Initial Margin Calculation Using Filtered Historical Simulation
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Solution Overview
Problem
Conventional systems for collateralizing counterparty credit risk in financial products are inadequate for non-linear products and fail to consider diversification and correlations between financial products, leading to inaccurate initial margin determinations.
Innovation Solution
A system and method that utilize a risk factor simulation process, including a filtered historical simulation, to decompose complex financial products into components, model these components, and reassemble them to determine initial margin, while considering diversification and correlations within a portfolio.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a linear analysis approach is used to determine initial margin, then the calculation is simple and fast, but the accuracy is poor for non-linear financial products
Solution Approach 1:
The patent segments the initial margin calculation process into multiple simulation steps (historical simulation, Monte Carlo simulation, filtered historical simulation) to handle different product types. This allows the system to use simplified linear analysis for linear products while applying more complex simulation methods for non-linear products, thus maintaining calculation efficiency while improving accuracy for complex instruments.
Solution Approach 2:
The patent implements dynamic simulation approaches that adapt to the characteristics of different financial products. The system dynamically selects between historical simulation, Monte Carlo simulation, and filtered historical simulation based on product complexity, allowing the calculation method to change according to the specific requirements of each product type.
2Device complexity
If each financial product is analyzed individually, then the calculation process is simple, but diversification and correlations between products are not considered
Solution Approach 1:
The patent merges individual product analyses into a comprehensive portfolio-level simulation framework. By combining historical simulation data across multiple products and applying portfolio-level risk assessment, the system captures diversification effects and correlations between products, improving the accuracy of initial margin determination for portfolios.
Solution Approach 2:
The patent creates a universal simulation framework that can handle both individual product analysis and portfolio-level analysis. The same simulation infrastructure (historical simulation, Monte Carlo simulation) serves multiple purposes: individual product risk assessment, portfolio diversification analysis, and correlation measurement, reducing overall system complexity.
Data Source
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AI summary
An exemplary system according to the present disclosure comprises a computing device that in operation, causes the system to receive financial product or financial portfolio data, map the financial product to a risk factor, execute a risk factor simulation process involving the risk factor, generate product profit and loss values for the financial product or portfolio profit and loss values for the financial portfolio based on the risk factor simulation process, and determine an initial margin for the financial product. The risk factor simulation process can be a filtered historical simulation process.