svi surface

financepy.models.svi_surface

Class

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.