block3.py

startrev = dcf_proj.loc["revenue",year] #get the starting revenue

allFVs = [] #create a list to store FV values

for p in range(10000): #run the simulation 10000 times
    #creating projections for a 5 year dcf model
    Fiveyrev = []
    Fiveyinc = []
    Fiveyfcf = []
    for i in range(5):
        startrev = startrev*(1+np.random.normal(loc=rev_change_mean, scale=rev_change_stdd))
        neti = startrev*(margin_change/100)
        fcf = neti*(fcf_change/100)
        Fiveyrev.append(startrev)
        Fiveyinc.append(neti)
        Fiveyfcf.append(fcf)