Fear, excitement, and financial risk-taking

Effect of real-world fear on risky decision-making in medical school-based students: A quasi-experimental study

Objective: To explore the effect of real-world fear on risky decision-making under certainty and uncertainty. Methods: This quasi-experimental study enrolled non-psychology undergraduate volunteers aged between 17 and 20 years old from the Preventive Medical Institute medical school in Xi'an. Participants were randomly divided into two groups, and each group received a two-stage crossover design intervention (of a calm and fearful situation) and completed the tasks of risky decision-making under uncertainty (the balloon analog risk task: BART) and certainty (the Cambridge gambling task: CGT), respectively. The primary outcomes included the behavioral impulsivity measured by the BART value, and the speed of decision-making, the quality of decisions, the adventure index, behavioral impulsivity, and risk adjustment measured by CGT. The secondary outcome was the concentration of cortisol in the saliva. Results: A total of 60 questionnaires and data were obtained from 60 participants (28 males and 32 females, aged 19.55 ± 0.75). Compared with the calm situation, participants were more likely to have a lower BART value (p = 0.013), slower speed of decision-making (p < 0.05), and higher adventure index (p = 0.018) in the fearful situation. The quality of decisions (p = 0.189), behavioral impulsivity index (p = 0.182), and risk adjustment (p = 0.063) between subjects in the fearful and calm situations were comparable. Furthermore, the mean value of the adventure index of CGT in male subjects was significantly higher than that in female subjects (p < 0.05), and the cortisol concentration in saliva during the fearful situation was significantly higher compared to the calm situation (p < 0.05). Conclusion: Fear might reduce behavioral impulsivity under uncertainty, and increase the adventure index under certainty in risky decision-making. Risky behavior might be influenced by gender: under certainty in risky decision-making, men were more adventurous. Additionally, fear increased the secretion of cortisol in saliva.

The effect of fear-inducing stimuli on risk taking in people with psychopathic traits

Research suggests that people with psychopathic traits experience fear-inducing stimuli differently from others, seeming to interpret fear as more positive and less negative. We expected that this reaction, termed fear enjoyment, would impact the effect of fear-inducing stimuli on self-report risk-taking behaviour. Risk-taking was measured before and after viewing excitement- and fear-inducing videos (N = 825). As expected from research showing that fear induction tends to reduce risk-taking tendencies, participants showed reduced risk-taking scores following a fear-inducing stimulus. Importantly, this relationship was moderated by psychopathic traits. Participants who did not decrease their risk-taking tendencies following the video scored significantly higher on psychopathic traits. Also, some of the variance in the relationship between psychopathic traits and change in risk-taking was partly accounted for by fear enjoyment, suggesting that future research should examine whether fear enjoyment may play a role in the relationship between psychopathy and risk-taking.

The influence of incidental emotions on decision-making under risk and uncertainty: a systematic review and meta-analysis of experimental evidence

Emotions influence human decisions under risk and uncertainty, even when they are unrelated to the decisions, i.e. incidental to them. Empirical findings are mixed regarding the directions and sizes of the effects of discrete emotions such as fear, anger, or happiness. According to the Appraisal-Tendency Framework (ATF), appraisals of certainty and control determine why same-valence emotions can differentially alter preferences for risky and uncertain options. Building upon this framework of emotion-specific appraisals, we conducted a systematic review and meta-analysis of 28 experimental studies on the effects of discrete incidental emotions on decision-making under risk and uncertainty. We evaluated potential moderators at the task and study levels. We find emotion-specific, moderately heterogeneous effects partially in line with the expectations of the ATF. The framing and financial consequences of choices, the type of choices, and the presence of other participants during the task do not moderate the effect. Our meta-analytic results support the differential influence of discrete, incidental emotions on decision-making under risk and uncertainty depending on appraisals other than valence. We discuss limited sample sizes and heterogeneity as reasons for the absence of significant moderators and encourage experimental investigations of individual differences in the susceptibility to incidental affective influences.

