Let's set the spot price as 1 (spot price of underlying security) and express each option contract as a point in 3D space $$ \{ x, y, z \} = \{ tenor, moneyness, premium \} $$ where the premium is also relative, like moneyness.
Past volatility, interest rates and in-the-money options are ignored, we are interested only in out-of-the money options.
Additionally we can add imaginary asymptotical points, contracts with $moneyness = 0$ and $moneyness = 10$ (10x spot price) and set its premium as zero. Just to introduce asymptotical constraints for our 3D surface.
All this would give us a set of points in 3D space. What would be the simple approach to interpolate it? Find points in-between? Find premium for arbitrary values of moneyness and tenor?
The simplest approach would be the Inverse distance weighting, find N nearest contracts to the given point $ \{ x, y \} = \{ tenor, moneyness \} $ and then compute the weighted average of its premiums.
I wonder if there are better simple options? I don't want to use BlackSholes model, because I don't intuitively understand how it works and I don't care about the past volatility and don't want to make too much assumptions about the surface. I want to stay close to the surface defined by the real prices, whatever shape it has and just interpolate it to fill the gaps. Just any universal and relatively simple method with the single assumption that surface is more or less smooth.
P.S.
Just to be sure we are talking about the same things.
tenor - how much days remained till the expiration date, moneyness - how far strike price is from the spot price (relative, to spot price), premium - how much money you get if you sell option (relative, to spot price).