FinancePy

FinancePy API Reference

Ssvi Surface

financepy.models.ssvi_surface

Classes

SSVIPowerLawPhi

SSVIPowerLawPhi(eta, gamma) -> None
Power-law SSVI phi function phi(theta) = eta * theta^(-gamma)

Methods

value

value(self, theta)

No description available.

parameters

parameters(self)

No description available.

SSVISurface

SSVISurface(expiries=None, atm_total_variances=None, rho=None, phi_function=None) -> None
Inherits from: ImpliedVolatilitySurface
SSVI implied-volatility surface w(k, theta) = theta / 2 [ 1 + rho phi(theta) k + sqrt( (phi(theta) k + rho)^2 + 1 - rho^2 ) ] using the power-law specification phi(theta) = eta theta^(-gamma). The surface can either be constructed from known parameters or calibrated directly to a market implied-volatility grid.

Methods

calibrate

calibrate(self, forwards, strikes, expiries, implied_volatilities)
Jointly calibrate theta(T_1), ..., theta(T_N), rho, eta, gamma to the complete implied-volatility grid. The theta term structure is parameterized so that 0 < theta_1 < theta_2 < ... < theta_N. This guarantees monotonic ATM total variance.

theta

theta(self, t_exp)
Return ATM total variance theta(T). Linear interpolation is performed in total variance.

total_variance_from_log_moneyness

total_variance_from_log_moneyness(self, k, t_exp)
Return SSVI total implied variance.

total_variance

total_variance(self, forward, strike, t_exp)

No description available.

implied_volatility

implied_volatility(self, forward, strike, t_exp)

No description available.

implied_volatility_curve

implied_volatility_curve(self, forward, strikes, t_exp)

No description available.

implied_volatility_surface

implied_volatility_surface(self, forwards, strikes, expiries)

No description available.

parameters

parameters(self)
Return global SSVI parameters rho, eta, gamma.

atm_total_variances

atm_total_variances(self)

No description available.

expiries

expiries(self)

No description available.

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