“Loss aversion” is a behavioral phenomenon in the area of behavioral decision-making where people exhibit a higher sensitivity to potential losses than to gains. On the other hand, those who are “risk averse” are more sensitive to or less interested in choices that may have unpredictable results. Here, we investigate whether negative symptoms, such as hypomania, can predict how severe these choice biases will be. We focused on these two symptom dimensions because they share a common thread with numerous syndromes characterized by impaired decision-making. We used a non-clinical sample in our exploratory study to separate the hypomanic from the negative symptom dimension with regard to choice behavior. From a student population (18–37 years old) with no self-reported psychiatric diagnoses (n = 835) we randomly selected a sample of 45 individuals. Using the hypomanic personality scale (HPS-30) and community assessment of psychic experiences (CAPE), we divided them into three groups based on percentiles: low hypomania/low negative symptoms (n = 15), hypomania (n = 15), and negative symptoms (n = 15). With no gain or loss, participants had to make forced binary decisions between a financial gamble and a risk-free option as part of a loss aversion task. In participants who experienced more negative symptoms, we discovered that their loss aversion was lower. In addition, participants with higher levels of negative symptoms and hypomania showed less risk aversion than those with lower levels of negative symptoms and hypomania. This study advances knowledge of the psychological processes that underlie risk aversion and loss. Further research is required to determine whether hypomania and negative symptoms affect loss and risk aversion through dissociable mechanisms given the partially opposing nature of both.
A number of psychiatric disorders, including schizophrenia, depression, and bipolar disorder, exhibit negative symptoms, such as apathy and diminished expression, and (hypo-) mania (1). Daily functioning can be significantly hampered by symptoms from both dimensions (2, 3). Additionally, they have been associated with altered decision-making patterns (4–7), which may contribute to the development and/or maintenance of the observed symptoms.
Behavioral economics provide powerful methods to investigate variance in decision-making. These techniques have recently been successfully used in the study of psychopathology (8–10). Negative symptoms and (hypo-)mania have typically been linked to a decrease in the frequency and vigor of goal-directed behavior, respectively. Core decision-making processes directing adaptive goal-directed behavior include valuing losses and gains and the uncertainty that goes along with them. Therefore, these processes may be especially important for symptoms that are negative and (hypo-) manic. Clinical observations show a decrease in goal-directed behavior and invested effort or motivation in negative symptoms (13, 14) and an increase in goal-directed behavior and concomitant investment of effort as well as the pursuit of goals without regard to risks in mania (11, 12), both of which lead to an impairment of effort-cost computations.
Loss aversion, which describes a greater sensitivity to losses than to gains and is observable in the general population, is a well-replicated phenomenon in behavioral economics. In other words, when something is given up rather than gained, its value is considered to be higher (15, 16). When one’s survival is in jeopardy, marginal losses prove more important for reproductive success than marginal gains (18), and in a resource-limited environment, humans are cognitively biased to prevent them from falling below some minimal threshold of resources necessary for survival (19). The social and economic effectiveness of an individual may suffer from a significant miscalculation of their loss aversion, which may also be accompanied by psychopathology.
It has been noted that schizophrenia patients exhibit altered risk-taking when making decisions based on prospective outcomes, as well as a decreased or absent sensitivity to loss (20–22). Additionally, a study discovered a negative correlation between loss aversion and the total severity of symptoms (21) This stands in contrast to the notion that a rise in loss aversion could reduce goal-directed behavior, which would then manifest as negative symptoms. However, no research has yet looked at potential connections to particular symptom dimensions, like negative symptoms. Furthermore, to our knowledge, no research has examined loss aversion in (hypo-) manic states, which is surprising given that impulsivity and a disregard for the risks and losses that might result from one’s actions are diagnostic features of manic episodes (1). Using a computerized decision-making task, one study in euthymic bipolar patients found that in positively framed dilemmas, i e. The shift between risk-averse and risk-seeking choices was significantly reduced in bipolar patients when opportunities for rewards were presented. Bipolar participants made riskier decisions for greater gains in positively framed dilemmas than they did for greater losses in negatively framed dilemmas (23) In a probability-based gambling paradigm that involves risk-taking scenarios aimed at maximizing gain and minimizing loss, another study found no performance deficit in manic bipolar patients (24) It is still unclear how exactly (hypo-)manic or negative symptom dimensions relate to how much a person fears loss and taking risks.
