Natural SVI¶
Overview¶
The natural SVI parametrization (Gatheral & Jacquier 2014). Same 5 degrees of freedom as raw SVI, connected by an explicit bijection, but the parameters map more directly to ATM level, skew, and curvature — often better behaved in calibration, and useful as an initialisation coordinate system for raw SVI.
Model¶
The bijection to raw SVI \((a, b, \rho, m, \sigma)\):
and its inverse:
Both directions are exposed as natural_to_raw and raw_to_natural.
Parameters¶
Parameter |
Meaning |
Constraint |
|---|---|---|
\(\Delta\) |
vertical variance shift |
unconstrained |
\(\mu\) |
log-moneyness translation |
unconstrained |
\(\rho\) |
skew (correlation) |
\(|\rho| < 1\) |
\(\omega\) |
overall variance scale |
\(\omega > 0\) |
\(\zeta\) |
curvature / smile-width scale |
\(\zeta > 0\) |
Usage¶
from pysvi import get_model, calibrate_slice
model = get_model("natural") # or "nsvi"
params = calibrate_slice(df_slice, model)
# params: {'delta', 'mu', 'rho', 'omega', 'zeta', 'forward'}
No extra keyword arguments are required. Converting a fit between conventions:
from pysvi import natural_to_raw, raw_to_natural
raw = natural_to_raw(params["delta"], params["mu"], params["rho"],
params["omega"], params["zeta"])
Arbitrage behaviour¶
Identical to raw SVI (the curves are the same family): soft parameter bounds by default (QUASI); NO_BUTTERFLY and NO_CALENDAR penalties supported via the raw-SVI conversion — see Arbitrage freeness. Wing slopes for the Lee-bound diagnostics are the raw-SVI asymptotes \(b(1 \mp \rho)\).
References¶
Gatheral, J., Jacquier, A. (2014). “Arbitrage-free SVI volatility surfaces.” Quantitative Finance 14(1), section 3.