Alternative Asset Valuation With Stochastic Default Modeling
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Solution Overview
Problem
Existing asset classes, such as artwork and alternative assets, lack robust markets for efficient valuation, hindering effective financial planning and management.
Innovation Solution
A computer-implemented method and system for evaluating and pricing alternative asset products, including stochastic simulation models to project cashflows, determine Default probabilities, and set Financing parameters to achieve a desired credit rating.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional valuation methods are used for alternative assets, then the valuation process is simple, but the valuation accuracy and reliability are insufficient due to lack of robust markets
Solution Approach 1:
The valuation system segments the complex task of alternative asset valuation into multiple distinct modules: cashflow projection module, stochastic simulation module, probability of default calculation module, and credit rating module. Each module handles a specific aspect of the valuation process, allowing for specialized algorithms and methods to be applied to each segment, thereby improving overall valuation accuracy while managing system complexity through modular design.
Solution Approach 2:
The patent introduces a computer system as an intermediary between the asset data and the valuation output. This intermediary system processes raw asset information through multiple computational layers (cashflow projections, stochastic simulations, probability calculations) to produce refined valuation results. The intermediary system bridges the gap between incomplete market data and reliable valuation metrics, enhancing measurement precision through systematic data processing.
2Reliability
If comprehensive risk assessment models are implemented, then the reliability of financial decision-making improves, but the computational resources and time required increase significantly
Solution Approach 1:
The system performs preliminary cashflow projections and identifies key risk factors before conducting full stochastic simulations. By pre-processing asset data and establishing baseline scenarios, the system reduces the computational burden of subsequent probability of default calculations. This preliminary action allows for more comprehensive risk assessment while managing valuation time through staged processing.
Solution Approach 2:
The patent employs parameter changes by adjusting simulation variables and model inputs based on asset-specific characteristics. The system dynamically modifies simulation parameters (such as volatility assumptions, correlation structures, and cashflow timing) to match the specific risk profile of each alternative asset. This approach enables tailored risk assessment that improves reliability without requiring uniformly complex computational resources for all assets.
3Measurement precision
If stochastic simulation models are used to determine probability of default, then the credit rating accuracy improves, but the computational complexity and data requirements increase
Solution Approach 1:
The patent develops a universal stochastic simulation framework that can be applied across multiple alternative asset classes (real estate, private equity, infrastructure, etc.). The core simulation engine and probability of default calculation methods are designed to be asset-agnostic, requiring standardized input parameters that can be adapted to different asset types. This universal approach improves credit rating accuracy through consistent methodology while managing model complexity by avoiding asset-specific customizations for each valuation.
Data Source
AI summary
Disclosed is a computer-implemented system for processing algorithms to calculate a target level of financing of (or investment in) an alternative asset corresponding to a mid-point within a tolerance of a probability of default.