It’s significant that characteristics of negative symptoms and (hypo-)mania can be found not only in patients who are extremely ill, but also range across a continuum in the general population (25, 26). These dimensional approaches to psychopathology are predicated on the idea that both clinical and non-clinical symptom expression should be connected to similar underlying mechanisms, at least in part. Because they are easier to study, the extreme members of the “normal” population make for an effective way to analyze both non-clinical and clinical disease mechanisms (27, 28).
Using a binary choice task with monetary incentives, the current study examined whether elevated negative and hypomanic symptoms in a stratified non-clinical sample were associated with variations in decision-making, specifically loss and risk aversion. We had predicted that groups with a high level of negative symptoms and/or hypomania would show less loss and a different level of risk aversion. As stated above, negative symptoms are one of the main psychopathologic components of schizophrenia, which has been linked to decreased or absent sensitivity to loss and altered behavioral approaches to risk. The clinical definition of (hypo-)mania includes impulsivity and a disregard for risks and potential losses, which is a behavior consistent with a diminished aversion to losses.
The Canton of Zurich’s regional ethics committee examined and approved the studies involving human subjects. In order to take part in this study, the participants’/patients’ written informed consent was provided. No animal studies are presented in this manuscript. In this study, no potentially identifiable human subjects or data are presented.
There are 835 students at the University of Zurich, 607 of whom are men and are 24 years old. 3, SD = 5. 49) were recruited through university mailing lists and social media. Eligible participants completed online trait questionnaires after passing an initial screening via an online questionnaire that asked if the participants were receiving treatment for a mental illness and whether they had a psychiatric diagnosis (eligibility criteria: respond “no” to these questions). These surveys used the Hypomanic Personality Scale (HPS-30: M = 11) to measure hypomania. 1, SD = 4. Utilizing the negative symptom items from the Community Assessment of Psychic Experiences (CAPE, M = 1), 88) (29) and negative symptoms 62, SD = 0. 49) (30). They participated in a lottery for $300 Swiss Franc Amazon gift cards as compensation. e. ~300 USD).
Being receiving therapy or medication for a mental illness was a requirement for exclusion, while the age range for inclusion was 18 to 55. Based on this sizable reference population, we identified three target subpopulations: high negative symptoms/low hypomania (the “negative symptom group”), high hypomania/low negative symptoms (the “hypomania symptom group”), and low negative symptoms/low hypomania (the “low hypomania/low negative symptoms group”). Scores below the 40th percentile and above the 60th percentile of the reference population, respectively, were considered to be “low” or “high,” respectively, scores. These cutoffs enabled the three groups to be clearly distinguished while still leaving a large enough pool in each group for conducting random samplings of participants in the experimental tasks.
Using a random number generator [MATLAB rand function, 2012 (31)] in a second step, participants who met the target criteria were contacted at random and invited to the lab. The three equal groups were created by uniformly selecting 15 participants from each stratum. The recruitment process was stopped when there were 15 enrolled participants per group, yielding a total of n = 45 participants. Please be aware that we did not perform a power analysis due to the exploratory nature of the study and the limited literature (32).
