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Research Interests

Computational and Mathematical Finance

Neural Networks and Scientific Machine Learning

Numerical Analysis and Differential Equations

Numerical Methods for PDEs and Data-driven Modeling

Publications

1. S. Bansal, S. Natesan, Richardson Extrapolation Technique for Generalized Black–Scholes PDEs for European Options, Computational and Applied Mathematics, 42(5) (2023), 238. (Springer, SCIE, IF: 2.5, MCQ: 0.47)

2. S. Bansal, S. Natesan, An Efficient Fourth-Order Numerical Scheme for Nonlinear Multi-Asset Option Pricing Problems, Mediterranean Journal of Mathematics, 21(7) (2024), 1–25. (Springer, SCIE, IF: 1.1, MCQ: 0.68)

3. S. Bansal, S. Natesan, A Novel Higher-Order Efficient Computational Method for Pricing European and Asian Options, Numerical Algorithms, 99 (2025), 1127-1159. (Springer, SCIE, IF: 1.7, MCQ: 1.21)

 

4. S. Badireddi, S. Bansal, S. Natesan, Numerical Solution of Passport Option Pricing Problem With Polynomial Neural Networks, Computational Economics, 1–32, 2025. (Springer, SCIE, IF: 1.9)

 

5. S. Bansal, S. Natesan, A Robust and Effective Numerical Technique for Solving Black–Scholes PDEs, Current Progress in Interdisciplinary Research. (In Press)

 

6. S. Bansal, S. Natesan, An Efficient Robust Computational Method for Solving Black–Scholes PDEs, Mathematical Communications, 2025. (Mathos, SCIE, IF: 0.7, MCQ: 0.19)

 

7. S. Bansal, S. Natesan, An Accurate and Stable Numerical Method for Pricing Asian Options, Methodology and Computing in Applied Probability, 2025. (Springer, SCIE, IF: 1.0, MCQ: 0.25)

 

8. S. Bansal, S. Natesan, An Efficient and Robust Computational Approach to Passport Option Pricing PDEs, Decisions in Economics and Finance, 2025. (Springer, ABDC-ranked B, IF: 0.7, MCQ: 0.19)

 

9. S. Bansal, S. Natesan, A Stabilized Finite Element Method for Solving Black–Scholes PDEs With Applications to Lookback Options, Indian Journal of Pure and Applied Mathematics, 2025. (Springer, SCIE, IF: 0.5, MCQ: 0.19)

 

10. S. Bansal, P. Boro, S. Natesan, Physics-Informed Neural Network for Option Pricing Weather Derivatives Model, Computers & Mathematics with Applications, 2025. (Elsevier, SCIE, IF: 2.5, MCQ: 1.04)

 

11. S. Bansal, P. Boro, S. Natesan, Application of Physics-Informed Neural Networks to Partial Integro-Differential Equations in Financial Modeling and Decision Making, Applied Soft Computing, 2025. (Elsevier, SCIE, IF: 6.6)

 

12. S. Bansal, S. Natesan, Physics-Informed Neural Networks: A New Frontier in Option Pricing, 2025. (Under review)

 

13. S. Bansal, S. Natesan, Physics-Informed Neural Networks for Accurate Pricing of American Options Under Jump-Diffusion Models, 2024. (Under review)​​

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