runtimewarning: invalid value encountered in true_divide

It'll tell Numpy to ignore the divide by zero warning - all the allowed parameters for seterr. RuntimeWarning: invalid value encountered in truedivide x np.divide(x1, x2, out).

If you want to suppress the warning using warning filters: np.seterr(divide='ignore') You're getting this warning because you're dividing by zero i.e. Printing errors and warnings to stderr is default Python functionality. Np.seterr(divide='ignore', invalid='ignore')īut it was not useful for me for some reason!Ĭan anyone please have a look at my code and tell me what is my mistake! Return S * sqrt(T) * norm.pdf(d1) * exp(-r * T)Īnd K, Ta, S, sigma, call_price_list are lists and r is just a number. Numerd1 = logSoverK + (r + sigma**2 / 2) * T Where fprime is def fprime(sigma, S, K, r, T): If scipy.absolute( v - sigmaOld ) < epsilon: V = sigmaOld - bs_option_call(v, s, k, r, t, call_price1) / fprime(sigmaOld, s, k, r, t) V = sigmaOld - bs_option_call(v, s, k, r, t, call_price1)/fprime(sigmaOld, s, k, r, t)e hereįor (v, k, s, t, call_price1) in zip(sigma, K, S, Ta, call_price_list): I keep getting this error message when I running the code: RuntimeWarning: divide by zero encountered in true_divide I am trying to compute implied volatility of black scholes formula using python.

Runtimewarning: invalid value encountered in true_divide