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Stock Returns, Implied Volatility Innovations, and the Asymmetric Volatility Phenomenon

Journal of Financial and Quantitative Analysis 2006 41(2), 381-406
We study the dynamic relation between daily stock returns and daily innovations in optionderived implied volatilities. By simultaneously analyzing innovations in index- and firmlevel implied volatilities, we distinguish between innovations in systematic and idiosyncratic volatility in an effort to better understand the asymmetric volatility phenomenon. Our results indicate that the relation between stock returns and innovations in systematic volatility (idiosyncratic volatility) is substantially negative (near zero). These results suggest that asymmetric volatility is primarily attributed to systematic market-wide factors rather than aggregated firm-level effects. We also present evidence that supports our assumption that innovations in implied volatility are good proxies for innovations in expected stock volatility.

Trading around macroeconomic announcements: Are all traders created equal?

Journal of Financial Intermediation 2006 15(4), 470-493
This paper examines the effects of macroeconomic announcements on equity index markets using high frequency transactions data for the regular and E-mini S&P 500 index futures contracts. For ten types of announcements that significantly affect prices, we analyze the price adjustment process and the trading patterns of exchange locals and off-exchange customers around the announcements. We find a large increase in trading activity immediately after the announcement. The results also show that during this initial surge in trading activity, locals are able to time their trades better than off-exchange traders even when locals do not have the advantage of access to the order flow. The trading strategy followed by exchange locals in the first 20 seconds after the announcement tends to be profitable, while off-exchange traders tend to make losing trades over the same time period. These results lend evidence that local traders tend to react to the macroeconomic information faster than off-exchange traders.

An Experimental Test of the Interaction of the Insurance and Information‐Signaling Hypotheses in Auditing*

Contemporary Accounting Research 2006 23(1), 267-289
Three incentives for hiring auditing services have been proposed in the literature: (1) to signal outsiders about the company's prospects, (2) to provide a potential source of loss recovery for investors (insurance), and (3) to reduce agency costs. The objective of this study is to examine the potential for the first two (signaling and insurance) to interact while controlling for agency costs. We conduct an experiment in which highly experienced financial analysts provide stock price estimates for a company that is under financial stress. We manipulate, between participants, the signal provided by the audit opinion (going‐concern modification, yes/no) and the ability of investors to recover losses from auditors. The key finding is that the effect of the going‐concern opinion on investor value judgements is moderated by the extent to which the auditor provides an insurance function. Specifically, the negative effect of a going‐concern opinion on the analysts' stock price estimates is reduced by the extent that the environment treats the auditor as an insurer.

Admission, Tuition, and Financial Aid Policies in the Market for Higher Education

Econometrica 2006 74(4), 885-928
We present an equilibrium model of the market for higher education. Our model simultaneously predicts student selection into institutions of higher education, financial aid, educational expenditures, and educational outcomes. We show that the model gives rise to a strict hierarchy of colleges that differ by the educational quality provided to the students. We also develop a new estimation procedure that exploits the observed variation in prices within colleges. Identification is based on variation in endowments and technology. It does not rely on observed variation in potentially endogenous characteristics of colleges such as peer quality measures and expenditures. We estimate the structural parameters using data collected by the National Center for Education Statistics and aggregate data from Peterson's and the National Science Foundation.