30 CHF were given to each participant at the start of the study. The next task was a loss aversion task (33), which involved 20 forced binary decisions between a financial gamble (P = 0) and not. 5) as well as a risk-free option with no gain or loss (P = 1). Three numbers representing amounts of money were shown to participants on a computer screen; two of the numbers represented the potential gain or loss in the event that the gamble was accepted, and one number represented 0 CHF in the event that the gamble was rejected (Supplementary Figure S2). According to accepted behavioral economics procedures, participants were informed beforehand that their final payment would be equal to their 30 CHF endowment plus or minus one of their 20 randomly chosen outcomes. Each bet’s result was immediately disclosed to the subject. When the experiment was over, they were paid in accordance with the previously mentioned policy, given a debriefing, and then fired. We quantified a subject-specific loss parameter called below using their decisions. Choices were also used to measure attitudes toward uncertainty (risk aversion) and consistency in decision-making (logit sensitivity).
To calculate choice behavior, we used a three-parameter model. Gains were calculated using equation 1 (u(x+)x), and losses were calculated using equation 2 (u(x)=*(x)). Equation 3 combines these, where p(gamble acceptance)=(1+exp-(u(gamble)-u(guaranteed)))1), where u(gamble) is the difference between equations 1 and 2. u denotes anticipated utility or “desirability,” x denotes the (monetary) value, denotes the utility function’s curvature and risk aversion, denotes the loss aversion coefficient and refers to the multiplicative valuation of losses relative to gains (with >1: loss aversion, 1: gain seeking, =0: gain-loss neutral), p denotes the probability of an event, and From subject-specific expected marginal posteriors, the subject-specific parameter, our main outcome representing loss aversion, was calculated. Parameters μ and ρ were estimated in the same way. For details see (33–35). With,, and as dependent measures and group as the independent measure, a one-way multivariate analysis of variance was carried out using IBM SPSS 25 to identify the between-subject differences. Due to the exploratory nature of this study, age was included as a covariate. Post-hoc testing was done using Cohen’s d, partial eta square (2), and least significant difference to estimate effect sizes.
Gender differences between the three groups weren’t very different (F(2,42) = 368, p = . 694), income (F(2,42) = . 883, p = . 421), education (F(2,42) = 1. 451, p = . 246), or money spent per month (F(2,42) = 1. 037, p = . 363). However, there was a significant age difference between the groups (F(2,42) = 4). 055, p = . 025). The hypomania group (age: M = 21. 80, SD = 2. Age: M = 24) was significantly younger than the adverse symptom (age: M = 25, age range: 18-27 years). 93, SD = 5. group of 26, aged 20 to 37, with a mean difference of 4 13 years (p = . Compared to the low hypomania/negative symptom group (age: M = 23), the negative symptom and hypomania groups did not differ in age. 80, SD = 3. 84, age range: 20–31 years) (p = . 149 and p =. 176 respectively).
Loss Aversion vs Risk Aversion
What is loss aversion?
People naturally focus more intensely on potential losses than on potential gains, a phenomenon known as loss aversion. This phrase is used by behavioral economists to describe how humans have a psychological tendency to avoid circumstances where there is a risk of loss, even when there is also a chance of gain. Loss averse investors believe that the possibility of loss is more severe than the possibility of gain, which may affect their investment behavior. A risk-averse investor may be more likely to adopt an investment strategy than a risk-neutral investor to avoid losses.
What is risk aversion?
Risk aversion is a term used to describe an investment strategy that favors capital preservation by steering clear of risky bets even when they have a high return potential. The volatility or stability of an asset determines the risk of an investment. Assets that exhibit greater volatility are viewed as being riskier than those that exhibit a more stable pricing pattern. A volatile asset can either generate a high rate of return for the investor or cause them to suffer a sizable financial loss, whereas a less volatile asset may only generate a meager return on their initial investment.
Risk aversion vs loss aversion
Although risk aversion and loss aversion have a strong relationship and are similar concepts, knowing the differences between them can help you use them in practice. The main distinctions between these expressions are as follows, along with suggestions for appropriate usage:
Loss aversion and risk aversion may have similar but dissimilar root causes. Investors who experience loss aversion are typically more likely to adopt risk-averse investing strategies. Some investors may experience risk aversion due to loss aversion, but others may experience risk aversion due to other factors. For instance, if an older investor has a strong financial foundation, such as a nest egg, they are likely to experience risk aversion. These investors may believe there is little benefit from investing in risky assets because they have already attained their financial objectives.
