Pricing Model for Data Assets in Investment-Consumption Framework with Ambiguity

Paper: arXiv 2505.16106

Authors: Xiaoshan Chen, Chen Yang, Zhou Yang

Abstract

Data assets are data commodities that have been processed, produced, priced, and traded based on actual demand. Reasonable pricing mechanism for data assets is essential for developing the data market and realizing their value. Most existing literature approaches data asset pricing from the seller’s perspective, focusing on data properties and collection costs, however, research from the buyer’s perspective remains scarce. This gap stems from the nature of data assets: their value lies not in direct revenue generation but in providing informational advantages that enable enhanced decision-making and excess returns. This paper addresses this gap by developing a pricing model based on the informational value of data assets from the buyer’s perspective. We determine data asset prices through an implicit function derived from the value functions in two robust investment-consumption problems under ambiguity markets via the indifference pricing principle. By the existing research results, we simplify the value function, using mathematical analysis and differential equation theory, we derive general expressions for data assets price and explore their properties under various conditions. Furthermore, we derive the explicit pricing formulas for specific scenarios and provide numerical illustration to describe how to use our pricing model.

Complexity vs Empirical Score

• Math Complexity: 8.5/10
• Empirical Rigor: 2.5/10
• Quadrant: Lab Rats — theoretically deep, empirically untested

Why this score: The paper provides a strong theoretical contribution by applying indifference pricing and robust control theory under ambiguity to data asset pricing from a buyer’s perspective. However, it is purely mathematical and lacks empirical validation, real-world data application, or a provided code repository.

Research Flowchart

  flowchart TD
    A[Research Goal: Price Data Assets from Buyer Perspective] --> B[Model Setup: Robust Investment-Consumption Framework under Ambiguity]
    C[Inputs: Market Parameters, Risk/Ambiguity Aversion, Data Info Value] --> B
    B --> D[Methodology: Indifference Pricing Principle via Value Functions]
    D --> E[Derivation: Mathematical Analysis & Differential Equations]
    E --> F[Outcomes: Implicit & Explicit Pricing Formulas + Numerical Sensitivity Analysis]