I'm trying to make a portfolio construction model that only allows a set amount of equal weighted positions based on the total value of the portfolio. However, when a stock is shorted it adds money to the portfolio that then is included in the calculation for how many positions it can open that day, resulting in it trying to open more positions than it can. The code works great for only long positions, but I want to be able to open both short and long positions at the same time. Does anyone know of any way to solve this?

Here is my code:

import numpy as np

class MaximumPositionPortfolio(PortfolioConstructionModel):
   def __init__(self, algorithm, positionLimit):
       self.positionLimit = positionLimit
       self.percent = 1/self.positionLimit
       
   def CreateTargets(self, algorithm, insights):
       
       targets = []
       
       #calculates how big the position should be
       positionSize = algorithm.Portfolio.TotalPortfolioValue*self.percent
       #calculates how many positions to let through
       openPositions = np.floor(algorithm.Portfolio.Cash/positionSize)
       
       #counts how many positions have been opened
       count = 0
       for i in insights:
       
       		#closes positions with a flat insight
           if i.Direction == InsightDirection.Flat:
               targets.append(PortfolioTarget(i.Symbol, 0))
               
           #opens long positions
           elif i.Direction == InsightDirection.Up:
               if count < openPositions:
                   count += 1
                   targets.append(PortfolioTarget.Percent(algorithm, i.Symbol, self.percent))
           
           #opens short positions
           elif i.Direction == InsightDirection.Down:
               if count < openPositions:
                   count += 1
                   targets.append(PortfolioTarget.Percent(algorithm, i.Symbol, -self.percent))
                   
       return targets
   
   def OnSecuritiesChanged(self, algorithm, changes):
       pass