Three essays on climate finance and international finance
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Date
2024-05-01
Authors
Qi, Zhen
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Abstract
This thesis includes three essays. In the first essay, In the first essay, we employ machine learning techniques to predict corporate bond returns globally. Utilizing a unique dataset, we identify strong predictability in international corporate bond markets. Notably, factors influencing U.S. bond returns differ significantly from those impacting non-U.S. markets, where downside risk and illiquidity play a more prominent role. Additionally, we observe variations in the degree of bond cross-country integration and bond-stock integration, with developed markets generally exhibiting higher integration than emerging markets.
The second essay investigates the impact of abnormal-temperature-related climate risk on bank loan pricing using syndicated loans from 35 countries. Our findings indicate that banks charge higher interest rates for borrowers with higher climate risk. We also find that climate risk affects loan spreads of both long-term and non-long-term loans, and this effect is more pronounced for non-long-term loans. Our cross-sectional analyses reveal that voluntary climate risk disclosures in conference calls by borrowers mitigate the impact of climate risk on loan spreads, especially when lead banks have less climate-risk-related lending experience. Furthermore, the U.S. borrowing cost for high-climate-risk borrowers decreases following SEC guidance on climate risk disclosure, while ESG disclosure requirements in 19 other countries do not alter climate risk's effect on bank loan pricing.
In the third essay, we explore the influence of climate risk disclosures in earnings conference calls on analyst forecast errors and dispersion for U.S. firms. The disclosure of physical climate risk correlates with smaller forecast errors, particularly after the SEC issued guidance. However, disclosures of regulatory and opportunity shocks related to climate change show no significant impact. Subsample analyses reveal that physical climate risk disclosures enhance forecast accuracy for industries sensitive to climate change, firms in regions affected by extreme weather events, and states with stronger beliefs in climate change. Overall, our findings suggest that physical climate risk disclosures in earnings conference calls contribute to more accurate analyst forecasts.
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Keywords
International Finance, Climate Finance, Return Predictability, Bank Loan Pricing, Climate Risk Disclosure, Analyst Forecast