Research on Artificial Intelligence Classification and Statistical Methods of Financial Data in Smart Cities

In order to improve the effect of financial data classification and extract effective information from financial data, this paper improves the data mining algorithm, uses linear combination of principal components to represent missing variables, and performs dimensionality reduction processing on multidimensional data. In order to achieve the standardization of sample data, this paper standardizes the data and combines statistical methods to build an intelligent financial data processing model. In addition, starting from the actual situation, this paper proposes the artificial intelligence classification and statistical methods of financial data in smart cities and designs data simulation experiments to conduct experimental analysis on the methods proposed in this paper. From the experimental results, the artificial intelligence classification and statistical method of financial data in smart cities proposed in this paper can play an important role in the statistical analysis of financial data.

Impact of Induced Moods, Sensation Seeking, and Emotional Contagion on Economic Decisions Under Risk

In addition to probabilities of monetary gains and losses, personality traits, socio-economic factors, and specific contexts such as emotions and framing influence financial risk taking. Here, we investigated the effects of joyful, neutral, and sad mood states on participants' risk-taking behaviour in a simple task with safe and risky options. We also analysed the effect of framing on risk taking. In different trials, a safe option was framed in terms of either financial gains or losses. Moreover, we investigated the effects of emotional contagion and sensation-seeking personality traits on risk taking in this task. We did not observe a significant effect of induced moods on risk taking. Sad mood resulted in a slight non-significant trend of risk aversion compared to a neutral mood. Our results partially replicate previous findings regarding the presence of the framing effect. As a novel finding, we observed that participants with a low emotional contagion score demonstrated increased risk aversion during a sad mood and a similar trend at the edge of significance was present in high sensation seekers. Overall, our results highlight the importance of taking into account personality traits of experimental participants in financial risk-taking studies.

Immediate emotions and subjective stakes in risky decision-making under uncertainty

BACKGROUND

Previous research has shown that immediate emotions and cognitive processing of the stakes of outcomes influence decision-making under uncertainty. The effect of perceived beneficial stakes and different types of immediate emotions on decision-making is an important topic that has received little attention in the literature. This study investigated the effects of trait anxiety and anticipatory emotions (fear, sadness, excitement and comfortability) on the perception of thee stakes of outcomes and behavioral intentions.

METHOD

Participants from the community completed a task measuring anticipatory emotions and their perceived stakes of risky and beneficial outcomes in a range of uncertain situations. Trait anxiety was also measured.

RESULTS

Results revealed that anticipatory emotions (except for sadness), trait anxiety and subjective stakes all demonstrated significant associations with risky behavioral intention in uncertain situations. Anticipatory emotions, but not trait anxiety, had stable effects on stake perceptions. However, trait anxiety moderated the effect of excitement on risky behavioral intention. In addition, positive emotions (comfortability and excitement) and beneficial stakes demonstrated consistent effects in the decision-making process.

CONCLUSIONS

The current study sheds light on future immediate-emotion-based interventions for deficits in uncertain decision-making.

"I Feel Therefore I Decide": Effect of Negative Emotions on Temporal Discounting and Probability Discounting

Temporal and probability discounting are considered two fundamental constructs in economic science, as they are associated with phenomena with major societal impact and a variety of sub-optimal behaviors and clinical conditions. Although it is well known that positive and negative affective states bear important cognitive/behavioral consequences, the effect of emotional experiences on decision-making remains unclear due to the existence of many conflicting results. Inspired by the need to understand if and to what extent the current COVID-19 pandemic has determined changes in our decision-making processes by means of the unusual, prolonged experience of negative feelings, in this study we investigate the effect of anger, fear, sadness, physical and moral disgust on intertemporal and risky choices. Results show that all emotions significantly increase subjects' preferences for immediate rewards over delayed ones, and for risky rewards over certain ones, in comparison to a "neutral emotion" condition, although the magnitude of the effect differs across emotions. In particular, we observed a more pronounced effect in the case of sadness and moral disgust. These findings contribute to the literature on emotions and decision-making by offering an alternative explanation to the traditional motivational appraisal theories. Specifically, we propose that the increased preference for immediate gratification and risky outcomes serves as a mechanism of self-reward aimed at down-regulating negative feelings and restore the individual's "emotional balance".

