Faculdades Guarulhos

ABSTRACT We examine whether a simple quantitative measure of language can be used to predict individual firms' accounting earnings and stock returns. Our three main findings are: (1) the fraction of negative words in firm‐specific news stories forecasts low firm earnings; (2) firms' stock prices briefly underreact to the information embedded in negative words; and (3) the earnings and return predictability from negative words is largest for the stories that focus on fundamentals. Together these findings suggest that linguistic media content captures otherwise hard‐to‐quantify aspects of firms' fundamentals, which investors quickly incorporate into stock prices.

ABSTRACT The returns earned by U.S. equities since 1926 exceed estimates derived from theory, from other periods and markets, and from surveys of institutional investors. Rather than examine historic experience, we estimate the equity premium from the discount rate that equates market valuations with prevailing expectations of future flows. The accounting flows we project are isomorphic to projected dividends but use more available information and narrow the range of reasonable growth rates. For each year between 1985 and 1998, we find that the equity premium is around three percent (or less) in the United States and five other markets.

ABSTRACT We examine debenture yields over the period 1983–1991 to evaluate the market's sensitivity to bank‐specific risks, and conclude that investors have rationally reflected changes in the government's policy toward absorbing private losses in the event of a bank failure. Although this evidence does not establish that market discipline can effectively control banking firms, it soundly rejects the hypothesis that investors cannot rationally differentiate among the risks undertaken by the major U.S. banking firms.

ABSTRACT This paper derives a closed‐form solution for European options on pure discount bonds, assuming a mean‐reverting Gaussian interest rate model as in Vasicek [8]. The formula is extended to European options on discount bond portfolios.

ABSTRACT I exploit the adoption of state‐level labor protection laws as an exogenous increase in employee firing costs to examine how the costs associated with discharging workers affect capital structure decisions. I find that firms reduce debt ratios following the adoption of these laws, with this result stronger for firms that experience larger increases in firing costs. I also document that, following the adoption of these laws, a firm's degree of operating leverage rises, earnings variability increases, and employment becomes more rigid. Overall, these results are consistent with higher firing costs crowding out financial leverage via increasing financial distress costs.

Abstract. We describe and begin to evaluate a parameterization to include the vertical transport of hot gases and particles emitted from biomass burning in low resolution atmospheric-chemistry transport models. This sub-grid transport mechanism is simulated by embedding a 1-D cloud-resolving model with appropriate lower boundary conditions in each column of the 3-D host model. Through assimilation of remote sensing fire products, we recognize which columns have fires. Using a land use dataset appropriate fire properties are selected. The host model provides the environmental conditions, allowing the plume rise to be simulated explicitly. The derived height of the plume is then used in the source emission field of the host model to determine the effective injection height, releasing the material emitted during the flaming phase at this height. Model results are compared with CO aircraft profiles from an Amazon basin field campaign and with satellite data, showing the huge impact that this mechanism has on model performance. We also show the relative role of each main vertical transport mechanisms, shallow and deep moist convection and the pyro-convection (dry or moist) induced by vegetation fires, on the distribution of biomass burning CO emissions in the troposphere.

ABSTRACT During 2005 to 2007, the SEC ordered a pilot program in which one‐third of the Russell 3000 index were arbitrarily chosen as pilot stocks and exempted from short‐sale price tests. Pilot firms’ discretionary accruals and likelihood of marginally beating earnings targets decrease during this period, and revert to pre‐experiment levels when the program ends. After the program starts, pilot firms are more likely to be caught for fraud initiated before the program, and their stock returns better incorporate earnings information. These results indicate that short selling, or its prospect, curbs earnings management, helps detect fraud, and improves price efficiency.

ABSTRACT Kothari, Shanken, and Sloan (1995) claim that β s from annual returns produce a stronger positive relation between β and average return than β s from monthly returns. They also contend that the relation between average return and book‐to‐market equity (BE/ME) is seriously exaggerated by survivor bias. We argue that survivor bias does not explain the relation between BE/ME and average return. We also show that annual and monthly β s produce the same inferences about the β premium. Our main point on the β premium is, however, more basic. It cannot save the Capital asset pricing model (CAPM), given the evidence that β alone cannot explain expected return.

In this paper we study high-dimensional time series that have the generalized dynamic factor structure. We develop a test of the null of k0 factors against the alternative that the number of factors is larger than k0 but no larger than k1>k0. Our test statistic equals maxk0<kk1(γk−γk+1)(γk+1−γk+2), where γi is the ith largest eigenvalue of the smoothed periodogram estimate of the spectral density matrix of data at a prespecified frequency. We describe the asymptotic distribution of the statistic, as the dimensionality and the number of observations rise, as a function of the Tracy–Widom distribution and tabulate the critical values of the test. As an application, we test different hypotheses about the number of dynamic factors in macroeconomic time series and about the number of dynamic factors driving excess stock returns.

While vote-buying is common, little is known about how politicians determine who to target. We argue that vote-buying can be sustained by an internalized norm of reciprocity. Receiving money engenders feelings of obligation. Combining survey data on vote-buying with an experiment-based measure of reciprocity, we show that politicians target reciprocal individuals. Overall, our findings highlight the importance of social preferences in determining political behavior.

ABSTRACT An uninformed observer using the tools of mean variance and security market line analysis to measure the performance of a portfolio manager who has superior information is unlikely to be able to make any reliable inferences. While some positive results of a very limited nature are possible, e.g., when there is a riskless asset or when information is restricted to be “security specific,” in general anything is possible. In particular, a manager with superior information can appear to the observer to be below or above the security market line and inside or outside of the mean‐variance efficient frontier, and any combination of these is possible.

