Análise da relação entre aspectos comportamentais e temporal com a acurácia da previsão do analista
| Autor | Paula Carolina Ciampaglia Nardi, Evandro Marcos Saidel Ribeiro, José Lino Oliveira Bueno, Ishani Aggarwal |
| Cargo | PhD in Organizational Administration (FEARP/USP) Professor at the Faculty of Economics, Administration and Accounting (USP), Ribeirão Preto/SP, Brazil paulanardi@fearp.usp.br / PhD in Physics (UFSCAR) Professor at the Faculty of Economics, Administration and Accounting (USP), Ribeirão Preto/SP, Brazil esaidel@usp.br / PhD in Psychology (USP) ... |
| Páginas | 53-69 |
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Artigo
Original
Original
Paper
Revista Contemporânea de Contabilidade, Florianópolis, v. 20, n. 54, p. 01-17, 2023.
Universidade Federal de Santa Catarina. ISSN 2175-8069. DOI: https: //doi.org/10.5007/2175-8069.2023.e83406
Analysis of the relationship between temporal and behavioral
aspects of the analyst's forecasting accuracy
Análise da relação entre aspectos comportamentais e temporal com a acurácia da previsão do
analista
Análisis de la relación entre los aspectos conductuales y temporales de la preci sión del pronóstico
del analista
Paula Carolina Ciampaglia Nardi*
PhD in Organizational Administration (FEARP/USP)
Professor at the Faculty of Economics, Administration and
Accounting (USP), Ribeirão Preto/SP, Brazil
paulanardi@fearp.usp.br
https://orcid.org/0000-0001-7897-3070
José Lino Oliveira Bueno
PhD in Psychology (USP)
Professor at the Faculty of Philosophy, Sciences and
Letters of Ribeirão Preto (USP), Ribeirão Preto/SP, Brazil
jldobuen@usp.br
https://orcid.org/0000-0002-4193-5094
Evandro Marcos Saidel Ribeiro
PhD in Physics (UFSCAR)
Professor at the Faculty of Economics, Administration and
Accounting (USP), Ribeirão Preto/SP, Brazil
esaidel@usp.br
https://orcid.org/0000-0001-7213-0240
Ishani Aggarwal
PhD in Organizational Behavior and Theory (Carnegie
Mellon University)
Professor at the EBAPE (FGV), Rio de Janeiro/RJ, Brazil
ishani.aggarwal@fgv.br
https://orcid.org/0000-0002-7885-7114
Primary contact address for correspondence *
Av. Bandeirantes, 3900, Monte Alegre, CEP: 14040-905 - Ribeirão Preto/SP, Brazil
Abstract
The study analyzed the relationship between optimism, anchoring, overconfidence, representativeness,
realism, commonality and time, with the accuracy in the profit forecast of analysts. Publicly traded Brazilian
companies were considered in 2019, and correlation tests, mean differences and multiple regression
analyses were applied. The results indicated that accuracy is negatively influenced by optimism and
positively by anchoring and commonality. In addition, the uncertainty present in the distance between the
forecast issued and the disclosure of earnings per share also negatively influences the accuracy of analysts.
Additionally, it was found that fair value, profitability, issuing ADRs and self-regulated sector, are aspects
related to greater accuracy. Thus, the research contributes to the literature by linking behavi oral and
temporal aspects to financial ones, as well as by signaling the importance of analysts' forecasting models to
consider behavioral aspects in their information technologies.
Keywords: Analyst's forecast; Behavioral biases; Forecast time
Resumo
O estudo analisou a relação entre otimismo, ancoragem, excesso de confiança, representatividade,
realismo, comunalidade e tempo, com a acurácia na previsão de lucro de analistas. Foram consideradas
empresas brasileiras de capital aberto em 2019, aplicando teste de correlação, diferença de média e
regressão múltipla. Os resultados indicaram que a acurácia é influenciada negativamente pelo otimismo e
positivamente pela ancoragem e comunalidade. Ademais, a incerteza presente na distância entre a previsão
emitida e a divulgação do lucro por ação também implica negativamente na acurácia dos analistas.
Adicionalmente, constatou-se que o valor justo, lucratividade, emissão de ADRs e setor auto
regulamentado, são aspectos relacionados com maior acurácia. Desse modo, a pesquisa contribui com a
literatura para reflexão quanto à necessidade de concatenar aspectos comportamentais e temporais aos
financeiros, bem como para sinalizar a importância de que os modelos de previsão dos analistas
considerem os aspectos comportamentais em suas tecnologias de inform ação.
Palavras-chave: Previsão do analista; Vieses Comportamentais; Tempo de previsão
Analysis of the relationship between temporal and behavioral aspects of the a nalyst's forecasting accuracy
2
Revista Contemporânea de Contabilidade, Florianópolis, v. 20, n. 54, p. 01-17, 2023.
