We study the relationship between U.S. corporate bond recovery rates and macroeconomic variables used in the credit risk literature. The least absolute shrinkage and selection operator (LASSO) is used in selecting macroeconomic variables. The LASSO-selected macroeconomic variables are considered to be explanatory variables in ordinary least squares regressions, bootstrap aggregating (bagging), regression trees, boosting, LASSO, ridge regression and support vector regression techniques. We compare the out-of-sample predictive power of two types of models (LASSO-selected models with models that add principal components derived from 179 macroeconomic variables as explanatory variables). We find the recovery models with LASSO-selected macroeconomic variables outperform suggested models in the literature.

This paper investigates whether elections delay regulatory action against failing financial institutions by exploiting the cross-sectional and time-series heterogeneity in the exogenous electoral cycles of US insurance regulators and governors. We find causal evidence that regulators delay interventions before elections. The extent of the delay is larger for elected regulators than regulators appointed by the governor. Interventions by appointed regulators are less likely before competitive gubernatorial elections. Regulatory governance mechanisms that constrain the discretion of regulators reduce the delays of appointed regulators but not elected. Finally, we find evidence that suggests electoral delays increase the ultimate costs of failure.

We study market segmentation effects using data on U.S. railroads that list their bonds in New York and London between 1873 and 1913. This sample provides a unique setting for such analysis because of the precision offered by bond yields in cost of capital estimation, the geography-specific nature of railroad assets, and ongoing substantial technological change. We document a significant reduction in market segmentation over time. While New York bond yields exceeded those in London in the 1870s, this premium disappeared by the early 1900s. However, the segmentation premium persisted in the more remote regions of the United States. Received June 18, 2015; editorial decision October 4, 2017 by Editor Robin Greenwood.

In this article, we use micro data on both trade and production for a sample of large Chinese manufacturing firms in the footwear industry from 2002 to 2006 to estimate an empirical model of export demand, pricing, and market participation by destination market. We use the model to construct indexes of firm-level demand, marginal cost, and fixed cost. The empirical results indicate substantial firm heterogeneity in all three dimension with demand being the most dispersed. The firm-specific demand and marginal cost components account for over 30% of market share variation, 40% of sales variation, and over 50% of price variation among exporters. The fixed cost index is the primary factor explaining differences in the pattern of destination markets across firms. The estimates are used to analyse the supply reallocation following the removal of the quota on Chinese footwear exports to the EU. This led to a rapid restructuring of export supply sources on both the intensive and extensive margins in favour of firms with high demand and low fixed costs indexes, with marginal cost differences not being important.

The size premium has been accused of having a weak historical record, being meager relative to other factors, varying significantly over time, weakening after its discovery, being concentrated among microcap stocks, residing predominantly in January, relying on price-based measures, and being weak internationally. We find, however, that these challenges disappear when controlling for the quality, or its inverse, junk, of a firm. A significant size premium emerges, which is stable through time, robust to specification, not concentrated in microcaps, more consistent across seasons, and evident for non-price-based measures of size, and these results hold in 30 different industries and 24 international equity markets. The resurrected size effect is on par with anomalies such as value and momentum in terms of economic significance and gives rise to new tests of, and challenges for, existing asset pricing theories.

Donald Trump's surprise election shifted expectations: corporate taxes would be lower and trade policies more restrictive. Relative stock prices responded appropriately. High-tax firms and those with large deferred tax liabilities (DTLs) gained; those with significant deferred tax assets from net operating loss carryforwards (NOL DTAs) lost. Domestically focused companies fared better than internationally oriented firms. A price contribution analysis shows that easily assessed consequences (DTLs, NOL DTAs, tax rates) were priced faster than more complex issues (net DTLs, foreign exposure). In sum, the analysis demonstrates that expectations about tax rates greatly impact firm values.

The Hou et al. (2015) q-factor model outperforms other factor models in capturing the price-to-high (PTH, the ratio of current price to 52-week high price) anomaly; that is, high-PTH stocks earn high future returns. PTH's relations with future profitability and future investment growth are both significantly positive, and they mirror PTH's relation with future returns in the cross section and by time horizons. Incorporating the information about future investment growth contained in price level variables (e.g., PTH) helps the q factors to capture better those anomalies rooted in future investment growth. Together, these results suggest that the PTH anomaly is consistent with the investment capital asset pricing model.

We explore the dynamics of informed trading around corporate announcements of merger bids, dividend initiations, SEOs, and quarterly earnings by calculating daily posterior probabilities of informed buying and selling. We find evidence of informed trading before the announcements and a significant part of the news in announcements is impounded in stock prices before the announcements by pre-event informed trading. We also find evidence of informed trading after the announcements. Most strikingly, the probability of informed trading after merger bids predicts the probability of the bid being withdrawn or met with a competing bid. For other announcements, post-announcement informed-trading probabilities predict subsequent returns. Received September 26, 2016; editorial decision December 17, 2017 by Editor Andrew Karolyi.

A common belief held among researchers and policy makers is that regulatory reliance has inflated market demand for credit ratings, despite their decreasing informational value. Advances in information technology, coupled with reputation losses following the subprime crisis, renew the question of whether investors still rely on ratings to assess credit risk. Using Moody’s 2010 scale recalibration, which was unrelated to changing issuer fundamentals, we find that ratings still matter to investors and to issuers—apart from any regulatory implications. Our results commend improved disclosure to mitigate mechanistic reliance on ratings and inefficiencies due to rating standards that vary across asset classes. Received October 9, 2015; editorial decision June 7, 2017 by Editor Andrew Karolyi.

We examine a specific channel through which director connectedness may improve monitoring: financial reporting quality. We find that the connectedness of independent, non-co-opted audit committee members has a positive effect on financial reporting quality and accounting conservatism. The effect is not significant for non-audit committee or co-opted audit committee members. Our results are robust to tests designed to mitigate self-selection. Consistent with connected directors being valuable, the market reacts more negatively to the deaths of highly connected directors than to the deaths of less connected directors. Better connected directors also have better career prospects, suggesting they have greater incentives to monitor.