Option pricing mechanisms driven by backward stochastic differential equations
This paper presents a deep learning g-pricing framework integrating BSDEs for enhanced option pricing versus the traditional BSM model.
What it examines
This paper introduces a deep learning method that uses backward stochastic differential equations and a g-pricing mechanism to price options. It integrates neural networks with numerical BSDE solutions, addressing market data challenges and improving upon traditional models like Black-Scholes-Merton.
What it concludes
The study shows that the deep learning g-pricing model achieves lower absolute errors compared to the BSM model. Its potential applications include better market pricing, risk management, and hedging for options. Future work will refine relative error handling and joint parameter estimation.
Evidence objects
A new deep learning-based $$g$$-pricing method leveraging $$BSDEs$$ integrates neural networks to estimate $$g$$, achieving lower absolute pricing errors compared to the classic Black-Scholes-Merton model while addressing market complexities effectively.
key_findings bullet 1 · key_findings · validation V0
The innovative algorithm unifies option price estimation and hedging strategies within a single optimization framework, demonstrating flexibility across various option types and expiry dates while showing relative error performance remarkably.
key_findings bullet 2 · key_findings · validation V0
Empirical analysis with S&P 500 index option data confirms lower mean squared errors, yet highlights challenges like controlling relative errors and instability from quadratic growth in components, suggesting refinements notably.
key_findings bullet 3 · key_findings · validation V0
The paper introduces a deep learning-based g-pricing mechanism integrating backward stochastic differential equations ($BSDEs$) with modern neural networks for option pricing. It innovatively refines volatility estimation and derivative modeling by merging classical frameworks like the Black-Scholes model with data-driven techniques, delivering fresh perspectives and significant advancements in financial market analysis.
key_findings bullet 4 · key_findings · validation V0
Raw abstract and provenance
- … A typical BSDE computational problem involves solving an equation using a given … We propose a method that integrates the deep learning numerical computation of …
Source row: 1517 · abstract type: snippet