Svi Surface
financepy.models.svi_surface
Classes
SVISurface
SVISurface(expiries=None, svi_parameters=None) -> None
Inherits from: ImpliedVolatilitySurface
SVI implied-volatility surface.
The surface consists of one raw-SVI smile for each market expiry.
Each smile is parameterized in forward log-moneyness
k = log(K / F_T)
using total implied variance
w(k,T) = sigma_imp(k,T)^2 T.
Between calibrated expiries, total variance is interpolated linearly
in time.
Methods
calibrate
calibrate(self, forwards, strikes, expiries, implied_volatilities)
Calibrate one raw-SVI smile to each expiry.
Parameters
----------
forwards : array_like
Forward price for each expiry.
strikes : array_like
Strike grid.
expiries : array_like
Expiry times.
implied_volatilities : array_like
Market implied-volatility surface with shape
(num_expiries, num_strikes).
Returns
-------
calibration_errors : ndarray
Calibration cost for each maturity slice.
total_variance
total_variance(self, forward, strike, t_exp)
Return total implied variance
w(K,T) = sigma_imp(K,T)^2 T.
At calibrated expiries the corresponding SVI smile is evaluated
directly. Between expiries, total variance at fixed forward
log-moneyness is interpolated linearly in time.
implied_volatility
implied_volatility(self, forward, strike, t_exp)
Return Black implied volatility.
implied_volatility_curve
implied_volatility_curve(self, forward, strikes, t_exp)
Return an implied-volatility smile for a fixed expiry.
implied_volatility_surface
implied_volatility_surface(self, forwards, strikes, expiries)
Return an implied-volatility surface.
The returned array has shape
(num_expiries, num_strikes).
parameters
parameters(self)
Return calibrated raw-SVI parameters.
Each row contains
(a, b, rho, m, sigma).
Generated automatically from the FinancePy source code.
Do not edit this file manually.