Neuroeconomics research shows that brain areas that generate emotional states also process information about risk, rewards, and punishments, suggesting that emotions influence financial decisions in a predictable and parsimonious way. We find that positive emotional states such as excitement induce people to take risks and to be confident in their ability to evaluate investment options, while negative emotions such as anxiety have the opposite effects. Beliefs are updated so as to maintain a positive emotional state by ignoring information that contradicts individuals’ prior choices. Marketplace features or outcomes of past choices may change emotions and thus influence future financial decisions.

The recent credit crisis has highlighted the importance of market liquidity and its interaction with the price of credit risk. We investigate this interaction by relating the liquidity of corporate bonds to the basis between the credit default swap (CDS) spread of the issuer and the par-equivalent bond yield spread. The liquidity of a bond is measured using a recently developed measure called latent liquidity, which is defined as the weighted average turnover of funds holding the bond, where the weights are their fractional holdings of the bond. We find that bonds with higher latent liquidity are more expensive relative to their CDS contracts after controlling for other realized measures of liquidity. Analysis of interaction effects shows that highly illiquid bonds of firms with a greater degree of uncertainty are also expensive, consistent with limits to arbitrage between CDS and bond markets, due to the higher costs of “shorting” illiquid bonds. Additionally, we document the positive effects of liquidity in the CDS market on the CDS-bond basis. We also find that several firm- and bond-level variables related to credit risk affect the basis, indicating that the CDS spread does not fully capture the credit risk of the bond.

We examine the relation between chief executive officers’ equity incentives and their use of performance-sensitive debt contracts. These contracts require higher or lower interest payments when the borrower’s performance deteriorates or improves, thereby increasing expected costs of financial distress while making a firm riskier to the benefit of option holders. We find that managers whose compensation is more sensitive to stock volatility choose steeper and more convex performance pricing schedules, while those with high delta incentives choose flatter, less convex pricing schedules. Performance pricing contracts therefore seem to provide a channel for managers to increase firms’ financial risk to gain private benefits.

We study earnings management (EM) efforts surrounding seasoned bond offerings using discretionary current accruals. We find that issuers tend to inflate earnings performance prior to an offering. In order for EM efforts to effectively mislead ratings agencies and the bond market, they must lead to inflated bond ratings and decreased offering yields. Regression results indicate the opposite; aggressive EM efforts are associated with lower initial ratings and higher offering yields. We also find a statistically lower proportion of subsequent downgrades for firms with the most aggressive EM efforts, which is inconsistent with these firms’ inflated initial ratings. While some firms may attempt to mislead ratings agencies and market participants by window-dressing earnings, these efforts appear to be counterproductive.

This paper examines the relation between information transmission and cross-autocorrelations. We present a simple model, where informed trading is transmitted from large to small stocks with a lag. In equilibrium, large stock illiquidity induced by informed trading portends stronger cross-autocorrelations. Empirically, we find that the lead-lag relation increases with lagged large stock illiquidity. Further, the lead from large stock order flows to small stock returns is stronger when large stock spreads are higher. In addition, this lead-lag relation is stronger before macro announcements (when information-based trading is more likely) and weaker afterward (when information asymmetries are lower).

We first develop a theory-based metric to judge the popularity of value weighting in a stock market. We then use our metric to document that although value weighting is less popular in emerging markets than in developed markets, its popularity is increasing almost everywhere. Finally, as we have better data for the United States, we explore why value weighting is becoming more popular in the United States.

Using stock returns around recommendation changes to measure the information produced by analysts, I find that analysts produce more firm-specific than industry-level information. Analysts produce more firm-specific information on stocks with higher idiosyncratic return volatilities. The amount of industry information produced by analysts increases with the absolute value of the stock’s industry beta and decreases with the stock’s idiosyncratic volatility. Other stocks in the industry also respond to the recommendation change, and the magnitude of the response increases with the absolute value of the industry beta of the recommended stock and that of other stocks in the industry. I also offer results on how investors may use analyst research more effectively and potentially improve their investment performance.

We study optimal replacement and abandonment decisions for real assets, when both revenues and costs are uncertain and deteriorate with age. We develop an implicit representation of the renewal boundary as the solution to a set of simultaneous equations. This quasi-analytical method has the merit of computational ease and transparency. We show that the correlation between revenues and operating costs has a significant influence on the renewal boundary, and that the increase in revenue immediately following a renewal has a greater relative influence on the boundary than either operating cost or renewal cost. The quasi-analytical method is sufficiently flexible to deal with other real option models involving 2 variables.

I develop new results for long-horizon predictive regressions with overlapping observations. I show that rather than using autocorrelation robust standard errors, the standard t-statistic can simply be divided by the square root of the forecasting horizon to correct for the effects of the overlap in the data. Further, when the regressors are persistent and endogenous, the long-run ordinary least squares (OLS) estimator suffers from the same problems as the short-run OLS estimator, and it is shown how similar corrections and test procedures as those proposed for the short-run case can also be implemented in the long run. An empirical application to stock return predictability shows that, contrary to many popular beliefs, evidence of predictability does not typically become stronger at longer forecasting horizons.

We study the role played by the informal links, or “connections,” between the chief executive officer (CEO) and the divisional managers of conglomerate organizations. Using data on a large sample of multisegment U.S. corporations from 1996 to 2004, we show that segments run by connected managers receive more investment and exhibit lower sensitivity to cash flow shortfalls (and exhibit higher sensitivity to other segments’ cash flow). At the firm level, having more connected managers presiding over segments with high Tobin’s Q improves resource allocation and increases firm value. These findings are consistent with the hypothesis that the mutual trust associated with connections reduces the need for wasteful reallocation of resources across divisions of conglomerate firms.

This paper proposes a measure of ex ante equity premium, IPOFDR, which is the average difference between the initial public offering (IPO) offer price and the 1st-trading-day close price. I test the idea in 3 ways. First, there is a positive relation between IPOFDR and future market returns. Second, changes in IPOFDR help explain the cross section of stock returns. Third, the predictive power of IPOFDR for stock returns reflects mainly its close relation with market variance and average idiosyncratic variance—arguably measures of systematic risk. These results cast doubt on the notion that the IPO 1st-day return is a measure of investor sentiment.