This study had as objective to propose a new approach for quality evaluation of variety trials for determination of cropping and use values (VCU), which considers three attributes simultaneously: magnitude of the residual variation, replication number, and genetic control of the trait under selection. It was also emphasized the need for using shrinkage estimators/predictors of genotypic values instead of unshrunk phenotypic means of varieties, i.e., the procedures should consider the genetic coefficient of determination of the traits, as well as the eventual heterogeneity of residual variance within varieties. Targeting an accuracy of 90%, it was concluded that Snedecor F test values associated to treatment effects in the analysis of variance should be above 5.0. The magnitude of genotypic variability of the traits is also involved in the F statistics. This means that the approach of fixing minimum values for replication number and maximum values for residual variation coefficient (CVe) is not sufficient. For traits related to yield (with low genetic coefficient of determination) the normally used replication number, between two and four, does not permit to reach the targeted accuracy, even if residual variation coefficients below 10% are aimed, and the experimentation is conducted on several sites and years. For that target accuracy it is recommended the use of at least six replications. It was also shown that shrinkage estimators provide more precise and reliable inferences concerning genotypic means of the varieties, and their use is encouraged. KEY-WORDS: Accuracy; shrinkage estimator; variance heterogeneity; biased estimator; variation coefficent.

Higher reversible capacity of 333 mA h g⁻¹ in Na cell is demonstrated for hard carbon derived from HCl-treated argan.

Abstract We analyze the dynamic investment decision of a firm subject to an endogenous financing constraint. The threat of future funding shortfalls lowers the value of the firm's timing options and encourages acceleration of investment beyond the first‐best optimal level. As well as highlighting another way by which capital market frictions can distort investment behavior, this result implies that (1) the sensitivity of investment to cash flow can be greatest for high‐liquidity firms and (2) greater uncertainty has an ambiguous effect on investment.

ABSTRACT We develop a framework for estimating expected returns—a predictive system —that allows predictors to be imperfectly correlated with the conditional expected return. When predictors are imperfect, the estimated expected return depends on past returns in a manner that hinges on the correlation between unexpected returns and innovations in expected returns. We find empirically that prior beliefs about this correlation, which is most likely negative, substantially affect estimates of expected returns as well as various inferences about predictability, including assessments of a predictor's usefulness. Compared to standard predictive regressions, predictive systems deliver different expected returns with higher estimated precision.

AbstractThe usual practice in using a control chart to monitor a process is to take samples of size n from the process every h hours. This article considers the properties of the X̄ chart when the size of each sample depends on what is observed in the preceding sample. The idea is that the sample should be large if the sample point of the preceding sample is close to but not actually outside the control limits and small if the sample point is close to the target. The properties of the variable sample size (VSS) X̄ chart are obtained using Markov chains. The VSS X̄ chart is substantially quicker than the traditional X̄ chart in detecting moderate shifts in the process.KeywordsDouble Sampling X̄ ChartShewhart Control ChartVariable Sampling Interval X̄ ChartVariable Sample Size X̄ Chart Additional informationNotes on contributorsAntonio F. B. CostaDr. Costa is an Assistant Professor in the Department of Production.

ABSTRACT We merge portfolio theories of home bias with corporate finance theories of insider ownership to create the optimal corporate ownership theory of the home bias. The theory has two components: (1) foreign portfolio investors exhibit a large home bias against countries with poor governance because their investment is limited by high optimal ownership by insiders (the “direct effect” of poor governance) and domestic monitoring shareholders (the “indirect effect”) in response to the governance and (2) foreign direct investors from “good governance” countries have a comparative advantage as insider monitors in “poor governance” countries, so that the relative importance of foreign direct investment is negatively related to the quality of governance. Using both country‐level data on U.S. investors' foreign investment allocations and Korean firm‐level data, we find empirical evidence supporting our optimal corporate ownership theory of the home bias.

Abstract Merton (1987) proposes that an increase in a firm's investor base increases the firm's value. In Japan, companies can reduce their stock's minimum trading unit—the number of shares in a “round lot”—which facilitates trading in the stock by small investors. We find that a reduction in the minimum trading unit greatly increases a firm's base of individual investors and its stock liquidity, and is associated with a significant increase in the stock price. Further, the stock price appreciation is positively related to an increase in the number of shareholders.

Abstract A multinomial probit (MNP) model is applied to the modeling of adoption decisions by farmers facing multiple technologies which can be adopted in various combinations. This model allows for full investigation of the interactions between decisions to adopt or not adopt several technologies. Estimation is carried out in a Bayesian framework employing Gibbs sampling to circumvent past difficulties encountered in maximum likelihood estimation of the MNP model. The model is estimated for a sample of U.S. apple growers with four possible sustainable production technology bundles. The results show that adoption decisions are most significantly influenced by off‐farm labor supply.

Abstract We investigate the political bias of a large language model (LLM), ChatGPT, which has become popular for retrieving factual information and generating content. Although ChatGPT assures that it is impartial, the literature suggests that LLMs exhibit bias involving race, gender, religion, and political orientation. Political bias in LLMs can have adverse political and electoral consequences similar to bias from traditional and social media. Moreover, political bias can be harder to detect and eradicate than gender or racial bias. We propose a novel empirical design to infer whether ChatGPT has political biases by requesting it to impersonate someone from a given side of the political spectrum and comparing these answers with its default. We also propose dose-response, placebo, and profession-politics alignment robustness tests. To reduce concerns about the randomness of the generated text, we collect answers to the same questions 100 times, with question order randomized on each round. We find robust evidence that ChatGPT presents a significant and systematic political bias toward the Democrats in the US, Lula in Brazil, and the Labour Party in the UK. These results translate into real concerns that ChatGPT, and LLMs in general, can extend or even amplify the existing challenges involving political processes posed by the Internet and social media. Our findings have important implications for policymakers, media, politics, and academia stakeholders.