In contrast, loss aversion is a cognitive bias that may not be driven by rational considerations. People naturally react emotionally more strongly to losses than to victories, but some people may be predisposed to having more intense emotional responses than others. In addition, people may develop a greater or lesser fear of losing things over the course of their lives depending on certain life experiences. For instance, someone who has previously suffered a significant financial loss might develop a greater aversion to loss. Loss aversion is almost always irrational and rooted in emotional predispositions, whereas some investors experience risk aversion based on justifiable financial goals.
Although low-risk, conservative investment strategies are favored by both risk-averse and loss-averse investors, not all loss-averse investors follow the same behavioral patterns as risk-averse investors. For instance, an investor with high levels of loss aversion may be more likely to adopt a risk-averse investing strategy, but some investors may defy their cognitive predisposition and opt for riskier ventures. Contrarily, risk aversion describes a particular pattern of investing that leads to more cautious investment choices.
Because the term “risk aversion” more accurately describes an investment strategy, the results for risk-averse investors are more predictable than the results for loss-averse investors. The term “loss averse” does not specify any specific investment style, whereas the term “risk averse” designates a conservative investment approach that yields low-stakes, low-reward earnings. However, some investors may choose to ignore their aversion and make risk-neutral or risk-positive investments. Loss-averse investors may be more likely to adopt a conservative investment strategy.
Despite some similarities, there are differences in the meanings and applications of these terms. The phrase “risk aversion” in particular is more precise and designates a particular investor or investment style. In behavioral economics, the psychological tendency that makes people perceive losses as disproportionately negative in comparison to gains is known as loss aversion. Loss aversion may explain why some investors favor a less risky investing approach, but it does not describe an investment approach or a particular type of investor.
Tips for managing loss and risk aversion
As you manage your own loss and risk aversion or assist clients in overcoming aversions to make more strategic investment decisions, consider the following advice:
Use a strategic asset allocation style
This investment plan takes the investor’s time horizon, investment goals, and risk tolerance into consideration. Regular portfolio evaluations and rebalancing are required based on evolving factors surrounding the initial investment. The regular evaluation and updating of the investment portfolio required by this investment strategy may help risk-averse investors increase their risk tolerance. Loss-averse investors may feel more comfortable making riskier investment decisions when they are aware that they can alter their investment portfolios as needed.
Follow a formula investing strategy
A fixed ratio of risky and conservative investments is the foundation of a formula investing strategy. This approach strikes a balance between risky and conservative investments, which may be advantageous for investors seeking to take low-risk bets while protecting capital. An investor who is afraid of losing money might use this investment approach to gradually increase their risk tolerance while maintaining other, more conservative investments.
Identify irrational thinking patterns
It’s beneficial to consider the underlying causes of these behaviors in addition to creating investment strategies that help risk- and loss-averse people develop risk tolerance. Understanding whether a risk-averse investment pattern is driven by loss aversion or a specific objective can help you decide whether a particular investment is appropriate for you or your client. Recognizing the irrationality of one’s fears can help loss-averse investors get over their aversion and make better investment choices.
What is an example of loss aversion?
If someone would rather take the risk and possibly receive nothing than accept a certain payment (certainty equivalent) of less than $50 (for instance, $40), they are said to be risk averse (or risk avoiding).
What is loss aversion meaning?
Examples of Loss Aversion You might sell a stock that has slightly increased in price just to make a profit of any size, despite the fact that your analysis suggests that you should hold onto the stock for much longer to make a much larger profit. telling oneself that until a loss is realized, an investment is not a loss (i e. , when the investment is sold).
What is the difference between risk aversion and risk management?
A cognitive bias known as loss aversion explains why, for people, the pain of losing is psychologically twice as strong as the pleasure of winning. Losing money or any other valuable item can be more painful than gaining the same thing. 1.