We examine the relationship between IPO underpricing and litigation risk in an international setting using a sample of 13,759 firms that went public across 40 countries between 1991 and 2011. While the majority of single-country studies do not find support for the lawsuit avoidance hypothesis, we find a significant positive relationship between litigation risk and underpricing in a cross-country framework. Contrary to all single-country legal liability studies outside the U.S. and consistent with the U.S. studies of Tiniç (1988) and Lowry and Shu (2002), our empirical results support the insurance effect of the lawsuit avoidance hypothesis in an international context. Our findings imply that the degree of litigation risk in a given country affects the level of underpricing for firms that go public in that country. We conclude that differences in legal risk factors can partially explain differences in underpricing across countries.

We conducted a field experiment in Southern Ghana to test the effect of asymmetric information on intrahousehold allocation. A lottery was conducted, where prizes were distributed in public and in private. The results indicate that asymmetric information over windfalls has a differential effect on observable and concealable expenses, consistent with hiding. Husbands' public windfalls increase investment in assets and social capital, while there is no such effect when wives win. Private windfalls of both spouses are committed to cash (wives) or in-kind gifts (husband) which are either difficult to monitor or to reverse if discovered by the other spouse.

This paper explores whether and how political connections affect the likelihood of completing a cross-border M&A deal for Chinese publicly listed, but privately-owned enterprises (POEs) and the resulting firm performance. In line with our proposed political connection trade-off theory, we find that POEs with politically connected top managers are more likely to complete a cross-border M&A deal than POEs with no such connections, but that this comes at the cost of negative announcement returns and subsequent lower accounting performance. These findings support the idea that politically connected top managers engage in “political empire building” behavior at the cost of shareholders' wealth.

In this paper we examine institutional trading in proximity to takeover rumors by combining the ANcerno dataset of transaction-level institutional trades with a unique sample of takeover rumor ‘scoops’. We find that institutions are net buyers in firms which subsequently become subject to takeover speculation and that institutional trading predicts which rumored firms will eventually receive takeover bids. Segregating funds according to their propensity to trade, we show that those less likely to purchase rumored targets by chance over the pre-rumor period are more likely to identify firms which will receive bid proposals and that they trade more profitably over both the pre- and post-rumor periods. We test for the presence of informed trading in a variety of ways and conclude that institutional investors appear to trade on material private information which identifies the firms soon to be the target of takeover speculation.

This paper explores whether and how political connections affect the market for corporate bonds issued by privately owned enterprises (POEs) in China. We test two competing theories – the zero-default myth and the borrower channel theory – that offer alternative explanations for the effect of political connections on the likelihood of bond issuance, the costs of refinancing, the market reaction to a bond issue announcement, and the performance of the firm after the bond has been issued. Using a sample of Chinese POEs from 2007 to 2016, we show that – in line with the zero-default myth theory – politically connected POEs are more likely to issue corporate bonds as a debt financing instrument than their non-connected counterparts. They also achieve lower coupon rates (i.e., lower refinancing costs), despite exhibiting lower overall performance after bond issuance. We find that investors react positively to corporate bond-issuing announcements if the issuing firm is politically connected. At the same time, our research indicates that politically connected bond-issuing POEs in China have weaker corporate governance and a surprisingly higher default probability than non-connected issuers.

According to the existing literature, institutional investors have a significant impact on the litigation risk of publicly traded companies. This should be particularly true after the Private Securities Litigation Reform Act (PSLRA) of 1995 that encourages institutional investors to serve as lead plaintiffs in securities class actions. Using a large sample of securities class action lawsuits, we distinguish between different types of institutional investors based on their investment horizon and ownership structure and find that both factors significantly affect a firm's litigation risk. Short-term institutional investors are more likely to monitor firms through ex-post litigation, whereas long-term institutional investors prefer to monitor firms internally. Further, we document a nonlinear relation between the stock ownership of the largest institutional investor and a firm's litigation risk. In particular, as measures of long-term (short-term) ownership increase, the likelihood of litigation declines (increases). In summary, shareholder litigation may be an effective external monitoring device for short-term investors that serves as a substitute for internal corporate governance mechanisms.

We propose CTREND, a new trend factor for cryptocurrency returns, which aggregates price and volume information across different time horizons. Using data on more than 3,000 coins, we employ machine learning methods to exploit information from various technical indicators. The resulting signal reliably predicts cryptocurrency returns. The effect cannot be subsumed by known factors and remains robust across different subperiods, market states, and alternative research designs. Moreover, it survives the impact of transaction costs and persists in big and liquid coins. Finally, an asset pricing model that incorporates CTREND outperforms competing factor models, providing a superior explanation of cryptocurrency returns.