This paper provides empirical evidence that increasing risk results in higher demand for hedging among firms. Through a natural experiment exploring the Korean Government's legislative change on shareholder class action, I show that firms increase the liability insurance coverage for their directors and officers in response to increased litigation risk, despite the increase in costs associated with buying further coverage. I further test the heterogeneous effects in two dimensions of corporations: industry classification, and type of shareholder-management relationship. The results confirm that firms in high litigation risk industries and those with high agency conflicts between shareholders and management increase their insurance coverage relatively more. Overall, the results demonstrate that corporations adjust their hedging demand in response to changing risk environment and that the adjustment depends on the level of risk exposure of individual firms.

We document a significant role for nonbanks in financing the green transition following the Paris Agreement, primarily through lending partnerships with banks. Using textual analysis to identify green loans, we show that nonbanks participate in a greater number of green syndicated loans and commit larger amounts in response to corporate demand for green financing. Such nonbank investment in green loans is associated with more favorable loan terms and is consistent with a nonbank-led expansion in credit supply rather than bank-driven risk offloading. Nonbank investment is highly sensitive to policy signals, suggesting that regulatory transition risk is a key driver. Overall, our findings show the potential for nonbanks to support the transition but only under credible political commitment to climate goals.

We examine global bank lending during geopolitical conflicts. Exploiting Russia’s 2014 countersanctions on the European agricultural industry, we analyze global banks’ syndicated lending to affected firms. We document a significant increase in credit supply to the sanctioned industry, accompanied by a significant increase in the shares of loans with lower spreads and longer maturities. The expansion of credit is not driven by incumbent banks alone. Instead, banks with little prior exposure to agriculture—particularly foreign banks headquartered in alternative export destinations where European firms are likely to redirect trade—account for a considerable proportion of the increased lending. This finding suggests banks actively rebalance their loan portfolio and strategic positioning in response to shifting trade flows. Our findings highlight the role of banks as intermediaries that adjust credit allocation across sectors during geopolitical disruptions, thereby cushioning targeted industries and facilitating their transition toward new markets.

We study the dynamics of information demand and supply in capital markets, focusing on how firms’ disclosures align with analysts’ information needs. Using a novel dataset from Visible Alpha, we analyze granular data from analysts’ forecasting models to understand the breadth of information they seek and how firms meet these demands through mandatory and voluntary disclosures. We document significant variation in the complexity of analysts’ models and the extent of firms’ disclosures, leading to some items in analysts’ models remaining undisclosed. This unmet information demand gives rise to a novel concept we term “uncertainty about the past” ( UP ). We investigate its implications for key capital market outcomes, including analyst forecast dispersion, market reactions to earnings announcements, and stock market liquidity. Our results demonstrate that UP plays a significant role in shaping the information environment, challenging the assumption that earnings announcements fully resolve uncertainty about past performance.

In about 20%–30% of cases where an analyst revises two outputs (namely, earnings estimates, target prices, or stock recommendations) simultaneously, the two estimates are revised in opposite directions. Existing literature notes that these inconsistent outputs are widespread, and concludes that they are lower-quality, driven by strategic bias, and are viewed as less valid by investors. We find that these characterizations are generally inaccurate. Apparent inconsistency is largely driven by accounting and economic factors, with only limited evidence that investment banking-related conflicts play a role. Moreover, inconsistent outputs are neither less accurate than consistent outputs nor do they resolve less investor uncertainty upon their release. Overall, our results suggest that researchers should be cautious in interpreting the correlation between analyst outputs as a measure of bias or quality, and in using a single analyst output as a proxy for an analyst's overall views.

Financial analysts closely follow a firm’s operations and assess the risks that it faces. In this paper, we examine whether analysts incorporate ESG risks into their stock recommendations and target prices. Specifically, we use a unique firm-day level dataset on negative ESG risk incidents to proxy for unobservable risk assessments of analysts. We find that analyst outputs predict future ESG incidents, suggesting that analysts incorporate ESG risks into their models. Our results are robust to controlling for ESG incidents that firms experienced in the past, and are stronger in more transparent information environments, and in the presence of more guidance on ESG issues from the Sustainability Accounting Standards Board. Importantly, we find that analysts incorporate ESG risks through adjusting discount rates rather than cash flow estimates. Overall, our results highlight the ability of financial analysts to synthesize and integrate ESG risks into their research.