Earnings forecasts of female CEOs: quality and consequences

This study examines the voluntary disclosure of earnings forecasts by female CEOs. We find that in the backdrop of increased pressure to perform from investors and other stakeholders, female CEOs tend to issue more earnings forecasts than male CEOs, and those forecasts are more accurate. We also find that while financial analysts generally prefer to follow companies headed by male CEOs, female CEOs’ efforts to issue accurate earnings forecasts pay off, as these efforts help them close the analyst coverage gap. We provide complementary evidence on the disclosure efforts of female CEOs with regard to updates to the forecast and the 10-K report. Lastly, we show that financial analysts rely more on the earnings forecasts of female CEOs, possibly because they recognize female CEOs’ superior forecasting quality. Our results are robust to the use of alternative research designs, including difference-in-difference, propensity score matching, and entropy balancing. Overall, our study documents gender differences in voluntary disclosure by senior management.

Summarization and Sentiment Analysis for Financial News

Data is growing at an unimaginable speed around us, but what part of it is really useful information? Business leaders, financial analysts, stock market enthusiasts, researchers etc. often need to go through a plethora of news articles and data every day, and this time spent may not even result in any fruitful insights. Considering such a huge volume of data, there is difficulty in gaining precise, relevant information and interpreting the overall sentiment portrayed by the article. The proposed method helps in conceptualizing a tool that takes financial news from selected and trusted online sources as an input and gives a summary of the same along with a basic positive, negative or neutral sentiment. Here it is assumed that the tool user is familiar with the company’s profile. Based on the input (company name/symbol) given by the user, the corresponding news articles will be fetched using web scraping. All these articles will then be summarized to gain succinct and to the point information. An overall sentiment about the company will be portrayed based on the different important features in the article about the company. Keywords: Financial News; Summarization; Sentiment Analysis.

Impact of market-wide versus firm-specific information on financial analysts

PurposeThis paper documents the effect of different types of information on the value of financial analysts.Design/methodology/approachThe authors use the pooled OLS regression and the data of nonfinancial firms from France to test our hypotheses. The data covers the period between 1997 and 2019.FindingsThe results show that analysts are more likely to cover those firms that incorporated greater proportion of market-wide information in their prices. Consistent with the economies of scale view, the authors argue that analysts specialize in the interpretation market-wide information. By doing so, they are able to cover relatively large number of firms simultaneously. The results also show that the value of analyst coverage (measured as the impact of analyst coverage on firm value, probability of stock price crash and probability of stock price jump) is a function of the extent to which different types of information are incorporated in prices. The authors’ results suggest that the impact of analyst coverage on firm value and on probability of crash is less pronounced in firms that incorporate greater proportion of market-wide information. In case of probability of jump, the results show that the impact of analyst coverage is more pronounced firms that incorporate greater proportion of market-wide information.Originality/valueThe major contribution of this paper is to document the impact of different types of information on the extent of analyst coverage. Furthermore, this paper also uses various measures (the impact of analyst coverage on firm value, probability of stock price crash and probability of stock price jump) to show how different types of information affects the value of analyst coverage.

How valuation approach choice affects financial analysts’ target price accuracy

This paper examines which valuation approaches financial analysts use to value a company and whether the chosen valuation approach affects the target price accuracy. To address these questions, we conduct content analyses of 867 hand-collected analyst reports on German publicly listed companies published between January 2014 and June 2017. We find that sell-side analysts more frequently use the single-period market approach when formulating target prices, followed by the multi-period income approach, and a mixture of both by combining the results, the so-called hybrid valuation approach. Additionally, we show that 612 of the analyzed analyst reports are based on a holistic valuation methodology instead of a sum of the parts valuation technique. Both univariate and multivariate analyses emphasize that the choice of valuation approach is significantly associated with the accuracy of price targets. Specifically, the income and market approach lead to significantly more accurate target prices compared to the hybrid approach. We also find that the target price accuracy is higher when analysts apply the holistic rather than the sum of the parts valuation approach to determine the fundamental value of the company. Additional results emphasize that target price accuracy improves when analysts use the sum of the parts valuation that bases solely on market or income approaches rather than hybrid approaches. Hence, we contribute to theory and practice by providing evidence on the link between the choice of valuation approach and the analysts’ target price accuracy as well as on the performance of certain valuation techniques.