3D Tensor-based Deep Learning Models for Predicting Option Price

2021/06/05 by Muyang Ge, Ge, Muyang, Zhou Shen +5 · 1 citation
Computer Science · Physics and Astronomy · #Computational Finance (q-fin.CP) #Computational Physics and Python Applications #FOS: Economics and business #Medical Image Segmentation Techniques #NMR spectroscopy and applications

paper · pdf · doi:10.48550/arxiv.2106.02916

openalex publication_date 2021/06/05 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

Option pricing is a significant problem for option risk management and trading. In this article, we utilize a framework to present financial data from different sources. The data is processed and represented in a form of 2D tensors in three channels. Furthermore, we propose two deep learning models that can deal with 3D tensor data. Experiments performed on the Chinese market option dataset prove the practicability of the proposed strategies over commonly used ways, including B-S model and vector-based LSTM.

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• Option Pricing Using Ensemble Learning

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