Why can't the curve find the least squares parameters when I used it in SABR model? (SABR Calibration)

Question

Follow is the SABR function part of my code in python：

def SABR_func( K, alp, bet, rho, nu ):
    "SABR"
    f = mV0*np.exp((0.02 - q)*tau)
    z = nu/alp*(f * K)**(0.5*(1 - bet)) * np.log(f / K)
    xz = np.log((np.sqrt(1 - 2*rho*z + z*z) + z - rho) / (1 - rho))
    zdivxz = z / xz
    zdivxz[np.isnan(zdivxz)] = 1.0
    result = ( alp*(f*K)**(0.5* (bet-1) )*
            (1 + ( ((1 - bet)*np.log(f/K))**2/24 + ((1 - bet)*np.log(f/K))**4/1920 ))**(-1.0)
            * zdivxz
            * ( 1 + ( ((1 - bet)*alp )**2 / (24*(f*K)**(1 - bet))
            + 0.25*alp*bet*rho*nu / ((f*K)**(0.5*(1-bet)))
            + ((2-3*rho**2)*nu**2)/24)*tau )
            )
    return result

And I use the function to fit the data in every time slice:

popt, pcov = curve_fit(SABR_func, cp[0, :], cp[1, :], p0 = init_guess,maxfev=10000)
#init_guess = [alp,bet,rho, nu] I have write before this
print(popt)
y1[it, :] = SABR_func(stkSet, *popt)

where:

mV0 is the Synthetic futures prices for atm options

cp[0,:] is the strike of option

cp[1,:] is the price of option

But I found that the model fitting is very poor,and be like this gif(pink points are true data)

Thanks for jChoi's help, I find I have some wrong with the f's formula,but when I using the right foluma, the result is same. Is there any other wrong I don't find ?

Answer 1

f should be the forward rate. I have no idea where this line comes from?

f = alp*np.exp((0.02 - q)*tau)

It seems like that alp is playing the role of the spot price. You should take spot as an input and define

f = spot*np.exp((0.02 - q)*tau)