---
title: Applying Informer for Option Pricing: A Transformer-Based Approach
url: https://www.ml-quant.com/papers/doi/10-5220-0013320900003890/
site: ML-Quant (https://www.ml-quant.com)
updated: 2026-09-26
license: Summaries CC BY 4.0; links go to the original sources
index: https://www.ml-quant.com/llms.txt
identifier: doi:10.5220/0013320900003890
source_url: http://dx.doi.org/10.5220/0013320900003890
featured: 2025-06-11
citations: 8
topic: Derivatives & Volatility
---


# Applying Informer for Option Pricing: A Transformer-Based Approach

The research uses the Informer neural network for option pricing in financial markets, showing its improved performance over traditional models and improving financial forecasting.

- Source: http://dx.doi.org/10.5220/0013320900003890
- Identifier: doi:10.5220/0013320900003890
- Released: 2025-06-05
- First featured: Quant Letter No. 101 (2025-06-11): https://www.ml-quant.com/issues/2025-06-11/
- Citations (Semantic Scholar): 8
- Published in: International Conference on Agents and Artificial Intelligence
- Topic: Derivatives & Volatility

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