Diversification to mitigate expropriation in the tobacco industry

While it is well established that diversifying acquisitions by large, cash-rich firms destroy shareholder wealth, we document positive abnormal returns to such acquisitions in the tobacco industry. We show that these abnormal returns are associated with proxies for lower expected expropriation costs. Specifically, we show that wealth creation increases in the degree of domestic geographic expansion afforded by the acquisition (increasing tobacco firms’ influence in more political districts) and in the liquidity of tobacco firms’ assets (converting cash to harder-to-expropriate operating assets). We also show that the threat of expropriation constrains payments to shareholders before expropriation becomes certain in 1998.     

Information friction and investor home bias: A perspective on the effect of global IFRS adoption on the extent of equity home bias

This paper provides a perspective on the effect of IFRS adoption on the tendency of investors to under-invest in foreign equities. We consider explanations for the equity home bias described in prior research and discuss research relevant to the informational consequences of global adoption of IFRS. Specifically, we evaluate whether IFRS adoption reduces information processing costs or decreases investor uncertainty about either the quality of financial reporting or the distribution of future cash flows. We predict that the effect of any reduction in information processing costs from the adoption of IFRS is likely to be small relative to the effects of other determinants of home bias such as the strength of investor protection mechanisms in foreign countries, behavioral biases toward familiar equities, and informational advantages related to geographical proximity. We argue that the quality of the information that investors have (or perceive they have) decreases with distance, conclude that global IFRS adoption is unlikely to affect home bias, and propose avenues for future research.     

Explaining CEO retention in misreporting firms

We propose a framework that advances our understanding of Chief Executive Officer (CEO) retention decisions in misreporting firms. Consistent with economic intuition, outside directors are more likely to fire (retain) CEOs when retention (replacement) costs are high relative to replacement (retention) costs. When the decision is ambiguous because neither cost dominates, outside directors are more likely to retain the CEO when they both benefit from selling stock in the misreporting period. We show that joint abnormal selling captures director–CEO alignment incrementally to biographical overlap. This new proxy operationalizes information sharing and trust, making it useful for studying economic decision-making embedded in social relationships.     

Measurement Error and Nonlinearity in the Earnings-Returns Relation

There is a long history of research which examines the relation between unexpected earnings and unexpected returns on common stock. Early literature used simple linear regression models to describe this relation. Recently, a number of authors have proposed nonlinear models. These authors find that the earnings-returns relation is approximately linear for small changes but is 'S'-shaped globally. However, unexpected earnings are generated by the sum of a measurement error and a true earnings innovation, so the apparent nonlinearity could be an artifact of nonlinearity in the measurement errors. Using a research design that minimizes the presence of measurement errors, we provide evidence consistent with the hypothesis that measurement errors contribute to the nonlinearities in the earnings-returns relation. While we are not suggesting that the earnings-returns relation is linear, our evidence suggests that there is no advantage to using a nonlinear model for large firms that are widely followed by analysts.     

Contextual Fundamental Analysis Through the Prediction of Extreme Returns

This study examines the usefulness of contextual fundamental analysis for the prediction of extreme stock returns. Specifically, we use a two-stage approach to predict firms that are about to experience an extreme (up or down) price movement in the next quarter. In the first stage, we define the context for analysis by identifying extreme performers; in the second stage we develop a context-specific forecasting model to separate winners from losers. We show that extreme performers share many common market-related attributes, and that the incremental forecasting power of accounting variables with respect to future returns increases after controlling for these attributes. Collectively, these results illustrate the usefulness of conducting fundamental analysis in context.