CODEWITHSUNDEEP
python
roby
roby

Reputation: 123

Invalid value encountered in true_divide

I am trying to compute implied volatility of black scholes formula using python. however, I have problem with my code. I keep getting this error message when I running the code:

RuntimeWarning: divide by zero encountered in true_divide
v = sigmaOld - bs_option_call(v, s, k, r, t, call_price1)/fprime(sigmaOld, s, k, r, t)e here

and here is my code:

while True:
for (v, k, s, t, call_price1) in zip(sigma, K, S, Ta, call_price_list):
    sigmaOld = v
    v = sigmaOld - bs_option_call(v, s, k, r, t, call_price1) / fprime(sigmaOld, s, k, r, t)
    if scipy.absolute( v - sigmaOld ) < epsilon:
        break
print(sigma)

where fprime is 

def fprime(sigma, S, K, r, T):
    logSoverK = log(S / K)
    numerd1 = logSoverK + (r + sigma**2 / 2) * T
    d1 = numerd1 / (sigma*sqrt(T))
    return S * sqrt(T) * norm.pdf(d1) * exp(-r * T)

and K, Ta, S, sigma, call_price_list are lists and r is just a number.

I tried to use 

import numpy as np
np.seterr(divide='ignore', invalid='ignore')

but it was not useful for me for some reason!

can anyone please have a look at my code and tell me what is my mistake! Many thanks in advance

Upvotes: 4

Views: 11302

Answers (1)

Nabeel Ahmed
Nabeel Ahmed

Reputation: 19252

Printing errors and warnings to stderr is default Python functionality.

You're getting this warning because you're dividing by zero i.e. the fprime is returning zero.

If you want to suppress the warning using warning filters:

np.seterr(divide='ignore')

It'll tell Numpy to ignore the divide by zero warning - all the allowed parameters for seterr.

Upvotes: 2

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