That's Interesting

  • 12 Best Practices for Leveraging Generative AI in Experimental Research

    This paper provides twelve best practices and discusses how each practice can help researchers accurately, credibly, and ethically use Generative AI (GenAI) to enhance experimental research.

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  • End of an Era: The Coming Long-Run Slowdown in Corporate Profit Growth and Stock Returns

    This paper shows that the decline in interest rates and corporate tax rates over the past three decades accounts for the majority of the period’s exceptional stock market performance. Lower interest expenses and corporate tax rates mechanically explain over 40 percent of the real growth in corporate profits from 1989 to 2019, however, the boost to profits and valuations from ever-declining interest and corporate tax rates is unlikely to continue, indicating significantly lower profit growth and stock returns in the future.

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  • Corporate Mergers and Acquisitions Under Lender Scrutiny

    This paper examines corporate mergers and acquisitions (M&A) outcomes under lender scrutiny. Using the unique shocks of U.S. supervisory stress testing, we find that firms under increased lender scrutiny after their relationship banks fail stress tests engage in fewer but higher-quality M&A deals. Evidence from comprehensive supervisory data reveals improved credit quality for newly originated M&A-related loans under enhanced lender scrutiny.

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  • Survey: Market Risk Premium and Risk-Free Rate used for 96 countries in 2024

    This paper contains the statistics of a survey about the Risk-Free Rate (RF) and the Market Risk Premium (MRP) used in 2024 for 96 countries.

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  • Noise in Expectations: Evidence from Analyst Forecasts

    Analyst forecasts outperform econometric forecasts in the short run but underperform in the long run. This article decomposes these differences in forecasting accuracy into analysts’ information advantage, forecast bias, and forecast noise. It finds that noise and bias strongly increase with forecast horizon, while analysts’ information advantage decays rapidly.

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  • Fundamental Analysis via Machine Learning

    This article examines the efficacy of machine learning in a central task of fundamental analysis: forecasting corporate earnings. We find that machine learning models not only generate significantly more accurate and informative out-of-sample forecasts than the state-of-the-art models in the literature but also perform better compared to analysts’ consensus forecasts.

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  • An Analysis of Decision Under Risk

    This paper presents a critique of expected utility theory as a descriptive model of decision making under risk, and develops an alternative model, called prospect theory. Choices among risky prospects exhibit several pervasive effects that are inconsistent with the basic tenets of utility theory.

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  • Quadrophobia: Strategic Rounding of EPS Data

    Managers’ incentives to round up reported earnings per share (EPS) cause an underrepresentation of the number 4 in the first post-decimal digit of EPS, or “quadrophobia.” This article has developed a novel measure of aggressive financial reporting practices based on a firm’s history of quadrophobia. Quadrophobia is pervasive, persistent, and successfully predicts future restatements, Securities and Exchange Commission enforcement actions, and class action litigation.

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  • Counterproductive Sustainable Investing: The Impact Elasticity of Brown and Green Firms

    The article develops a new measure of impact elasticity, defined as a firm’s change in environmental impact due to a change in its cost of capital. It shows empirically that a reduction in financing costs for firms that are already green leads to small improvements in impact at best. In contrast, increasing financing costs for brown firms leads to large negative changes in firm impact. Thus, sustainable investing that directs capital away from brown firms and toward green firms may be counterproductive, in that it makes brown firms more brown without making green firms more green.

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  • OECD Corporate Governance Factbook 2021

    Between 2005 and 2020, according to the OECD, almost 30,000 companies delisted from global markets via conventional takeovers, share buybacks and leverage buyouts. Over most of that period delistings were not matched by new issues so there was a net loss of listed companies, mainly in the US and Europe.

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