The Statistical and Economic Role of Jumps in Continuous-Time Interest Rate Models

This paper analyzes the role of jumps in continuous‐time short rate models. I first develop a test to detect jump‐induced misspecification and, using Treasury bill rates, find evidence for the presence of jumps. Second, I specify and estimate a nonparametric jump‐diffusion model. Results indicate that jumps play an important statistical role. Estimates of jump times and sizes indicate that unexpected news about the macroeconomy generates the jumps. Finally, I investigate the pricing implications of jumps. Jumps generally have a minor impact on yields, but they are important for pricing interest rate options.     

Industry‐Specific Human Capital,Idiosyncratic Risk,and the Cross‐Section of Expected Stock Returns

Human capital is one of the largest assets in the economy and in theory may play an important role for asset pricing. Human capital is heterogeneous across investors. One source of heterogeneity is industry affiliation. I show that the cross‐section of expected stock returns is primarily affected by industry‐level rather than aggregate labor income risk. Furthermore, when human capital is excluded from the asset pricing model, the resulting idiosyncratic risk may appear to be priced. I find that the premium for idiosyncratic risk documented by several empirical studies depends on the covariance between stock and human capital returns.     

Networks in Production: Asset Pricing Implications

In this paper, I examine asset pricing in a multisector model with sectors connected through an input‐output network. Changes in the network are sources of systematic risk reflected in equilibrium asset prices. Two characteristics of the network matter for asset prices: network concentration and network sparsity. These two production‐based asset pricing factors are determined by the structure of the network and are computed from input‐output data. Consistent with the model predictions, I find return spreads of 4.6% and ?3.2% per year on sparsity and concentration beta‐sorted portfolios, respectively.     

Renegotiation and the pricing structure of sovereign bank loans: Empirical evidence

It is generally accepted that banks offer renegotiation services to sovereign borrowers facing short-term liquidity shortages. However, the literature has yet to find evidence of such services from the pricing of sovereign bank loans. The research on the pricing of sovereign bank loans has focused on interest spreads alone, while the pricing structure typically includes an up-front fee, as well. In this paper, I explore empirically the economic motivations for such a pricing structure. I find that up-front fees are explained by the probability of renegotiation and by proxies for informational problems. My findings provide evidence that the unique pricing structure of bank loans helps banks provide sovereign borrowers with renegotiation services.     

Pricing and commitment by two‐sided platforms

I study pricing and commitment by platforms in two‐sided markets with the following characteristics: (i) platforms are essential bottleneck inputs for buyers and sellers transacting with each other; (ii) sellers arrive before buyers; and (iii) platforms can charge both fixed fees and variable fees (royalties). I show that a monopoly platform may prefer not to commit to the price it will charge buyers at the same time it announces its seller price if it faces unfavorable seller expectations. With competing platforms, commitment makes the existence of an exclusive equilibrium (in which sellers register with only one platform) less likely, but it has no impact on multi‐homing equilibria (in which sellers support both platforms) whenever these exist.     

Equity value,implied cost of equity and shareholders’ real options

This study investigates the effects of shareholders’ real options on (i) firm financial performance and (ii) estimations of the implied cost of equity. After measuring the equity value of steady‐state operations using the residual income model, and the abandonment and expansion options using the Black‐Scholes option pricing model, I find that firms with a large expansion (abandonment) option value experience better (worse) financial performance than those with a small such value. I also find that ignoring these options results in a downward bias in implied cost of equity estimates by an average of 1.23 percentage points.     

The Determinants of Underpricing for Seasoned Equity Offers

Seasoned offers were underpriced by an average of 2.2 percent during the 1980s and 1990s, with the discount increasing substantially over time. The increase appears to be related to Rule 10b‐21 and to economic changes affecting both IPOs and SEOs. Consistent with temporary price pressure, underpricing is positively related to offer size especially for securities with relatively inelastic demand. Underpricing is also positively related to price uncertainty and, after Rule 10b‐21, to the magnitude of preoffer returns. Additionally, I find that underpricing is significantly related to underwriter pricing conventions such as price rounding and pricing relative to the bid quote.     

What Drives the Cross‐Section of Credit Spreads?: A Variance Decomposition Approach

I decompose the variation of credit spreads for corporate bonds into changing expected returns and changing expectation of credit losses. Using a log‐linearized pricing identity and a vector autoregression applied to microlevel data from 1973 to 2011, I find that expected returns contribute to the cross‐sectional variance of credit spreads nearly as much as expected credit loss does. However, most of the time‐series variation in credit spreads for the market portfolio corresponds to risk premiums.     

