Preprint Communication Version 1 Preserved in Portico This version is not peer-reviewed

Building Local Correlation Models for Analytical Pricing

Version 1 : Received: 26 April 2023 / Approved: 27 April 2023 / Online: 27 April 2023 (03:22:51 CEST)

How to cite: Escobar-Anel, M. Building Local Correlation Models for Analytical Pricing. Preprints 2023, 2023041011. https://doi.org/10.20944/preprints202304.1011.v1 Escobar-Anel, M. Building Local Correlation Models for Analytical Pricing. Preprints 2023, 2023041011. https://doi.org/10.20944/preprints202304.1011.v1

Abstract

This short paper reveals a simple methodology to create local-correlation models suitable for the closed-form pricing of multi-asset financial derivatives. The multivariate models are built to ensure two conditions, first, marginals follow desirable processes, e.g. we choose the Geometric Brownian Motion (GBM), popular for stock prices. Second, the payoff of the derivative should follow a desired one dimensional process. These conditions lead to a specific choice of the dependence structure, in the form of a local-correlation model. Two popular multi-asset options are entertained, a spread option and a basket option.

Keywords

local correlation; closed-form prices; spread option; basket option

Subject

Business, Economics and Management, Finance

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