The SINC way: A fast and accurate approach to Fourier pricing

TL;DR

The paper introduces the SINC method, a Fourier-based approach for option pricing that offers improved accuracy and speed over existing techniques, with rigorous convergence proofs and broad applicability to various option types and models.

Contribution

It provides a rigorous convergence proof for the SINC approach, ready-to-implement formulas for multiple options, and extensive comparisons demonstrating its advantages over other Fourier methods.

Findings

SINC achieves higher accuracy and speed in option pricing.

The method efficiently prices multiple options simultaneously.

SINC outperforms alternative Fourier-based pricing methods.

Abstract

The goal of this paper is to investigate the method outlined by one of us (PR) in Cherubini et al. (2009) to compute option prices. We name it the SINC approach. While the COS method by Fang and Osterlee (2009) leverages the Fourier-cosine expansion of truncated densities, the SINC approach builds on the Shannon Sampling Theorem revisited for functions with bounded support. We provide several results which were missing in the early derivation: i) a rigorous proof of the convergence of the SINC formula to the correct option price when the support grows and the number of Fourier frequencies increases; ii) ready to implement formulas for put, Cash-or-Nothing, and Asset-or-Nothing options; iii) a systematic comparison with the COS formula for several log-price models; iv) a numerical challenge against alternative Fast Fourier specifications, such as Carr and Madan (1999) and Lewis (2000); v) an extensive pricing exercise under the rough Heston model of Jaisson and Rosenbaum (2015); vi) formulas to evaluate numerically the moments of a truncated density. The advantages of the SINC approach are numerous. When compared to benchmark methodologies, SINC provides the most accurate and fast pricing computation. The method naturally lends itself to price all options in a smile concurrently by means of Fast Fourier techniques, boosting fast calibration. Pricing requires to resort only to odd moments in the Fourier space. A previous version of this manuscript circulated with the title `Rough Heston: The SINC way'.