Search results

This paper investigates the role of economic disagreement in the cross-sectional pricing of individual stocks. Economic disagreement is quantified with ex ante measures of cross-sectional dispersion in economic forecasts from the Survey of Professional Forecasters (SPF), determining the degree of disagreement among professional forecasters over changes in economic fundamentals.

The authors introduce a broad index of economic disagreement based on the innovations in the cross-sectional dispersion of economic forecasts for output, inflation and unemployment so that the index is a shock measure that captures different aspects of disagreement over economic fundamentals and also reflects unexpected news or surprise about the state of the aggregate economy. After building the broad index of economic disagreement, the authors test out-of-sample performance of the index in predicting the cross-sectional variation in future stock returns.

Univariate portfolio analyses indicate that decile portfolios that are long in stocks with the lowest disagreement beta and short in stocks with the highest disagreement beta yield a risk-adjusted annual return of 7.2%. The results remain robust after controlling for well-known pricing effects. The results are consistent with a preference-based explanation that ambiguity-averse investors demand extra compensation to hold stocks with high disagreement risk and the investors are willing to pay high prices for stocks with large hedging benefits. The results also support the mispricing hypothesis that the high disagreement beta provides an indirect way to measure dispersed opinion and overpricing.

Most literature measures disagreement about individual stocks with the standard deviation of earnings forecasts made by financial analysts and examines the cross-sectional relation between this measure and individual stock returns. Unlike prior studies, the authors focus on disagreement about the economy instead of disagreement about earnings growth. The authors' argument is that disagreement about the economy is a major factor that would explain disagreement about stock fundamentals. The authors find that disagreement in economic forecasts does indeed have a significant impact on the cross-sectional pricing of individual stocks.

The purpose of this paper is to explore the overlooked relationship between politics and the performance of anomaly-based investment strategies.

Monthly long-short portfolios are formed based on relative mispricing scores according to the Stambaugh et al. (2012, 2015) relative mispricing measure. Portfolio performance is examined throughout various presidential terms. The design also introduces economic policy uncertainty (EPU) as a possible explanatory variable for portfolio performance.

The analysis reveals that anomaly-based returns are higher under Republican administrations than they are under Democratic administrations. Moreover, the results show that the impact of EPU on the relationship between the political party affiliation of the president and future anomaly-based returns are driven by the election and post-election years.

The examination of returns on a long-short portfolio may be of particular value to investment companies, such as hedge funds, who regularly employ this type of strategy.

While the impact of presidential terms on raw equity returns has been well examined, the paper is the first to examine the impact of presidential terms on the return of an anomaly-based investment strategy. EPU is also introduced as an important contributing factor.

The research aims to examine the impact of economic policy uncertainty (EPU) on a company's behaviour concerning its human capital. Additionally, the difference in effect for companies with specific human capital is analysed.

The hypotheses are tested on a multi-industry sample of large public companies from five European countries, using panel data modelling. The index of Baker et al. (2016) is used to measure EPU.

In the case of increasing EPU on one standard deviation, companies tend to reduce their human capital by approximately 1.7%. Moreover, despite theoretical assumptions, the effect on companies with more specific human capital is twice stronger. The heterogeneity of effect across countries and industries is also present.

Regulators and governments should consciously introduce changes in relation to regulations and decrease the uncertainty of economic policy to stimulate corporate investments in human capital.

This is the first study that considers the mechanism of EPU and its influence on corporate human capital. The results suggest that concerns regarding economic policy cause companies to reduce human capital.

Financial analysts have been found to be overconfident. The purpose of this paper is to study the ramifications of that overconfidence on the dispersion of earnings estimates as a predictor of the US business cycle.

