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CB-LMs: language models for central banking
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The Anchoring CEO: Cross-Domain Behavioral Consistency in Financial Decision Making
We examine whether managerial cognitive heuristics spill over from personal to corporate decisions. We identify “anchoring CEOs” who anchor on the 52-week high in personal stock trading and show that this behavior extends to corporate financial decisions. These CEOs are more likely to issue seasoned equity offerings near the 52-week high and place greater weight on the target’s 52-week high in acquisition pricing, with the latter associated with negative abnormal returns. The effect is stronger under competitive pressure and uncertainty but weaker with stronger governance and CEO experience. Our findings highlight cross-domain persistence in managerial heuristics and the role of governance in mitigating behavioral distortions.
Removing sludge: How rating system design affects the informativeness of crowd-based performance measures
Do different measures of stock market volatility risk have the same price?
Excess Liquidity, Cryptocurrency Returns, and the Moderating Role of Economic Policy Uncertainty
Competing creditor claims and loan recoverability: evidence from anti-recharacterization laws
Anti-recharacterization laws significantly increase the rights of securitization creditors by allowing the buyers of securitized assets to exclusively and immediately seize collateral in bankruptcy. However, strengthening the rights of securitization creditors can limit other creditors’ ability to recover loans. We find that, after a state adopts an anti-recharacterization law, local banks operating in the same state accrue more loan loss provisions, tighten their loan contracts, and incur higher future loan charge-offs. These findings are consistent with the argument that a safe harbor for securitization transactions advantages Wall Street-style structured finance at the expense of Main Street-style lending.
Measurement Error when Estimating Covenant Slack and Violations
An Empirical Investigation of New and Existing Non-GAAP Exclusion Quality Indicators
We examine commonly used indicators of aggressive non-GAAP exclusions and find that the majority perform poorly at identifying low-quality exclusions in terms of decision usefulness for investors. We propose a new firm-quarter-specific indicator that identifies instances in which GAAP earnings quality is high (i.e., when firms have less need to provide non-GAAP metrics) but managers disclose non-GAAP earnings anyway. Our new indicator is easy to calculate, requires minimal data, and performs far better at identifying low-quality exclusions than indicators used in prior research. Using our indicator, we find instances in which managers exclude earnings components that are decision useful, consistent with regulators’ concerns about the quality of some non-GAAP earnings disclosures. Our results are robust to a variety of specification checks. Data Availability: Data are derived from a combination of publicly available sources referenced in the article and third-party subscription data bases.