W-shaped implied volatility curves in a variance-gamma mixture model

In liquid option markets, W-shaped implied volatility curves have occasionally been observed. We introduce a single-period market model based on a mixture of two variance-gamma distributions – representing the diverging views of two groups of investors – in which such shapes can be reproduced. This is in contrast to lognormal models, where at least three different distributions have to be mixed in order to produce a W-shape, as shown by Glasserman and Pirjol [Quantitative Finance, 23(4), 2023]. Next to analytic proofs for the appearance of W-shapes curves, we also provide an explicit option pricing formula for our model. The methodology we develop can possibly be extended and applied to other mixture models constructed from (semi-)heavy-tailed distributions, offering a systematic way of capturing complex implied volatility patterns.

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Publication Details

Journal
Frontiers of Mathematical Finance
Published
2025-01-01
DOI
https://doi.org/10.3934/fmf.2025009
Primary Topic
Stochastic processes and financial applications
Type
article
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article

W-shaped implied volatility curves in a variance-gamma mixture model

Martin Keller‐Ressel
Frontiers of Mathematical Finance
Stochastic processes and financial applications
article

W-shaped implied volatility curves in a variance-gamma mixture model

Martin Keller‐Ressel
article en

Abstract

In liquid option markets, W-shaped implied volatility curves have occasionally been observed. We introduce a single-period market model based on a mixture of two variance-gamma distributions – representing the diverging views of two groups of investors – in which such shapes can be reproduced. This is in contrast to lognormal models, where at least three different distributions have to be mixed in order to produce a W-shape, as shown by Glasserman and Pirjol [Quantitative Finance, 23(4), 2023]. Next to analytic proofs for the appearance of W-shapes curves, we also provide an explicit option pricing formula for our model. The methodology we develop can possibly be extended and applied to other mixture models constructed from (semi-)heavy-tailed distributions, offering a systematic way of capturing complex implied volatility patterns.

Frontiers of Mathematical FinanceVol. 6(0)
Technische Universität Dresden (DE)
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Openalex Percentile: Top 81%
Stochastic processes and financial applications
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