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Bibliographic Details
Main Authors: Qiu, Jinniao, Ware, Antony, Yang, Yang
Format: Preprint
Published: 2024
Subjects:
Online Access:https://arxiv.org/abs/2406.16400
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author Qiu, Jinniao
Ware, Antony
Yang, Yang
author_facet Qiu, Jinniao
Ware, Antony
Yang, Yang
contents This paper is devoted to the price-storage dynamics in natural gas markets. A novel stochastic path-dependent volatility model is introduced with path-dependence in both price volatility and storage increments. Model calibrations are conducted for both the price and storage dynamics. Further, we discuss the pricing problem of discrete-time swing options using the dynamic programming principle, and a deep learning-based method is proposed for numerical approximations. A numerical algorithm is provided, followed by a convergence analysis result for the deep-learning approach.
format Preprint
id arxiv_https___arxiv_org_abs_2406_16400
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Stochastic Path-Dependent Volatility Models for Price-Storage Dynamics in Natural Gas Markets and Discrete-Time Swing Option Pricing
Qiu, Jinniao
Ware, Antony
Yang, Yang
Mathematical Finance
This paper is devoted to the price-storage dynamics in natural gas markets. A novel stochastic path-dependent volatility model is introduced with path-dependence in both price volatility and storage increments. Model calibrations are conducted for both the price and storage dynamics. Further, we discuss the pricing problem of discrete-time swing options using the dynamic programming principle, and a deep learning-based method is proposed for numerical approximations. A numerical algorithm is provided, followed by a convergence analysis result for the deep-learning approach.
title Stochastic Path-Dependent Volatility Models for Price-Storage Dynamics in Natural Gas Markets and Discrete-Time Swing Option Pricing
topic Mathematical Finance
url https://arxiv.org/abs/2406.16400