Fear in groups: Increasing group size reduces perceptions of danger

When we face danger or stress, the presence of others can provide a powerful signal of safety and support. However, despite a large literature on group living benefits in animals, few studies have been conducted on how group size alters subjective emotional responses and threat perception in humans. We conducted 5 experiments (N = 3,652) to investigate whether the presence of others decreases fear in response to threat under a variety of conditions. In Studies 1, 2 and 3, we experimentally manipulated group size in hypothetical and real-world situations and found that fear responses decreased as group size increased. In Studies 4 and 5 we again used a combination of hypothetical and real-world decisions to test whether increased anxiety in response to a potential threat would lead participants to choose larger groups for themselves. Participants consistently chose larger groups when threat and anxiety were high. Overall, our findings show that group size provides a salient signal of protection and safety in humans. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Fear From Afar, Not So Risky After All: Distancing Moderates the Relationship Between Fear and Risk Taking

A growing line of research has shown that individuals can regulate emotional biases in risky judgment and decision-making processes through cognitive reappraisal. In the present study, we focus on a specific tactic of reappraisal known as distancing. Drawing on appraisal theories of emotion and the emotion regulation literature, we examine how distancing moderates the relationship between fear and risk taking and anger and risk taking. In three pre-registered studies (N_total = 1,483), participants completed various risky judgment and decision-making tasks. Replicating previous results, Study 1 revealed a negative relationship between fear and risk taking and a positive relationship between anger and risk taking at low levels of distancing. Study 2 replicated the interaction between fear and distancing but found no interaction between anger and distancing. Interestingly, at high levels of distancing, we observed a reversal of the relationship between fear and risk taking in both Study 1 and 2. Study 3 manipulated emotion and distancing by asking participants to reflect on current fear-related and anger-related stressors from an immersed or distanced perspective. Study 3 found no main effect of emotion nor any evidence of a moderating role of distancing. However, exploratory analysis revealed a main effect of distancing on optimistic risk estimation, which was mediated by a reduction in self-reported fear. Overall, the findings suggest that distancing can help regulate the influence of incidental fear on risk taking and risk estimation. We discuss implications and suggestions for future research.

Digital inclusive finance risk prevention based on machine learning and neural network algorithms

To improve the effectiveness of digital inclusive finance risk prevention, this paper constructs a digital inclusive finance risk prevention system based on machine learning and neural network algorithms and performs special data pre-processing for convolutional neural networks. Moreover, based on the index data arrangement with the shortest double Euclidean distance, this paper uses the principle of combining qualitative analysis and quantitative analysis to process the data set. Aiming at the characteristics of different links in the whole process of digital inclusive finance, this paper has formed a preliminary digital inclusive finance risk factor assessment of influencing factors. Besides, this paper combines the needs of digital inclusive finance risk methods to construct a digital inclusive finance risk prevention model, and design functional modules based on process analysis. Finally, this paper designs experiments to verify the performance of the digital inclusive finance risk prevention model constructed in this paper. The experimental research results show that the model constructed in this paper has a certain effect.

Mathematical statistics of regional financial spatial spillover effect based on spatial dubin model

How to correctly use the spatial measurement model to analyze the differences, causes, and influencing factors of regional finance, and to establish corresponding development strategies to keep the regional financial differences in an ideal state is one of the problems that the current regional financial development needs to face. Based on the spatial Dubin model (SEM), spatial Dubin error model (SDEM), generalized spatial Dubin model (GSAM), etc. in the spatial measurement method, this paper compares the actual effects of different models, and combines the machine learning algorithm to improve the model algorithm, and intelligently analyzes the spillover effects of regional financial space. After constructing the model, this paper takes area A as an example to analyze the spillover effect of regional financial space through the model constructed in this paper. In addition, this paper conducts an empirical analysis on the influencing factors of regional financial development and proposes corresponding strategies to provide support for the construction of regional financial centers.

