Research Paper#Numerical Methods, BSDEs, Option Pricing, Financial Modeling🔬 ResearchAnalyzed: Jan 3, 2026 06:27
Improved Boundary Error Control for BSDEs using Convolution-FFT
Analysis
This paper builds upon the Convolution-FFT (CFFT) method for solving Backward Stochastic Differential Equations (BSDEs), a technique relevant to financial modeling, particularly option pricing. The core contribution lies in refining the CFFT approach to mitigate boundary errors, a common challenge in numerical methods. The authors modify the damping and shifting schemes, crucial steps in the CFFT method, to improve accuracy and convergence. This is significant because it enhances the reliability of option valuation models that rely on BSDEs.
Key Takeaways
- •Proposes improvements to the Convolution-FFT (CFFT) method for solving Backward Stochastic Differential Equations (BSDEs).
- •Focuses on reducing boundary errors, a common issue in numerical solutions.
- •Modifies damping and shifting schemes within the CFFT framework.
- •Demonstrates improved accuracy and convergence through numerical results and error analysis.
Reference
“The paper focuses on modifying the damping and shifting schemes used in the original CFFT formulation to reduce boundary errors and improve accuracy and convergence.”