Surface Interpolation

Surface interpolation is a statistical technique used to estimate missing values on a volatility surface. Because options are only traded at specific strike prices and expiration dates, the market does not provide a complete picture of implied volatility for every possible scenario.

Interpolation fills these gaps by using mathematical models to create a smooth, continuous surface from the available data points. This is critical for pricing non-standard options and for accurately calculating the risk metrics of a portfolio.

In the volatile world of cryptocurrency, accurate interpolation is essential to prevent mispricing and to ensure that risk models are robust. Advanced methods, such as cubic splines or neural networks, are often employed to capture the complex shapes of crypto volatility surfaces.