Knowledge that Transforms

Sequential financing is a popular strategy in corporate finance. However, depending on the type of financial instrument used to carry out the strategy, sequential financing can have many potential problems. This paper shows that certain types of convertibles can be deployed to resolve the problems completely. This may explain why convertibles are widely adopted to implement sequential financing in reality, especially among companies with many real options. We find that the call feature and some popular call restrictions are necessary for an efficient convertible. Indeed, almost all real-world convertibles have a call feature and call restrictions.

Large U.S. banks dramatically increased their capitalization during the 1990s, to the highest levels in more than 50 years. We document this buildup of capital and evaluate several potential motivations. Our results support the hypothesis that regulatory innovations in the early 1990s weakened conjectural government guarantees and enhanced bank counterparties' incentives to monitor and price default risk. We find no evidence that a bank holding company's (BHC's) market capitalization increases with its asset volatility prior to 1994. Thereafter, the data display a strong cross-sectional relation between capitalization and asset risk.

I present evidence of inefficient information processing in equity markets by documenting that negative information withheld by securities analysts is incorporated in stock prices with a significant delay. I estimate the extent of the withheld negative information based on the proportion of analysts who stop revising their annual earnings forecasts. This measure predicts negative earnings surprises and negative price reaction around earnings announcements. It could also be used to generate profitable trading strategies. I show that institutions tend to sell their stock holdings as my measure of unreported negative news increases, thus ameliorating the mispricing.

The tendency to introduce anonymity into financial markets apparently runs counter to the theory supporting transparency. This paper studies the impact of pre-trade transparency on liquidity in a market where risk-averse traders accommodate the liquidity demand of noise traders. When some risk-averse investors become informed, an adverse selection problem ensues for the others, making them reluctant to supply liquidity. Hence the disclosure of traders' identities improves liquidity by mitigating adverse selection. However, informed investors are effective liquidity suppliers, as their adverse selection and inventory costs are minimized. With endogenous information acquisition, transparency reduces the number of informed investors, thus decreasing liquidity. The type of information that traders hold and the effectiveness of insider trading regulation are crucial to distinguish between equilibria.

This paper shows that some of the most prominent risk-based theories offered as explanation for the value premium are at odds with data. The models proposed by Fama and French (1993), Lettau and Ludvingson (2001), Campbell and Vuolteenaho (2004), and Yogo (2006) can capture the cross-section of returns of portfolios sorted on book-to-market ratio and size, but not of portfolios sorted on book-to-market ratio and institutional ownership. These models generate economically large pricing errors in all the institutional ownership quintiles and each statistical test indicates that these pricing errors are significant. More generally, these results show that a minor alteration of the test assets can lead to a dramatically different answer regarding the validity of a given asset pricing model.

This paper examines whether firms manage analyst forecasts and the associated value consequences. We find that earnings forecasts tend to grow pessimistic over the forecast horizon and these forecast changes and their timing are key determinants of whether firms generate positive earnings surprises: Late forecasts that raise (lower) the consensus sharply reduce (raise) the probability of positive surprises. This findng is the opposite of that predicted if consensus revisions reflected new information arrival. Investors seem to be “misled”: downward consensus revisions lead to large abnormal returns following the earnings announcement. Paradoxically, downward forecast management reduces post-announcement share price, as the impact of reduced forecasts dominates the gain from generating positive surprises.

Despite the wide acceptance of return-based style analysis, the method has several limitations. One important drawback is the assumption that style exposures are time-invariant. We apply results on break tests developed in Bai and Perron (1998, 2003) to test for style breaks. We find strong evidence against the hypothesis of constant time exposures in daily return data for European equity funds. All funds exhibit at least one break, and 60% exhibit more than one break. We show that the main reason for style breaks is the mutual funds' reliance on conditional investment strategies based on public information and volatility estimates.

This paper investigates why traders hide their orders and how other traders respond to hidden depth. Using a logit model, we provide empirical findings suggesting that traders use hidden orders to manage both exposure risk and picking off risk. Using probit models, we show that hidden depth increases order aggressiveness. Our interpretation of this empirical evidence is threefold. First, hidden depth detection is possible and frequent. Second, when traders detecthidden volume at the best opposite uote, they strategically adjust their order submission to seize the opportunity for depth improvement. Third, traders' response when hidden depth is detected suggests either that they do not associate hidden orders with informed trading or that the risk of trading with an informed trader is widely offset by the opportunity for depth improvement.