sma = SimpleMovingAverage(30)
  92.         history = algo.History(symbol, 30, Resolution.Daily)
  93.         if not history.empty:
  94.             for time, row in history.loc[symbol].iterrows():
  95.                 self.sma.Update(time, row['volume'])
  97.     def Update(self, time, vol):
  98.         self.sma.Update(time, vol)
+ Expand

 

Thank you for taking the time to read this and maybe help me out as usual. 

Best, 

Jesse

Author

Jesse Fleming

March 2023