Analysts’ Recommendations and Press Sentiment: Complementary or Alternative to Drive Investors’ Trading Behavior?

AbstractThis paper focuses on the relationship between financial analysts’ recommendations and press sentiment from the perspective of the attention-grabbing theory. Specifically, attention-grabbing should not be enough to explain the effect that media coverage has on investment decisions, since investors are wary of making a mistake and anticipate the regret of a future loss. Our case study pertains to a column reporting on secondhand information and analysts’ recommendations. Once the column did not report the analysts’ advice anymore, we hypothesized investors also assess the sentiment of the column to make sure they are not making a costly mistake. Event studies on abnormal returns and multivariate analyses show that for columns with explicit analysts’ recommendations the attention-grabbing mechanism directs buying decisions while has no influences on selling decision. In the absence of explicit recommendations, investors transform the columns’ content into implicit recommendations leading their buying decisions when the sentiment is highly positive.Keywords: Behavioral financeinvestment decisionsattention grabbinganticipated regretsentiment analysisSubject classification codes: G40G110 Disclosure statementThe authors report there are no competing interests to declare.Notes1 For insights into the influence of media on financial markets, refer to Tetlock (Citation2015). To explore the literature on market reactions to the dissemination of analysts' recommendations in print media, consult the review by Cervellati, Ferretti, and Pattitoni (Citation2014).2 Retail investors tend to concentrate their purchases on attention-grabbing stocks that subsequently underperform (Barber, Lin, and Odean Citation2023).3 The European Court of Justice has revisited the issue of market abuse, specifically focusing on the disclosure of inside information by a journalist. In the case brought before the Court of Justice (Case C-302/20), a journalist published two articles on the Daily Mail website, reporting rumors about the filing of public offers to purchase shares of Hermès (by LVMH) and Maurel&Prom. The journalist was fined by the Autorité des marchés financiers (the French Financial Market Supervisory Authority) for disclosing the imminent publication of these articles, which was deemed as transmitting 'inside information'.4 Columns covering companies listed on foreign exchanges or companies with a short listing history (less than 130 trading days before the publishing date), as well as columns with incomplete data or mentioning more than one company, were excluded from the sample. Additionally, columns that were distributed with a delay due to a strike or columns for which the file could not be found in the newspaper's electronic database were also excluded from the analysis.5 Until 2010, all columns include a section presenting a list of analysts' recommendations. To establish a consensus recommendation, each recommendation is assigned a score based on a five-point rating scale: buy = 2, overweight = 1, hold/neutral = 0, underweight = -1, sell = -2. The average score and the modal score are calculated. If the average score is ≥ 0.8, or if the average score is ≥ 0.5 and the modal score is ≥ 1, the column is attributed a Positive Rating. Following the approach of Cervellati, Ferretti, and Pattitoni (Citation2014), neutral and negative ratings (underweight or sell) are grouped together. From 2011 to 2014, when analysts' recommendations are reported, they are presented in a condensed format using a pie chart displaying the buy, hold, and sell percentages. To convert the chart into a score, a three-point rating scale is used: buy = 2, hold = 0, sell = -2. The weighted average score is then calculated. If the average score is ≥ 0.8, the column is attributed a Positive Rating.6 The NRC lexicon is a comprehensive resource that consists of a list of words along with their associations with eight specific emotions and two sentiments: negative and positive. The lexicon provides sentiment values for a wide range of 13,901 words and covers translations for over 40 different languages, including Italian (see https://saifmohammad.com/WebPages/NRC-Emotion-Lexicon.htm).