Comprehensive analysis of risk factors in Internet agricultural finance based on neural network model

Agricultural industrialization is a major reform and practice in the process of agricultural development and requires theoretical guidance. However, the current theoretical research on financial support for the development of agricultural industrialization is insufficient, which to a certain extent seriously affects the development speed of agricultural industrialization. This paper studies the nature of the part and tail probability of dependent random variable sequences with different distributions, and focuses on the random variable sequences with wide dependent structures, and obtains the relevant probability estimation formulas. At the same time, this paper also considers the application of the main results in complete convergence. Moreover, based on the research on the nature of dependent random variable sequences, the dependent risk model is discussed, which combines Internet finance with the development of agricultural industrialization. In addition, this article uses agricultural industrialization theory and Internet finance theory to study the support of Internet finance for the development of agricultural industrialization in my country. The research results show that the model constructed in this paper has a certain effect.

Simulation of financial risk spillover effect based on ARMA-GARCH and fuzzy calculation model

Convergence and spillover are the characteristics shown in the process of financial development. By verifying whether there is convergence and spillover in financial development within a certain region and between regions, the stage of financial development in the region can be more accurately judged. This paper combines the actual needs of financial analysis to construct a financial risk spillover effect model based on ARMA-GARCH and fuzzy calculation. The model uses ARMA-GARCH and fuzzy algorithm to verify the financial multiple risk factors. Moreover, in order to verify the effect of the model, this paper uses case data analysis to study the model effect and combines mathematical statistics to process the model data. The research results show that the model constructed in this paper has a certain effect, and the ARMA-GARCH model is suitable for analysis and research on financial risk spillover effects. At the same time, when the statistical distribution is used to fit its error distribution, the fitting and prediction effect of the model is better.

Effects of experienced regret on risky decision making are dependent on risky degree

We investigated whether experienced regret influences risky decision making in future dissimilar situations and whether this effect is affected by risky degree. Therefore, participants (N = 39 and 54 in Experiment 1 and 2, respectively) were asked to select one of the two options. In the experienced regret condition, the selected option was worse than the unselected option; in the control condition, the information about the unselected option was unknown to the participants. Subsequently, participants were required to either keep the selected option or to gamble. Additionally, Experiment 2 varied in risky degree of the gamble from low to high. Results showed that experienced regret enhanced possibilities of gamble under low risk (Experiment 1 and 2). Under high risk, however, the effect of experienced regret was reversed (Experiment 2). The findings might suggest that experienced regret affects risky decision making in future dissimilar situations dependently on risky degree.

Hard to Bear

Abstract. Establishing a causal relationship between state boredom and risk taking is contributory to understand the nature of boredom and its influences. This research examines how and why state boredom influences financial risk taking. Across multiple inductions of state boredom, we found that state boredom increased participants’ preference for engaging in financial risk-taking behavior (Studies 1, 2, and 3) and actual financial risk-taking behavior (Studies 2 and 4). An internal meta-analysis verified the robustness of this effect. We also assessed four potential mediators and found motivation to seek stimulation as the best explicable mediator (Studies 3 and 4). Overall, the current research signified the role of state boredom in predicting financial risk taking as a function of motivation to seek stimulation.

Stress-related changes in financial risk taking: Considering joint effects of cortisol and affect

Many decisions under risk and uncertainty are made under physical or emotional stress. A recent meta-analysis suggested that stress reliably influences risk taking but did not find a relation between single measures of stress such as cortisol and risk taking. One reason for the conflicting findings could be that the influence of stress on risk taking depends not only on physiological but also on psychological stress responses, in particular affective valence. We tested this hypothesis in an exploratory empirical study: Seventy participants worked on a financial risk-taking task. In half of the participants acute stress was induced with a cold pressor task. For all participants we measured cortisol and α-amylase levels, blood pressure, subjective arousal, and affective valence before and after the task. The stress induction increased participants' levels of cortisol, subjective arousal, and systolic blood pressure but did not directly influence negative affect or risky decision making. Examining the interplay between physiological and psychological stress responses, a moderation analysis revealed an interaction between stress induction and affect valence: Negative affect predicted an increase in risk-seeking decision making in the stress condition, but not in the control group. A similar moderation was found with cortisol reactivity, that is, negative affect predicted an increase in risk-seeking decision making in participants with high cortisol reactivity but not in participants with low cortisol reactivity. These results suggest that the effect of stress on risky decision making depends on the interplay of affective valence and cortisol reactivity.