2025/12/5
Seyed Nourollah Mousavi

Seyed Nourollah Mousavi

Academic rank: Assistant Professor
ORCID: https://orcid.org/0000-0002-9208-1308
Education: PhD.
H-Index:
Faculty: Science
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E-mail: n-mousavi [at] araku.ac.ir
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Research

Title
European Option Valuation under SVSI Dynamics and Deep Learning Approach
Type
Presentation
Keywords
Option pricing, SVSI model, Conditional Monte Carlo, Deep learning.
Year
2025
Researchers Seyed Nourollah Mousavi

Abstract

This study examines option pricing under the SVSI model using deep learning. Monte Carlo simulation combined with Conditional Monte Carlo variance as a re- duction technique is employed to generate high-precision data for training the neural network. The results demonstrate that deep learning can be effectively used for option pricing, offering advantages in both computational accuracy and speed.