Knowledge that Transforms

Once a good idea comes to mind, it is hard to avoid wondering why no one else has already taken advantage of it. Is it because the idea is not as good as it initially appears? This concern gives rise to a dilemma over whether to pursue the idea or abandon it despite its apparent promise, a dilemma we call “the good idea dilemma”. Paradoxically, the more compelling an idea appears, the more puzzling it becomes that others have not exploited it, thereby deepening the dilemma. We study this dilemma in a continuous-time game with multiple players, analyzing idea adoption dynamics and their economic implications. The dilemma yields both under-implementation of good ideas and over-implementation of bad ideas. Its adverse consequences equally affect trivial ideas that arise frequently and creative ideas that rarely do, but intensify for ideas accessible to larger audiences or with riskier outcomes, even under risk neutrality.

Prior studies on cryptocurrency momentum overlook liquidation risk and other real-world frictions and inadequately assess its profitability. We evaluate time-series and cross-sectional momentum addressing these issues. When portfolios are marked to market daily, many cross-sectional momentum portfolios are liquidated, and those with statistically significant mean returns often earn negative profits. The mean return is insufficient for testing profitability in the cryptocurrency market, where returns are heavily skewed and fat-tailed. Evidence of time-series momentum is strong, whereas evidence of cross-sectional momentum is almost nonexistent. Investor overconfidence and the disposition effect appear to be important drivers of cryptocurrencies’ price dynamics.

Corporations make substantial progress toward their Zero Routine Flaring commitments globally, particularly in Africa where preexisting environmental standards are weak. Moreover, committers’ flaring reductions on the continent are driven primarily by operational improvements rather than offloading assets and are concentrated among committers facing greater stakeholder pressure. Although flaring is higher for assets continuously operated by, awarded to, or divested to noncommitters, corporate actions to uphold commitments are associated with a conservatively estimated 10 percent net reduction in flaring in Africa without a corresponding reduction in oil production or local economic activity in extraction communities. Our findings suggest that environmental commitments are backed by corporate policies akin to establishing a uniform cost of pollution across the firm’s global operations and therefore may alleviate the problems posed by globally fragmented regulation. Data Availability: All data except for Enverus oil and gas are publicly available. Enverus is available for purchase on a subscription basis.

Based on a comprehensive visual deception score constructed from China’s mandatorily disclosed IPO roadshow videos using computer vision and machine learning, we find that visual cues embedded in these videos predict IPO financial fraud. The predictive power is incremental to financial, textual, and audio indicators. Further analyses show that these cues are well grounded in psychology research and focusing on the psychology-based deception-cue-area features improves fraud predicting performance. Furthermore, decomposing each video into five topics, we find that only the deception score of the topic on financial performance is positively associated with financial fraud. We further show that insiders of firms with higher visual deception scores are more likely to sell shares shortly after lock-up periods expire, and these firms experience significantly lower subsequent stock returns. Our study demonstrates the feasibility and potential value of using video information for fraud detection in accounting and finance.

We show that leading investor disagreement proxies have near-zero cross-correlation – making disagreement pricing inferences challenging. We develop a frictionless model that generates overpricing from latent disagreement, jointly rationalizes major proxies, and generates new testable predictions. Equilibrium interrelationships motivate a new disagreement measure, DIS, which is more predictive of returns cross-sectionally than major proxies and more consistently predictive across macroeconomic regimes. We provide evidence that the friction-based channel of Miller (1977) and a frictionless mechanism coexist and are empirically separable. DIS also provides a micro-founded, disagreement-based account of the IVOL puzzle, absorbing IVOL’s predictability while revealing its regime and friction dependence.