Whether aggregate analyst forecast dispersion contains information about turning points in business cycles, especially downturns, is examined by utilizing the analyst earnings forecast dispersion metric. The primary analysis derives from logit regression and Markov switching models. The analysis controls for sentiment (consumer confidence), output (industrial production), and financial indicators (stock returns and turnover). Analyst data come from Institutional Brokers Estimate System, while the economic data are available at the Federal Reserve Bank of St Louis Economic Data site.

A rise in the dispersion of analyst forecasts is a significant predictor of turning points in the US business cycle. Financial analyst uncertainty of earnings estimate contains crucial information about the risks of US business cycle turning points. The results are consistent with some analysts becoming overconfident during the expansion period and misjudging the precision of their information, thus over or under weighting various sources of information. This causes the disagreement among analysts measured as dispersion.

This is the first study to show that analyst forecast dispersion contributions valuable information to predictions of economic downturns. In addition, that dispersion can be attributed to analyst overconfidence.

Anecdotal evidence suggests that emerging economy enterprises face higher uncertainty in business operations compared to their counterparts in more developed economies. However, there is little empirical evidence on this issue. The objective of this study is to fill this void in the literature and examine whether there is an association between the level of development of home country economy of a multinational corporation and uncertainty about future earnings measured by dispersion in analysts' earnings forecasts. After controlling for various firm‐ and country‐level factors, I find that the forecast dispersion tends to be larger for emerging economy enterprises (i.e., non‐U.S. firms cross‐listed in the U.S. whose home country economy is better characterized as emerging) than for developed economy enterprises (i.e., non‐U.S. firms cross‐listed in the U.S. whose home country economy is better characterized as developed), despite the fact that the emerging economy enterprises tend to be more heavily followed by analysts. Overall, the evidence supports the view that business uncertainty tends to be higher in emerging economies and highlights inherent difficulties associated with predicting future firm performance of the emerging economy enterprises.

This study aims to explore the relationship between product market competition (competition hereafter) and the quality of analysts’ forecasts.

This study uses industry-level (i.e. Herfindahl–Hirschman index), as well as firm-level (i.e. Lerner index) measures of competition and uses forecast accuracy and forecasts dispersion as proxies for analysts’ forecast quality. Further, this study considers a sample of Chinese-listed manufacturing companies for the period spanning 2005 to 2016 and uses various estimation techniques to empirically test the hypothesized relationship.

The results show that firms in highly competitive industries are characterized by greater accuracy and smaller dispersion in forecasts. Further, this positive association is more pronounced in SOEs as compared to NSOEs, and in industries characterized by intense competition. The sensitivity analysis further endorses the main results.

Presenting theoretical and empirical evidence, this study suggests that regulatory bodies should take steps to promote the competitive environment in China. This can help financial analysts in developing more accurate and reliable forecasts and ultimately can bring informational efficiency to the market. Finally, investors would be able to perform their business valuation process in a better way and make economic-useful decisions regarding their capital resource allocation.

The contribution of the current research is threefold: first, it adds to the limited literature available on this specific topic; second, this study examines the issue in China and further single out the influence of state-ownership and intensity of competition on the relation between competition and forecast properties; and third, this study provides theoretical arguments for the positive association between competition and forecasts quality while setting directions for future research on the topic and suggests the potential channels such as the reporting quality channel and the information disclosure channel that need to be explored further, to better understand the mechanism where competition influences the quality of analysts’ forecasts.

This paper aims to investigate the informativeness of rhetorical impression management patterns of CEO letters and examines whether these rhetorical features affect financial analysts’ forecasting behaviour.

The authors use textual analysis on a sample of 526 CEO letters of US firms and apply factor analysis on individual linguistic style measures to identify co-occurrence patterns of style features.

The authors identify three holistic style patterns (assertive acclaiming, cautious plausibility-based framing and logic-based rationalizing) and find that assertive rhetorical feature in CEO letters is negatively related with the dispersion of financial analysts’ earnings forecasts and positively associated with earnings forecast accuracy. CEOs’ use of a rationalizing rhetorical pattern tends to decrease the dispersion of financial analysts’ earnings, whereas a cautious plausibility-based rhetorical position is only marginally instrumental in getting more accurate earnings predictions.

