equity vol curve

financepy.market.volatility.equity_vol_curve

Types

EquityVolCurveDeltaTypes

Smile dynamics used when calculating option delta.

Members

STICKY_STRIKE = 0

STICKY_MONEYNESS = 1

EquityVolCurveExtrapTypes

Volatility extrapolation scheme.

Members

INTERPOLATOR = 0

TANGENT = 1

EquityVolCurveInterpTypes

Volatility interp scheme.

Members

CUBIC_SPLINE = 0

PCHIP = 1

SMOOTHING_SPLINE = 2

LOG_STRIKE_SMOOTHING_SPLINE = 3

Class

EquityVolCurve

EquityVolCurve(
    strikes: numpy.ndarray,
    volatilities: numpy.ndarray,
    s: float,
    t_exp: float,
    r: float,
    q: float,
    interp: EquityVolCurveInterpTypes = <EquityVolCurveInterpTypes.CUBIC_SPLINE: 0>,
    extrap: EquityVolCurveExtrapTypes = <EquityVolCurveExtrapTypes.TANGENT: 1>,
    smoothing: float = 0.0001,
    derivative_bump: float = 0.0001,
) -> None

No description available.

Methods

volatility


volatility(
    self,
    strike: float | numpy.ndarray,
) -> float | numpy.ndarray

Return interpolated volatility for the supplied strike.

delta_sticky_strike


delta_sticky_strike(
    self,
    strike: float | numpy.ndarray,
    option_type,
) -> float | numpy.ndarray

Return delta assuming sticky-strike volatility. The result is the standard Black-Scholes delta evaluated using the volatility from this curve.

delta_sticky_moneyness


delta_sticky_moneyness(
    self,
    strike: float | numpy.ndarray,
    option_type,
) -> float | numpy.ndarray

Return delta assuming sticky-moneyness volatility. The smile is held fixed as a function of K/S. So if sigma(K/S) then d sigma / dS = -(K/S) d sigma/dK and Delta = Delta_BS + Vega * d sigma/dS.

delta


delta(
    self,
    strike: float | numpy.ndarray,
    option_type,
    convention: EquityVolCurveDeltaTypes = <EquityVolCurveDeltaTypes.STICKY_STRIKE: 0>,
) -> float | numpy.ndarray

Return delta using the selected smile-dynamics convention.

pdf


pdf(
    self,
    smin: float,
    smax: float,
    n_intervals: int,
) -> tuple[numpy.ndarray, numpy.ndarray]

Calculate the smile/skew-implied probability distribution. Uses the market state stored in this volatility curve. Returns ------- tuple[np.ndarray, np.ndarray] Strike grid and probability masses f(K) * dK.

Generated automatically from the FinancePy source code. Do not edit this file manually.