Emotional Reactions of Students to Perceptions of Negative Trends and Small Losses in Short-Term Stock Market Simulation
Why this work is in the frame
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Bibliographic record
Abstract
Decision-making on stock markets is a complex experience characterized by strong emotions (Nofsinger, 2017). Price fluctuations are stimuli that can cause a wide range of psychological reactions in investors (Shiv et al., 2005). In particular, the perception of loss is a central area in behavioral finance: loss aversion (Kahneman & Tversky, 1979) suggests that the psychological impact of a loss is stronger than a gain of the same size. Traditionally, attention has focused on significant financial losses or bear markets, where intense emotions such as fear and panic are commonly found (Shiller, 2014). However, our study suggests addressing a less examined side of the emotional experience: the psychological and behavioral reactions of individuals to the perception of negative trends and small losses. Our goal is to understand if and how perceived unfavorable small stock market movements could induce significant emotional responses, particularly among novice investors. For this purpose, we used a qualitative exploratory study with eight students participating in a short-term (three-day) stock market simulation. During this period, the stock market index on which the students based their investments declined by 0.36%. This fluctuation does not constitute a bear market in the financial sense generally recognized. Nevertheless, our findings show that participants actively perceived a ‘general negative trend’ and exhibited significant emotional reactions, even facing small financial losses. Based on semi-structured interviews, our article aims at: 1) identifying the range of emotions felt by participants during the simulation; 2) describing the development of these emotions in response to perceived market variations; and 3) conducting a thematic analysis of their influence on participants' decisions, with a particular focus on emotional regret related to small losses and reactions to uncertainty and perceived losses. Our results demonstrate a significant change in emotions over time. From an initial interest and a relative emotional detachment, students show a growing emotional commitment to market fluctuations. Moreover, as the experiment progresses and disappointments increase, the emotional picture is largely defined by negative emotions, notably fear in relation to potential losses, as well as sadness and disappointment related to unfavorable results. Market surprises, particularly sudden falls, lead to intense reactions, which can result in panic and impulsive decisions. Given the inability to improve the financial situation, the experience can also result in abandonment and resignation. By examining these dynamics, we aim at contributing to understanding emotional impact in behavioral finance, beyond major crisis scenarios.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it