Whilst impression management communication is often theorized as manipulative and void of real information content, the findings suggest that impression management serves both self-presentation and information-sharing purposes.

This paper elaborates on the co-occurrence of style characteristics in management communication and is a first attempt to validate the external ramifications of holistic style profiles of corporate narratives by focusing on an economic target audience.

This study aims to examine the effects of product market competition (PMC) on analysts’ earnings forecast attributes, particularly forecast accuracy and dispersion. The authors also investigate whether investor protection moderates the relationship between PMC and forecast attributes.

The sample covers 49,578 firm-year observations from 38 countries. This study uses an ordinary least squares regression, a Heckman two-stage regression and an instrumental two-stage least squares regression.

This study finds that PMC is associated with higher forecast accuracy and lower dispersion. The results also show that investor protection enhances the effect of PMC on forecast accuracy and dispersion. These findings imply that countries with strong investor protection have a better information environment, as exhibited by the stronger relationship between PMC and analysts’ forecast properties.

The findings highlight the importance of strong governance mechanisms in both the country and industry environments. Policymakers, including government agencies and financial regulators, can leverage these insights to formulate regulations that promote competition, ensure investor protection and facilitate informed investment decisions.

This study advances our understanding of how PMC affects analysts’ earnings forecast attributes. In addition, it pioneers evidence of the moderating role of investor protection in the relationship between PMC and forecast attributes.

This study examined the effect of different types of politically connected (PCON) Malaysian firms on analysts' forecast accuracy and dispersion.

The study identified different types of PCON firms according to Wong and Hooy's (2018) classification, which divided political connections into government-linked companies (GLCs), boards of directors, business owners and family members of government leaders. The sample covered the period 2007–2016, for which earnings forecast data were obtained from the Institutional Brokers' Estimate System (IBES) database and financial data were extracted from Thomson Reuters Fundamentals. We deleted any market consensus estimates made by less than three analysts and/or firms with less than three years of analyst forecast information to control for the impact of individual analysts' personal attributes.

The study found that PCON firms were associated with lower analyst forecast accuracy and higher forecast dispersion. The effect was more salient in GLCs than in other PCON firms, either through families, business ties or boards of directors. Further analyses showed that PCON firms—in particular GLCs—were associated with more aggressive reporting of earnings and poorer quality of accruals, hence providing inadequate information for analysts to produce accurate and less dispersed earnings forecasts. The results were robust even after addressing endogeneity issues.

This study found new evidence of the impact of different types of PCON firms in exacerbating information asymmetry, which was not addressed in prior studies.

This study has a significant practical implication for investors that they should be mindful of high information asymmetry in politically connected firms, particularly government-linked companies.

This is the first study to provide evidence of the impact of different types of PCON firms on analysts' earnings forecasts.

This paper relates to the literature on central bank (CB) transparency and inflation uncertainty. Considering that opacity is a possible source for inflation uncertainty the purpose of this paper is to test the hypothesis that increase in the dispersion of the degree of CB opacity generates higher levels of inflation uncertainty.

In a first step, the authors present a theoretical model that shows how increase in the dispersion of the degree of CB opacity creates higher levels of inflation uncertainty. In a second step, the authors test the assumption that increase in the dispersion of the degree of CB opacity generates higher levels of inflation uncertainty in the Brazilian economy.

The findings denote that CB transparency is an important tool for guiding public expectations and thus contributes to avoiding the uncertainty caused by CB preferences.

This paper extends the theoretical model presented by de Mendonça and Simão Filho (2007) by the theoretical link between the forecast error and opacity. Furthermore, because the theoretical underpinning relies on the CB guiding inflation expectations, the authors construct an uncertainty measure based on survey of forecasts where such expectations can be inferred through the variability in the forecast error.