Using a novel typology of serial acquirers, we examine several puzzles documented in the prior literature. We show that acquisitions by different types of acquirers are driven by different factors, they acquire different sizes of targets, and subsequent acquisitions by acquirers are predictable ex ante. Controlling for market anticipation, the most frequent serial acquirers do not earn declining returns as they continue acquiring, while less frequent acquirers do. Our methodology enhances our understanding of serial acquisition dynamics, anticipation, and economic value adjustments. The methodology is likely to be relevant to topics related to event anticipation beyond those covered in this study.

Speculative language in corporate disclosures can convey valuable information about firms’ fundamentals. We evaluate this idea by developing a measure for speculative statements based on sentences marked with the “weasel tag” on Wikipedia. In the 16-week test period after filing, greater use of speculative statements in 10-Ks predicts higher and nonreverting abnormal returns, more insider and informed buying, and higher news sentiment. These findings imply that managers’ usage of speculative language in 10-Ks reflects voluntary disclosure of their private information about the positive prospects of events when market implications of the events are uncertain and thus have room for (re)interpretation.

We examine expectation documents’ effectiveness as an activism tool. We use the Norwegian sovereign wealth fund’s release of a corporate governance expectation document as a natural experiment. We introduce a novel, three-way analytical decomposition of the firms, the fund, and their joint response to this document. Firms’ governance practices adapt to the fund’s new portfolio-wide governance preferences, with heterogeneous responses across ownership and firm characteristics. The fund’s investment policies also change, even at the expense of financial returns. Overall, our research demonstrates the potential effectiveness of expectation documents as an emerging, low-cost activism tool for universal investors.

This article studies the optimal design of bank capital regulations when capital markets are subject to adverse selection. I show how the implementation of capital requirements can eliminate the information frictions that make raising capital costly by screening banks to reveal their private information to the market. The optimal regulations induce information revelation via recapitalization programs when the banking sector is weak and pool the banks’ private information via uniform capital requirements otherwise. Optimal capital requirements are linked to the securities issued to meet them, demonstrating potential welfare gains from incorporating more and less informationally sensitive securities into the design of capital regulations. Finally, the analysis generates insights into the joint design of equity capital requirements and additional tier 1 capital securities.

Data-driven lending relies on the calibration of models using training periods. We find that this type of lending is not resilient in the presence of economic conditions that are materially different from those experienced during the training period. Using data from a small business fintech lending platform, we document that the small business credit supply collapsed during the COVID-19 crisis of March 2020 even though the demand for loans doubled relative to pre-pandemic levels. As the month progressed, most lenders significantly reduced or halted their lending activities, likely due to the heightened risk of model miscalibration under the new economic conditions.

We model the execution of a large uninformed sell order in the presence of strategic competitive market makers. We solve for the unique symmetric equilibrium of the model in closed form. Analysis of this equilibrium reveals that large orders unequivocally benefit market makers, while smaller investors stand to benefit only if the order trades with a sufficiently high intensity. The equilibrium results further provide a rationale for the empirically observed patterns of (1) shorter orders trading at higher intensities and (2) price pressures potentially subsiding before large orders stop executing.

As early as 2015, financial regulators were developing disclosure frameworks aimed at enabling capital markets to price climate risks. Yet the literature on sustainability disclosure offers little insight into how regulatory agendas change, instead focusing on how nongovernmental organizations drive voluntary disclosure. To address this deficiency, this paper charts how financial regulators came to embrace climate risk, analyzing how an array of non‐state initiatives became coordinated in highlighting climate‐related impairment risks. This coordination is conceptualized via scholarship on decentered regulation, allowing a first, theoretical, contribution by constructing and demonstrating one analytical approach to studying substantive change on sustainability. This paper draws on a 25‐month participant observation of a United Nations standard‐setting project, supported by semi‐structured interviews. This allows a second, empirical, contribution by mapping how an accounting device, the so‐called “carbon budget” (the maximum amount of cumulative greenhouse gas emissions that limits the probability of exceeding 2°C of warming to 20%), coordinated this array of non‐state action toward resolving a core trade‐off: if we burn our current fossil fuel reserves, we will exceed our warming targets. The paper then shows how these coordinated efforts pressured regulatory authorities to intervene on how finance affects and is affected by climate change.

This paper presents an approach for pricing gold from investors’ perspective. The model is based on no-arbitrage principles with minimal structural assumptions. There is no need to specify investor preferences. When fitted to match 10-year real U.S. Treasury rates, the model can replicate the salient fluctuations in the time series of gold prices since 2007. The model is also able to capture key patterns of CME Comex gold futures prices. The model implies that the majority of the value of gold is due to its role as an investment asset.

We use a long time-series from Australia to shed light on economic factors that led to audit market concentration and the Big N. We show that increases in the size of a small number of public companies was an important factor that led to large audit firms and market concentration. We also show that emerging Big N firms made sunk cost investments, including in the ability to provide industry expertise and non-audit services, which allowed them to retain clients, differentiate, and grow. These changes occurred around the time the profession lifted restrictions on advertising, which helped facilitate differentiation, and that larger, more complex clients switched to emerging Big N firms while smaller clients switched to non-Big N firms. We do not find that increases in audit market concentration reduced competition; our results instead suggest the audit market became more competitive over time.