Pricing multi-asset options with tempered stable distributions

Abstract We derive methods for risk-neutral pricing of multi-asset options, when log-returns jointly follow a multivariate tempered stable distribution. These lead to processes that are more realistic than the better known Brownian motion and stable processes. Further, we introduce the diagonal tempered stable model, which is parsimonious but allows for rich dependence between assets. Here, the number of parameters only grows linearly as the dimension increases, which makes it tractable in higher dimensions and avoids the so-called “curse of dimensionality.” As an illustration, we apply the model to price multi-asset options in two, three, and four dimensions. Detailed goodness-of-fit methods show that our model fits the data very well.

Authors

Institutions

Publication Details

Journal
Financial Innovation
Published
2024-08-20
DOI
https://doi.org/10.1186/s40854-024-00649-9
Citations
2
Primary Topic
Stochastic processes and financial applications
Type
article
Field-Weighted Citation Impact
1.08
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Pricing multi-asset options with tempered stable distributions

Michael Grabchak, Yunfei Xia
2 citations
Financial Innovation
Stochastic processes and financial applications
1.08
article

Pricing multi-asset options with tempered stable distributions

Michael Grabchak, Yunfei Xia
article en
2 citations

Abstract

Abstract We derive methods for risk-neutral pricing of multi-asset options, when log-returns jointly follow a multivariate tempered stable distribution. These lead to processes that are more realistic than the better known Brownian motion and stable processes. Further, we introduce the diagonal tempered stable model, which is parsimonious but allows for rich dependence between assets. Here, the number of parameters only grows linearly as the dimension increases, which makes it tractable in higher dimensions and avoids the so-called “curse of dimensionality.” As an illustration, we apply the model to price multi-asset options in two, three, and four dimensions. Detailed goodness-of-fit methods show that our model fits the data very well.

Financial InnovationVol. 10(1)
University of North Carolina at Charlotte (US), Harbin Engineering University (CN)
Openalex Percentile: Top 21%
Stochastic processes and financial applications
1.08
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.