Climate Big Data and Green Financial Asset Pricing——A Carbon-Sensitive Valuation Model Based on Multi-Source Environmental Data

Haorong Ma

doi:10.62177/apemr.v2i6.939

Authors

Haorong Ma JT Academy

DOI:

https://doi.org/10.62177/apemr.v2i6.939

Keywords:

Climate Risk, Asset Pricing, Carbon-Sensitive Asset Pricing Models, Green Asset Excess Returns, Machine Learning Optimization

Abstract

Accelerating global efforts toward carbon neutrality are intensifying climate risks within financial markets. Traditional asset pricing models inadequately incorporate climate-related factors, resulting in systemic undervaluation of green assets. This study develops a Carbon-Sensitive Asset Pricing Model (CS-APM) integrating physical and transition risk factors. We conduct empirical analyses using data from six major economies spanning 2015-2024. Results indicate that singular climate risk factors exhibit positive sensitivity to asset returns. However, simultaneous exposure to dual risks triggers defensive capital reallocation and accelerates impairment of high-carbon assets. Emerging market assets demonstrate consistently positive sensitivity, while developed markets show greater climate risk resilience. Regulatory policy intensity maintains a nonlinear relationship with returns, where technological maturity and policy implementation jointly drive sustainable performance trends in industries. This modeling approach provides a new paradigm for quantifying climate risk premiums and redirecting capital toward climate-resilient sectors.

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