Abstract This paper develops a novel method for classifying oil price changes as supply or demand driven using information in asset prices. Motivated by a simple model, demand shocks are identified as returns to an index of oil producing firms which are orthogonal to unexpected changes in the VIX index, with supply shocks capturing the remaining variation in oil prices. Demand shocks are strongly positively correlated with market returns and economic output, whereas supply shocks have a strong negative correlation. The negative correlation of supply shocks and returns is strongest in industries that produce consumer goods, while the positive correlation of demand shocks is stronger for industries which use relatively large amounts of oil as an input.

The 1960s and 1970s witnessed rapid growth in the markets for new money market instruments, such as negotiable certificates of deposit (CDs) and Eurodollar deposits, as banks and investors sought ways around various regulations affecting funding markets. In this paper, we investigate the impacts of the deregulation and integration of the money markets. We find that the pricing and volume of negotiable CDs and Eurodollars issued were influenced by the availability of other short-term safe assets, especially Treasury bills. Banks appear to have issued these money market instruments as substitutes for other types of funding. The integration of money markets and ability of banks to raise funds using a greater variety of substitutable instruments has implications for monetary policy. We find that, when deregulation reduced money market segmentation, larger open market operations were required to produce a given change in the federal funds rate, but that the pass through of changes in the funds rate to other market rates was also greater.

Difference-in-differences (DID) is a method to evaluate the effect of a treatment. In its basic version, a “control group” is untreated at two dates, whereas a “treatment group” becomes fully treated at the second date. However, in many applications of the DID method, the treatment rate only increases more in the treatment group. In such fuzzy designs, a popular estimator of the treatment effect is the DID of the outcome divided by the DID of the treatment. We show that this ratio identifies a local average treatment effect only if the effect of the treatment is stable over time, and if the effect of the treatment is the same in the treatment and in the control group. We then propose two alternative estimands that do not rely on any assumption on treatment effects, and that can be used when the treatment rate does not change over time in the control group. We prove that the corresponding estimators are asymptotically normal. Finally, we use our results to reassess the returns to schooling in Indonesia.

ABSTRACT We show that the cost of trading on negative news, relative to positive news, increases before earnings announcements. Our evidence suggests that this asymmetry is due to financial intermediaries reducing their exposure to announcement risks by providing liquidity asymmetrically. This asymmetry creates a predictable upward bias in prices that increases preannouncement, and subsequently reverses, confounding short‐window announcement returns as measures of earnings news and risk premia. These findings provide an alternative explanation for asymmetric return reactions to firms' earnings news, and help explain puzzling prior evidence that announcement risk premia precede the actual announcements. Our study informs methods for research centering on earnings announcements and offers a possible explanation for patterns in returns around anticipated periods of heightened inventory risks, including alternative firm‐level, industry‐level, and macroeconomic information events.

We investigate how seasoned equity offerings (SEOs) by issuers with large customers affect both trading partners’ market values and the relationship's health. We hypothesize that SEOs reveal adverse information about an issuer's major customers and find that issuers and their large customers experience negative returns on SEO announcements. These results are more pronounced when customers have higher levels of information asymmetry and when customer-supplier relationships are particularly important. Large customers of issuers experience larger declines in post-SEO sales, operating performance, and credit ratings than large customers of non-issuers. Also, SEO issuer sales to large customers and relationship duration significantly decline.

ABSTRACT The literature on the usefulness of analysts’ cash flow forecasts is unsettled, with Call et al. ( ), Mohanram ( ), and Radhakrishnan and Wu ( ) providing evidence in favor of their usefulness, and Givoly et al. ( ), Bilinski ( ), and Ecker and Schipper ( ) questioning this. Target prices provide a good setting to test the usefulness of cash flow forecasts because they are an ultimate output of an analyst's valuation process to which cash flow forecasts are an input. Moreover, studying the effect of cash flow forecasts on target prices is more relevant for assessing their usefulness than is studying their effect on earnings‐forecast accuracy, as the accuracy of target prices requires a comparison with market prices, which are less subject to management influence than reported earnings. By improving an analyst's understanding of unexpected accruals and permanent earnings, a cash flow forecast can increase an analyst's target price accuracy and signal an analyst's superior forecasting ability. We examine whether, conditional on their earnings forecasts, analysts’ cash flow forecasts improve their target price accuracy. We find that when analysts issue cash flow forecasts, their target price accuracy increases. We also find that this accuracy increases with the accuracy of their cash flow forecasts. Finally, we find that this increased target price accuracy is greater for more challenging‐to‐value firms. Our study provides confirmatory evidence of the usefulness of analysts’ cash flow forecasts.

Using novel earnings calendar data, we show that firms’ advanced scheduling of earnings announcement dates foreshadows their earnings news. Firms that schedule later-than-expected announcement dates subsequently announce worse news than those scheduling earlier-than-expected announcement dates. Despite scheduling disclosures being observable weeks ahead of earnings announcements, we show that equity markets fail to reflect the information in these disclosures until the announcement itself. By also showing that option markets respond efficiently to volatility-timing information embedded in the same scheduling disclosures, we provide novel evidence that markets fail to react to information about future earnings despite investors immediately trading on the underlying signal.

We examine whether corporate social responsibility (CSR) creates value for seasoned equity issuers. Using a sample of seasoned equity offerings (SEOs) by U.S. companies between 2004 and 2013, we find a positive association between CSR performance and the stock price reaction to SEO announcements. Surprisingly, however, further tests reveal that seasoned equity issuers with high CSR scores tend to have higher post-SEO increases in cash holdings, and lower investments in real assets, than issuers with low CSR scores. Moreover, high-CSR issuers have worse post-SEO operating and stock price performance than low-CSR issuers. Together, our findings suggest that high CSR scores mislead shareholders into attributing value-increasing motives to seasoned equity issues.

We survey the literature on estimating risk preferences using field data. We concentrate our attention on studies in which risk preferences are the focal object and estimating their structure is the core enterprise. We review a number of models of risk preferences—including both expected utility (EU) theory and non-EU models—that have been estimated using field data, and we highlight issues related to identification and estimation of such models using field data. We then survey the literature, giving separate treatment to research that uses individual-level data (e.g., property-insurance data) and research that uses aggregate data (e.g., betting-market data). We conclude by discussing directions for future research. ( JEL C51, D11, D81, D82, D83, G22, I13)

We use a proprietary data set to test the implications of several asymmetric information models on how short-lived private information affects trading strategies and liquidity provision. Our identification rests on information acquisition before analyst recommendations are publicly announced. We provide the first empirical evidence supporting theoretical predictions that early-informed traders “sell the news” after “buying the rumor.” Further, we find distinct profit-taking patterns across different classes of institutions. Uninformed institutions, but not individuals, emerge as de facto liquidity providers to better-informed institutions. Placebo tests confirm that these trading patterns are unique to situations in which some investors have a short-lived informational advantage.