Pricing Model for Data Assets in Investment-Consumption Framework with Ambiguity
Xiaoshan Chen, Chen Yang, Zhou Yang

TL;DR
This paper develops a buyer-centric data asset pricing model based on informational value, using robust investment-consumption problems under ambiguity to derive explicit formulas and analyze properties.
Contribution
It introduces a novel pricing framework from the buyer's perspective, incorporating ambiguity and indifference pricing, with explicit formulas and numerical illustrations.
Findings
Derived general expressions for data asset prices.
Analyzed properties of prices under various market conditions.
Provided explicit pricing formulas for specific scenarios.
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…
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Taxonomy
TopicsDigital Platforms and Economics · Auction Theory and Applications · Blockchain Technology Applications and Security
