A Graph is Worth a Thousand Words: How Overconfidence and Graphical Disclosure of Numerical Information Influence Financial Analysts Accuracy on Decision Making

• Published in: PloS one Vol. 11; no. 8; p. e0160443
• Main Authors: Cardoso, Ricardo Lopes, Leite, Rodrigo Oliveira, de Aquino, André Carlos Busanelli
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 10-08-2016; Public Library of Science (PLoS)
• Subjects: Accountability; Accountants; Accounting; Accuracy; Adult; Analysis; Biology and Life Sciences; Chi-square test; Computer and Information Sciences; Decision analysis; Decision Making; Disclosure; Female; Financial analysts; Financial disclosure; Financial Management; Financial reporting; Gender; Gender Identity; Graphic methods; Graphs; Humans; International finance; Logistic Models; Male; Middle Aged; People and Places; Physical Sciences; Practice; Reading; Research and Analysis Methods; Social Sciences; Students; Studies; Tables; Brazil; Rio de Janeiro Brazil
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0160443

Previous researches support that graphs are relevant decision aids to tasks related to the interpretation of numerical information. Moreover, literature shows that different types of graphical information can help or harm the accuracy on decision making of accountants and financial analysts. We conducted a 4×2 mixed-design experiment to examine the effects of numerical information disclosure on financial analysts' accuracy, and investigated the role of overconfidence in decision making. Results show that compared to text, column graph enhanced accuracy on decision making, followed by line graphs. No difference was found between table and textual disclosure. Overconfidence harmed accuracy, and both genders behaved overconfidently. Additionally, the type of disclosure (text, table, line graph and column graph) did not affect the overconfidence of individuals, providing evidence that overconfidence is a personal trait. This study makes three contributions. First, it provides evidence from a larger sample size (295) of financial analysts instead of a smaller sample size of students that graphs are relevant decision aids to tasks related to the interpretation of numerical information. Second, it uses the text as a baseline comparison to test how different ways of information disclosure (line and column graphs, and tables) can enhance understandability of information. Third, it brings an internal factor to this process: overconfidence, a personal trait that harms the decision-making process of individuals. At the end of this paper several research paths are highlighted to further study the effect of internal factors (personal traits) on financial analysts' accuracy on decision making regarding numerical information presented in a graphical form. In addition, we offer suggestions concerning some practical implications for professional accountants, auditors, financial analysts and standard setters.