Individual risk tolerance and herding behaviors in financial forecasts

Abstract

Financial analysts tend to demonstrate herding behavior, which sometimes compromises accuracy. A number of explanations spanning rational economic logic, cognitive biases, and social forces have been suggested. Relying on an experimental setting where participants forecast future earnings from a rich information set, we posit and obtain support for individual risk tolerance (or lack thereof) as an explanatory variable for herding behaviors. Specifically, less risk‐tolerant individuals forecast with less boldness and instead issue forecasts in agreement with the consensus forecast. The results are argued to be at least partially a product of cognitive biases and an intuitive reaction to uncertainty.

The impact of heuristic availability bias on investmentdecision‐making: Moderated mediation model

“…The study evidence shows that risk tolerance mediates the relationship between heuristic availability bias and investment decision‐making. These results are reported as in line with the previous studies of Ameriks et al (2020), Nguyen et al (2019), Christoffersen and Staehr (2019) Hemrajani and Sharma (2017), Heo, Grable, Nobre, and Menjivar (2016), Mahat et al (2010).…”

“…Similarly, Christoffersen and Staehr (2019) reported that risk tolerance is positively and significantly related to herd behavior. Kannadhasan, Aramvalarthan, Mitra, and Goyal (2016) examined three factors such as self-esteem, A/B personality, and sensation seeking, and reported it significantly associated with risk tolerance.…”

Do expert experience and characteristics affect inflation forecasts?

“…In line with Clarke and Subramanian (2006), performance and boldness results in Table 5 are often similar in terms of signi…cance and sign, 23 con…rming that signi…cant underperformers are more likely to issue bolder forecasts and vice-versa. Like …nancial analysts who also tend to exhibit herding behavior, which sometimes compromises accuracy, our results suggest that social forces (ranking, institution type, and location), education (type and level), and experience (type and duration) in ‡uence an expert's rational economic logic and cognitive biases-an interpretation close to Christo¤ersen and Staehr (2019) that is presented in our next results (Section 5.3).…”

The Impact of Herding Tendency in Modular Networks on the Diffusion of Internet Investment Products

“…The first regular investor claimed a regular investment plan on 30 December 2018, suggesting 193 days duration of the diffusion of adoption. According to [31], risk averse investors are prone to follow the crowd. A money market fund is a low risk investment product, so we assume that the average risk aversion level of its investors is relatively low, and thus we set the herding coefficient as τ = 0.9.…”