MICDE Ph.D. Student Seminar: Mingyan Tian

Topic: Pricing Physical Water Risk: Machine Learning Approaches to Quantify the Impact of Corporate Water Use Efficiencies in the Financial Markets

Corporate financial risk in their operations resulting from climate change and water resource limitations result in volatility in the capital markets. This has become a regulatory focus under the Task for Climate-Related Financial Disclosures (TCFD), forcing companies to disclose how climate is impacting their financial performance. This includes water risk exposures in water security and the impact of floods in supply chains, logistics, and operations resulting from water access. Corporate water intensity, a proxy for climate transition risk, relates water use efficiency to operational and capital asset risks. This information is generally not disclosed in financial or sustainability reports and is difficult for investors or regulators to assess, and for risk managers to address. This seminar focuses on the development of econometric models to price water risk in equities with the aim of informing corporate decision-makers and external stakeholders to assess and benchmark the financial valuation of water risk and to allow for comparison across industry sectors.

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