Advancing Financial Modeling: Integrating Copulas and Deep Learning for Enhanced Risk Management and Derivative Pricing

This review paper systematically examines the integration of copula-based methods into the realms of deep learning and machine learning, with a focus on their impact on the accuracy and sophistication of financial models. It encompasses an analysis of the application of copulas in the pricing of derivatives and delves into the enhancement of loss computation within credit portfolios and CDO pricing frameworks. Additionally, the paper scrutinizes the use of copulas in the calculation of Credit Valuation Adjustment (CVA) and the management of wrong way risk. Through an exhaustive literature review and synthesis of current practices, this paper aims to chart a comprehensive overview of the state-of-the-art in copula applications across financial modeling.