This paper studies the presence of hedge funds in the Chapter 11 process and their effects on bankruptcy outcomes. Hedge funds strategically choose positions in the capital structure where their actions could have a bigger impact on value. Their presence, especially as unsecured creditors, helps balance power between the debtor and secured creditors. Their effect on the debtor manifests in higher probabilities of the latter's loss of exclusive rights to file reorganization plans, CEO turnover, and adoptions of key employee retention plan, while their effect on secured creditors manifests in higher probabilities of emergence and payoffs to junior claims.

Using mutual fund redemptions as an instrument for price changes, we identify a strong effect of market prices on takeover activity (the “trigger effect”). An interquartile decrease in valuation leads to a seven percentage point increase in acquisition likelihood, relative to a 6% unconditional takeover probability. Instrumentation addresses the fact that prices are endogenous and increase in anticipation of a takeover (the “anticipation effect”). Our results overturn prior literature that finds a weak relation between prices and takeovers without instrumentation. These findings imply that financial markets have real effects: They impose discipline on managers by triggering takeover threats.

This paper empirically investigates directors' ownership in the mutual fund industry. Our results show that, contrary to anecdotal evidence, a significant portion of directors hold shares in the funds they oversee. Ownership patterns are broadly consistent with an optimal contracting equilibrium. That is, ownership is positively and significantly correlated with most variables that are predicted to indicate greater value from directors' monitoring. For example, directors' ownership is more prevalent in actively managed funds and in funds with lower institutional ownership. We also show considerable heterogeneity in ownership across fund families, suggesting family‐wide policies play an important role.

An AI analyst trained to digest corporate disclosures, industry trends, and macroeconomic indicators surpasses most analysts in stock return predictions. Nevertheless, humans win ‘‘Man vs. Machine’’ when institutional knowledge is crucial, e.g., involving intangible assets and financial distress. AI wins when information is transparent but voluminous. Humans provide significant incremental value in ‘‘Man + Machine’’, which also substantially reduces extreme errors. Analysts catch up with machines after ‘‘alternative data’’ become available if their employers build AI capabilities. Documented synergies between humans and machines inform how humans can leverage their advantage for better adaptation to the growing AI prowess.

We propose a tractable model of dynamic investment, spinoffs, financing, and risk management for a multidivision firm facing costly external finance. Our analysis formalizes the following insights: (i) Within‐firm resource allocation is based not only on divisions' productivity, as in winner‐picking models, but also their risk; (ii) firms may voluntarily spin off productive divisions to increase liquidity; (iii) diversification can reduce firm value in low‐liquidity states, as it increases the spinoff cost and hampers liquidity management; (iv) corporate socialism makes liquidity less valuable; and (v) division investment is determined by the ratio between marginal and marginal value of cash.

This paper studies the “confidential holdings” of institutional investors, especially hedge funds, where the quarter‐end equity holdings are disclosed with a delay through amendments to Form 13F and are usually excluded from the standard databases. Funds managing large risky portfolios with nonconventional strategies seek confidentiality more frequently. Stocks in these holdings are disproportionately associated with information‐sensitive events or share characteristics indicating greater information asymmetry. Confidential holdings exhibit superior performance up to 12 months, and tend to take longer to build. Together the evidence supports private information and the associated price impact as the dominant motives for confidentiality.

We experimentally investigate how managers' decisions to invest discretionary resources in the company's corporate social responsibility (CSR) initiatives are affected by whether the investment decision is denominated in financial or nonfinancial measures (i.e., the measurement basis used for decision making). We posit that nonfinancial measures bring attention to the society-serving nature of CSR investments, thus activating the pro-CSR social norms of the company and managers' personal CSR norms. Norm activation, in turn, influences managers' investment decisions to the extent that social norms are congruent with personal norms. As predicted, we find that the level of CSR investment is higher under a nonfinancial measurement basis than under a financial measurement basis, but only when the manager is personally supportive of CSR. Supplemental analysis indicates that CSR-supportive managers continue to invest more under a combined financial/nonfinancial measurement basis than under a financial measurement basis only. Theoretical and practical implications are discussed.