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

TL;DR

This paper introduces 3D tensor-based deep learning models for option price prediction, demonstrating their effectiveness over traditional models using Chinese market data.

Contribution

It presents novel deep learning models capable of processing 3D tensor data for improved option pricing accuracy.

Findings

Models outperform B-S and LSTM methods

Effective on Chinese market option data

Demonstrates practical applicability

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.