Universidade Federal de Santa Catarina. ISSN 2175-8069. DOI: https: //doi.org/10.5007/2175-8069.2023.e83406
Resumen
El estudio analizó la relación entre optimismo, anclaje, exceso de confianza, representatividad, realismo,
concordancia y tiempo, con la precisión de las previsiones de los analistas. Se consideraron las empresas
brasileñas que cotizan en bolsa en 2019, aplicando la prueba de correlación, diferencia de medias y
regresión múltiple. Los resultados indicaron que la precisión est á influenciada negativamente por el
optimismo y positivamente por el anclaje y la similitud. La distancia entre el pronóstico emitido y la
divulgación de ganancias por acción también afecta negativamente la precisión de los analistas. Se
encontró que el valor razonable, la rentabilidad, la emisión de ADR y el sector autorregulado son aspectos
relacionados con una mayor precisión. La investigación contribuye a una reflexión sobre la necesidad de
concatenar aspectos conductuales y temporales a los financieros , y señalar la importancia de los modelos
de pronóstico de los analistas considerando aspectos conductuales en sus tecnologías de la información.
Palabras clave: Pronóstico del analista; Sesgos de comportamiento; Tiempo de previsión
1 Introdution
The capital market has a unique importance for the economic development of a country. It is
responsible for channeling society's savings towards more efficient allocation of resources, in order to
guarantee a better return on investments. In addition, it is able to favor corporate governance by
encouraging transparency in the disclosure of inform ation by companies, leading to greater economic
growth, more jobs, innovation, reduced cost of capital, increased availability of resources, greater liquidity for
companies and investors (ANBIMA, 2018). This represents improvements in resource allocation efficiency
(Wang, Hou & Chen, 20182).
However, the functioning of this market takes place through relations between agent and principal,
which, as recommended by the Agency Theory of Jensen and Meckling (1976), are subject to a series of
conflicts of interest potentiated by the condition of asymmetry of information between those involved.
In this context, financial analysts play an important role in brokering and monitoring information for
investors (Brauer & Wiersema, 2018), able to assist investment decisions and reduce this informational
asymmetry between companies and investors (Bildstein-Hagberg, 2003; Dalmácio, Lopes, Rezende & Sarlo
Neto, 2013), via profit forecast and disclosure of their reports. In addition, financial analysts, when providing
investment advice, influence the demand for a company's shares and, therefore, its price (Brauer &
Wiersema, 2018), further evidencing its importance in the capital market.
However, analysts do not have access to the same information at the same time, and yet, there are
different individual interpretations for the same information, which produces different results to the point of
recommending or not investing in a particular company. This means that the analysts' analysis is individual,
although based on a network of relationships, their risk assessment is particular and stems from their
perception. And, this diversity is the result of the analyst's cognitive capacity (Boff, Procianoy & Hoppen,
2006).
Therefore, the view that analysts know com panies, analyze and disclose information about future
scenarios, being considered intermediaries of information, places it in a perspective that is not subject to
cognitive biases or social context. But analysts operate in a social context that influences behavior making
them subject to behavioral biases (Brauer & Wiersema, 2018).
Given this context, and considering the seminal work of Simon (1955), which discusses concepts of
bounded rationality and simplifying approaches to rationality, some research has sought to observe the
relationship between behavioral biases and analysts' accuracy, such as: a) optimism (Gervais & Odean,
2001; Kafayat, 2014; Galanti & Vaubourg, 2017); b) overconfidence (Gervais, Heaton & Odean, 2002; Hilary
& Menzly, 2006; Du & Budescu, 2018); c) anchoring (Brown, 2001; Campbell & Sharpe, 2009; Silva Filho,
Miranda, Lucena & Machado, 2018); d) representativeness (Marsden, Veeraraghavan & Ye, 2008); e) time
(Amiran, Landsman, Ownes & Stubben, 2017; Muslu, Mutlu, Radhakrishnan & Tsang, 2019), etc.
Despite this research, Brauer and Wiersema (2018) state that research with analysts is still far from
maturity and, in fact, holds strong promise for future growth, as we do not have a coherent understanding of
the extent and nature of the various influences of analysts in executive and investor decision making and the
context in which analysts operate.
Therefore, what is perceived in these researches is the observation of the analysts' accuracy by an
average of forecasts of a group of analysts. In addition, behavioral factors tend to be observed by
quantitative techniques. However, there is the possibility of ascertaining this relationship considering these
main variables individually, that is, by analyst, and not by a concentrated data set. In addition, it is
understood from the previous literature that there is an advance in discussions in international works, and a
slower pace for national ones. Thus, the reflection on the relationship between accuracy and cognitive
biases in a different context from those in which most research is carried out can reveal different results,
which must be analyzed in order to better contribute to the academy.
It was also possible to identify that there is room for the development of research that considers in
their forecast models a concatenation of financial aspects with behavioral and temporal aspects, highlighting
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