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The volatility layer is the first stage in OIPD. It takes market option prices and attempts to fit an arbitrage-free implied-volatility model.

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Implied volatility

An option price can be translated into the volatility assumption that would make a pricing model produce that price. That translated number is implied volatility. It is not a forecast from OIPD. It is the volatility embedded in market prices.

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Curves and surfaces

VolCurve fits one expiry. VolSurface fits several expiries and lets you query between them. 
from oipd import VolCurve

vol = VolCurve().fit(chain, market)
ivs = vol.implied_vol([95, 100, 105])
The result is a fitted object. You can ask it for implied vols, option prices, Greeks, plots, or a probability distribution.

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Smile

Options with different strikes usually imply different volatilities. The shape across strikes is called the volatility smile. OIPD fits that smile with SVI, the public method exposed by VolCurve and VolSurface.

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Surface

A volatility surface adds the time dimension. Instead of one smile, VolSurface fits smiles across expiries. It then supports queries such as: 
from oipd import VolSurface

surface = VolSurface().fit(chain, market)
iv = surface.implied_vol(100, t=45 / 365)
Here t is time to expiry in years. OIPD also accepts date-like maturity inputs where the public API supports them.

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Use cases

Use it when you care about:
  • The fitted implied-volatility smile or surface.
  • Model option prices from the fitted volatility.
  • Greeks such as delta, gamma, vega, theta, and rho.
  • Converting fitted volatility into a probability object with .implied_distribution().
For detailed parameters and return types, use the API Reference pages for VolCurve and VolSurface.