New Evidence on Sources of Leverage Effects in Individual Stocks

I test Black's leverage effect hypothesis on a panel of U.S. stocks from 1997 to 2012. I find that negative stock return innovations increase the future volatility of equity returns by about 36% more than positive ones. There is a strong and positive relation between variation in the size of these leverage effects and variation in the firm's use of debt. I uncover this relation by applying the Fama/French/Carhart 4‐factor asset pricing model in the exponential generalized autoregressive conditional heteroskedasticity mean equation and by using panel data to control for firm‐ and time‐invariant unobservables via first differences and two‐way fixed effects.     

Presidential Address: Liquidity and Price Discovery

This paper examines the implications of market microstructure for asset pricing. I argue that asset pricing ignores the central fact that asset prices evolve in markets. Markets provide liquidity and price discovery, and I argue that asset pricing models need to be recast in broader terms to incorporate the transactions costs of liquidity and the risks of price discovery. I argue that symmetric information‐based asset pricing models do not work because they assume that the underlying problems of liquidity and price discovery have been solved. I develop an asymmetric information asset pricing model that incorporates these effects.     

Economic consequences of SFAS 142 goodwill write‐offs

This paper examines the economic consequences of goodwill write‐offs under Statement of Financial Accounting Standards No. 142 (SFAS 142). Although write‐off firms have performed poorly, it is evident that deteriorating economic performance explains only a small proportion of write‐offs. After controlling for endogeneity of write‐off choice, I fail to find evidence that investors and analysts fixate on SFAS 142 goodwill write‐offs. I also provide evidence that write‐off firms pay higher audit fees, suggesting that auditors charge higher fees in response to extra audit effort. These results are consistent with the principles of market efficiency, analyst‐forecast rationality and efficient audit pricing.     

Social learning with differentiated products

Learning from friends is a key process by which consumers acquire information about available products. This article embeds social learning in a model of firms producing differentiated products. I consider how the structure of social relationships between consumers influences pricing and welfare. In particular, how a variety of characteristics of social networks ‐ distribution of friendships, homophily, clustering, and correlations between an individual's preferences and number of friends ‐ influence these outcomes. I also find conditions under which consumer awareness and the sensitivity of demand to prices are useful measures of the informational efficiency of markets.     

A best choice among asset pricing models? The Conditional Capital Asset Pricing Model in Australia

We use Australian data to test the Conditional Capital Asset Pricing Model (Jagannathan and Wang, 1996). Our results are generally supportive: the model performs well compared with a number of competing asset pricing models. In contrast to the study by Jagannathan and Wang, however, we find that the inclusion of the market for human capital does not save the concept of the time‐independent market beta (it remains insignificant). We find support for the role of a small‐minus‐big factor in pricing the cross‐section of returns and find grounds to disagree with Jagannathan and Wang's argument that this factor proxies for misspecified market risk.     

The cross-market information content of stock and bond order flow

In this paper I test the hypothesis that trading activity in the stock and bond markets contains important marketwide pricing information. Using a large sample of actively traded stocks and U.S. Treasury securities, I find that aggregate order imbalances play a strong role in explaining cross-market returns. I interpret this as evidence that aggregate order flow reveals information about the risk preferences, beliefs, and endowments of the investor population that is relevant for pricing securities in both markets. I also find evidence that cross-market hedging is an important source of linkages across the two markets, especially during periods of elevated equity volatility.     

Nonfinancial Performance Measures and Promotion-Based Incentives

In this paper, I examine the sensitivity of promotion and demotion decisions for lower‐level managers to financial and nonfinancial measures of their performance and investigate the extent to which the behavior of lower‐level managers reflects promotion‐based incentives. Additionally, I test for learning versus effort‐allocation effects of promotion‐based incentives. I find that promotion and demotion decisions for store managers of a major U.S.‐based fast‐food retailer (QSR) are sensitive to nonfinancial performance measures of service quality and employee retention after controlling for financial performance. The likelihood of demotion in this organization is also sensitive to nonfinancial performance on the dimension of service quality, while the probability of exit is primarily sensitive to financial performance measures rather than nonfinancial performance measures. I also find evidence that the behavior of lower‐level managers is consistent with the incentives created by the weighting of nonfinancial performance measures in promotion decisions. Managers in locations where there is a higher ex ante probability of promotion and a higher potential reward upon promotion demonstrate significantly higher levels and rates of performance improvement in service quality. Finally, consistent with promotion‐based incentives inducing both effort‐allocation and learning effects, I find that performance‐improvement rates for service quality: (1) are higher in prepromotion periods in markets where promotions occur, (2) decrease immediately after the occurrence of a promotion in the same market area, and (3) remain higher than in markets where promotions do not occur. These findings provide some of the first empirical evidence on an alternative to the explicit weighting of nonfinancial metrics in compensation contracts as a mechanism for generating improvements in nonfinancial dimensions of performance.     

