I'm currently looking to convert my existing multipart algorithm into a QC framework algorithm. I had already built my own framework similar to QC's. In my existing framework each alpha class sets a desired allocation of securities and then the framework combines the allocations and executes them all to minimize transaction fees. My algorithm is designed to be used in an long-only retirement portfolio where my goal is to use smart rebalancing to beat a simple buy and hold portfolio on a risk adjusted basis rather than focus on making individual profitable trades.

Similar to this:

  • Algo 1:
    • Spy = 0.4 
    • TLT = 0.6
  • Algo 2:
    • Spy = 0.6
    • TLT = 0.2
    • XIV = 0.2
  • Combined allocations (equiweight) that get executed:
    • Spy = (0.4+0.6)/2 = 0.5
    • TLT = (0.6+0.2)/2 = 0.4
    • XIV = (0+0.2)/2 = 0.1
 Is  there any way to convert these to insight objects that would set the desired allocation? From everything I have read it seems the insights are designed to be more of a short term 100% long or 100% short signal rather than designed to be a long-term portfolio rebalance tool. My algo updates it's desired allocations every day but the allocations don't always change. Would they be considered confidence values? or perhaps make a custom Portfolio Construction Model?