Iteration with constants and other variables with Arrays Numpy Python

Question

I am trying to modify the function below so that it gives the expected output below. For the first calculation it go like 100+ 100*-87/100 = 13 with the equation NonC_Amount + Int_amount * np.cumprod(PnL / 100). Since -87 is the first element in the PnL, for the second calculation it will go as 13 + 100*-4/100 = 9. the NonC_Amounts value is updated.

PnL = np.array([-87., -4., -34.1, 8.5])
Int_amount = 100
NonC_Amount = 100
PnL.prod(initial=Int_amount)
NonCompounding =NonC_Amount  + Int_amount  * np.cumprod(PnL / 100)

Current Output:

[ 13, 103.48 , 98.81332,  99.8991322]

Expected Output:

[ 13,  9,  -25.1,  -16.6]

Reti43 · Accepted Answer · 2021-02-08 01:51:28Z

3

You do the wrong calculations. From your description it seems you want to do

NonC_Amount = 100
NonCompounding = np.zeros_like(PnL)
for i in range(PnL.shape[0]):
    NonCompounding[i] = NonC_Amount + Int_amount * PnL[i] / 100
    NonC_Amount = NonCompounding[i]

Edit: If you want this operation vectorised, you can do

NonCompounding = NonC_Amount + np.cumsum(Int_amount * PnL / 100)

np.cumprod() gives you the cumulative product up to the ith element. For np.cumprod(PnL) that'd be

[-87, -87*(-4), -87*(-4)*(-34.1), etc...]

and it's only by pure chance it gives you the correct result for the first element.

edited Feb 8, 2021 at 1:51

answered Feb 8, 2021 at 0:13

Reti43

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1 Comment

tony selcuk Over a year ago

I have updated the issue sorry about the mistake it was supposed to be -16. instead of 16. if possible I am trying to avoid for loops as they are slow and inefficient.

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