Non Parametric Estimates of Option Prices Using Superhedging

TL;DR

This paper introduces a non-parametric superhedging method for estimating option prices that handles market imperfections and is backed by strong statistical properties, demonstrated through simulations and real market data.

Contribution

It presents a novel superhedging-based non-parametric approach for option price estimation that relaxes arbitrage constraints and accounts for market frictions.

Findings

Effective on simulated data

Successful application to S&P 500 options

Estimates exhibit optimal statistical properties

Abstract

We propose a new non parametric technique to estimate the CALL function based on the superhedging principle. Our approach does not require absence of arbitrage and easily accommodates bid/ask spreads and other market imperfections. We prove some optimal statistical properties of our estimates. As an application we first test the methodology on a simulated sample of option prices and then on the S\&P 500 index options.