Relationship-Specific Assets and the Pricing of Underwriter Services

This paper investigates the effect of setup costs on the pricing of investment banking services. The existence of setup costs is predicted to result in lower underwriter spreads in IPOs for firms that are expected to issue again. Consistent with this prediction, I find significantly lower spreads for firms that make subsequent issues. I also find that a firm's likelihood of changing underwriters in a subsequent offer is related to the time between offerings and the underwriter's pricing performance in the IPO. These results suggest that the deviations from optimal IPO pricing carry a penalty for the underwriter.     

Intraday online investor sentiment and return patterns in the U.S. stock market

We implement a novel approach to derive investor sentiment from messages posted on social media before we explore the relation between online investor sentiment and intraday stock returns. Using an extensive dataset of messages posted on the microblogging platform StockTwits, we construct a lexicon of words used by online investors when they share opinions and ideas about the bullishness or the bearishness of the stock market. We demonstrate that a transparent and replicable approach significantly outperforms standard dictionary-based methods used in the literature while remaining competitive with more complex machine learning algorithms. Aggregating individual message sentiment at half-hour intervals, we provide empirical evidence that online investor sentiment helps forecast intraday stock index returns. After controlling for past market returns, we find that the first half-hour change in investor sentiment predicts the last half-hour S&P 500 index ETF return. Examining users’ self-reported investment approach, holding period and experience level, we find that the intraday sentiment effect is driven by the shift in the sentiment of novice traders. Overall, our results provide direct empirical evidence of sentiment-driven noise trading at the intraday level.     

Activity-Based Pricing in a Monopoly

In this article, I study the interaction between cost accounting systems and pricing decisions in a setting where a monopolist sells a base product and related support services to customers whose preference for support services is known only to them. I consider two pricing mechanisms—activity‐based pricing (ABP) and traditional pricing—and two cost‐accounting systems—activity‐based costing (ABC) and traditional costing, for support services. Under traditional pricing, only the base product is priced, whereas support services are provided free because detailed cost‐driver volume information on the consumption of support services by each customer is unavailable. Under ABP, customers pay based on the quantities consumed of both the base product and the support services because detailed cost‐driver volume information is available for each customer. Likewise, under traditional costing for support services the firm makes pricing decisions on cost signals that are noisier than they are under ABC. I compare the equilibrium quantities of the base product and support services sold, the information rent paid to the customers, and the expected profits of the monopolist under all four combinations of cost‐driver volume and cost‐driver rate information. I show that ABP helps reduce control problems, such as moral hazard and adverse selection problems, for the supplier and increases the supplier's ability to engage in price discrimination. I show that firms are more likely to adopt ABP when their customer base is more diverse, their customer support costs are more uncertain, their costing system has lower measurement error, and the variable costs of providing customer support are higher. Firms adopt ABC when their cost‐driver rates for support services under traditional costing are noisier measures of actual costs relative to their cost‐driver rates under ABC and when the actual costs of support services are inherently uncertain. I also show that cost‐driver rate information and cost‐driver volume information for support services are complements. Although the prior literature views ABC and activity‐based management (ABM) as facilitating better decision making, I show that ABC and ABP (a form of ABM) are useful tools for addressing control problems in supply chains.     

Derivative Pricing with Liquidity Risk: Theory and Evidence from the Credit Default Swap Market

We derive an equilibrium asset pricing model incorporating liquidity risk, derivatives, and short‐selling due to hedging of nontraded risk. We show that illiquid assets can have lower expected returns if the short‐sellers have more wealth, lower risk aversion, or shorter horizon. The pricing of liquidity risk is different for derivatives than for positive‐net‐supply assets, and depends on investors' net nontraded risk exposure. We estimate this model for the credit default swap market. We find strong evidence for an expected liquidity premium earned by the credit protection seller. The effect of liquidity risk is significant but economically small.     

Financial statement recasting and credit risk assessment

This article examines the importance of adjustments to corporate financial statements for credit risk assessment. Prior research has tended to examine individual adjustments one at a time. As correlations among adjustments and control variables may bias inferences when researchers examine a single adjustment and ignore other adjustments, our results provide important new information about previous research by documenting whether or not such bias exists. We find that financial statement recasting adjustments – which aim to better reflect firms' indebtedness, financing costs and recurring earnings than reported financial numbers – are reflected in bond yield spreads and have an economically significant impact on credit pricing and loss forecasting. Among individual adjustment categories, we find that those for off‐balance‐sheet leases, defined benefit pensions and securitized debt have an economically significant impact on credit pricing and loss forecasting.