Open Information: A Defining Perspective on Web Datasets for Carbon Pricing

2026-08-05

AI Summary

This study investigates the impact of online data—such as social media and news—on carbon market prices and introduces a novel category of “open information” that lies between public and private information. By integrating GDELT global event data with European Union Allowance (EUA) spot prices, the authors employ vector autoregressive (VAR) and GARCH-X models to conduct statistical tests and forecast returns. The research provides the first theoretical framework and empirical evidence supporting the incorporation of large-scale online data as an alternative information source in asset pricing. Findings demonstrate that open information exerts a statistically significant influence on carbon prices, thereby validating its efficacy in financial pricing and investment decision-making.

Abstract

The impact of web datasets on market prices has suggested the development of new sources of information, such as social media and web portals, indicating the possibility of an emergent phenomenon. We propose a defining perspective, termed open information, that adds to the existing types of public and private information. We demonstrate their existence and justify material significance for pricing. In this respect, we present statistical hypotheses to test for a web dataset, GDELT, integrated for carbon pricing, that is represented by EU Allowance spot prices. Tests are designed with VAR and GARCH-X formulations, and return forecasting. The outcomes cannot rule out the material existence of open information. The result is significant for providing a conceptual basis to integrate a vast number of web datasets as alternative data in investment decisions.

Problem

• open information
• web datasets
• carbon pricing
• market prices
• alternative data

Innovation

• open information
• web datasets
• carbon pricing
• GDELT
• alternative data