Local Stochastic Correlation Models for Derivative Pricing

This paper reveals a simple methodology to create local-correlation models suitable for the closed-form pricing of two-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.

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Publication Details

Journal
Stats
Published
2025-07-18
DOI
https://doi.org/10.3390/stats8030065
Primary Topic
Stochastic processes and financial applications
Type
article
Field-Weighted Citation Impact
0.00
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article

Local Stochastic Correlation Models for Derivative Pricing

Marcos Escobar‐Anel
Stats
Stochastic processes and financial applications
article

Local Stochastic Correlation Models for Derivative Pricing

Marcos Escobar‐Anel
article en

Abstract

This paper reveals a simple methodology to create local-correlation models suitable for the closed-form pricing of two-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.

StatsVol. 8(3)
Western University (CA)
Openalex Percentile: Top 74%
Stochastic processes and financial applications
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