Knowledge that Transforms

This paper investigates the optimal sequencing of debt issues. Our theoretical model suggests that once firms issue debt with one level of seniority, they may have an incentive to alternate seniorities, because of violations of the priced absolute priority rule (APR). When we introduce explicit costs of class conflict, the model yields cases of alternating seniorities and other cases in which firms issue only one class of debt. The implications of the model are consistent with the observed regularities in a large database of debt issues. We test several other implications of our model as well.

We use nearly 500 shifts in statutory corporate and personal income tax rates as natural experiments to assess the effect of corporate and personal taxes on capital structure. We find both corporate and personal income taxes to be significant determinants of capital structure. Based on ex post observed summary statistics, across Organisation for Economic Co-Operation and Development (OECD) countries, taxes appear to be as important as other traditional variables in explaining capital structure choices. The results are stronger among corporate tax payers, dividend payers, and companies that are more likely to have an individual as the marginal investor.

We explore the determinants of equity price risk of nonfinancial corporations. Operating and asset characteristics are by far the most important determinants of risk. For the median firm, financial risk accounts for only 15% of observed stock price volatility. Furthermore, financial risk has declined over the last 3 decades, indicating that any upward trend in equity volatility was driven entirely by economic risk factors. This explains why financial distress (as opposed to economic distress) was surprisingly uncommon in the nonfinancial sector during the 2007–2009 crisis even as measures of equity volatility reached unprecedented highs.

Researchers in empirical corporate finance often use bounded ratios (e.g., debt ratios) as dependent variables in their regressions. Using the example of estimating the speed of adjustment toward target leverage, we show by Monte Carlo and resampling experiments that commonly applied estimators yield severely biased estimates, as they ignore that debt ratios are fractional (i.e., bounded between 0 and 1). We propose a new unbiased estimator for adjustment speed in the presence of fractional dependent variables that also controls for unobserved heterogeneity and unbalanced panel data. This new estimator is suitable for corporate finance applications beyond capital structure research.

This study examines whether religiosity at the county level is associated with future stock price crash risk. We find robust evidence that firms headquartered in counties with higher levels of religiosity exhibit lower levels of future stock price crash risk. This finding is consistent with the view that religion, as a set of social norms, helps to curb bad-news-hoarding activities by managers. Our evidence further shows that the negative relation between religiosity and future crash risk is stronger for riskier firms and for firms with weaker governance mechanisms measured by shareholder takeover rights and dedicated institutional ownership.

We make use of a large sample of transaction-level institutional trading data to test an extended version of Brennan and Hughes’ (1991) information production theory of stock splits. We compare brokerage commissions paid by institutional investors before and after a split, assess the private information held by them, and relate the informativeness of their trading to brokerage commissions paid. We show that institutions make abnormal profits net of brokerage commissions by trading in splitting stocks. We also show that the information asymmetry faced by firms goes down after stock splits. Overall, our empirical results support the information production theory.

We study the impact of parameter uncertainty on the expected utility of a multiperiod investor subject to quadratic transaction costs. We characterize the utility loss associated with ignoring parameter uncertainty, and show that it is equal to the product between the single-period utility loss and another term that captures the effects of the multiperiod mean-variance utility and transaction cost losses. To mitigate the impact of parameter uncertainty, we propose two multiperiod shrinkage portfolios and demonstrate with simulated and empirical data sets that they substantially outperform portfolios that ignore parameter uncertainty, transaction costs, or both.

This paper examines trading patterns and market integration using laboratory asset markets. Our markets are designed to approximately correspond to the trading day for stocks cross-listed in markets in Europe and North America. Some of our markets feature timing restrictions so that participants cannot trade across markets except during a fully integrated overlap period. Comparison of markets with and without timing restrictions shows that restrictions reduce trading activity and shift transactions to the overlap period. When asset values are extreme, price discovery can be impeded when trading restrictions exist. The measurement of liquidity suggests that trading restrictions increase overall spreads.

This study examines the informational content of options trading on acquirer announcement returns. We show that implied volatility spread predicts positively on the cumulative abnormal return (CAR), and implied volatility skew predicts negatively on the CAR. The predictability is much stronger around actual merger and acquisition (M&A) announcement days, as compared with pseudo-event days. The prediction is weaker if pre-M&A stock price has incorporated part of the information, but stronger if the acquirer’s options trading is more liquid. Finally, we find that a higher relative trading volume of options to stock predicts higher absolute CARs. The relation also exists among the target firms.

Two-pass cross-sectional regression (TPCSR) is frequently used in estimating factor risk premia. Recent papers argue that the common practice of grouping assets into portfolios to reduce the errors-in-variables (EIV) problem leads to loss of efficiency and masks potential deviations from asset pricing models. One solution that allows the use of individual assets while overcoming the EIV problem is iterated TPCSR (ITPCSR). ITPCSR converges to a fixed point regardless of the initial factors chosen. ITPCSR is intimately linked to the asymptotic principal components (APC) method of estimating factors since the ITPCSR estimates are the APC estimates, up to a rotation.