Coding For Combining Multiple Algorithms Into One

Hi KY Hung,
To combine multiple algorithms as a single algorithm, we recommend using multiple alpha models and adding them using AddAlpha() method in the Algorithm Framework. Note that here each alpha model works independently in generating its insights, and the Portfolio Construction Model model decides how to consume these insights. Refer to the following code snippet. Alternatively, we can deploy multiple live algorithms to different broker's account or a subaccount.
 

class DynamicVerticalGearbox(QCAlgorithm):def Initialize(self):
   self.SetStartDate(2019, 12, 14)
   self.SetCash(100000)
   self.AddAlpha(CustomAlphaOne())
   self.AddAlpha(CustomAlphaTwo())
  def OnData(self, data):
    pass
  def OnSecuritiesChanged(self, changed):
    # do rebalancing here:
    pass
class CustomAlphaOne:
    def Update(self, algorithm, slice):
      return []
    def OnSecuritiesChanged(self, algorithm, changes):
       # set up indicators for new securities (e.g. SMA)
       pass
 class CustomAlphaTwo:
       def Update(self, algorithm, slice):
          return []
       def OnSecuritiesChanged(self, algorithm, changes):
           pass

Best,

Varad Kabade

Hi Varad Kabade is there an example algorithm as you've described above? Also what about one that emits insights for the same asset which then have to be averaged somehow?

Hi Richard, 

maybe this post could be helpful to you ;

https://www.quantconnect.com/forum/discussion/4530/framework-algorithm-with-two-or-more-alphas/p1

Thanks!