Volume 26 Issue 3 Article 3 September 2024 Effects of Neuroticism–Anxiety and Sociability Personality Traits Effects of Neuroticism–Anxiety and Sociability Personality Traits on the Relationship Between Testosterone and Risk Propensity in on the Relationship Between Testosterone and Risk Propensity in Finance Finance Urš a Ferjanč ič University of Ljubljana, School of Economics and Business, PhD Student, Ljubljana, Slovenia, ursa.ferjancic@ef.uni-lj.si Fajko Bajrović University Medical Centre Ljubljana, Department of Vascular Neurology and Intensive Neurological Therapy, Ljubljana, Slovenia and University of Ljubljana, Faculty of Medicine, Institute of Pathophysiology, Ljubljana, Slovenia Aljoš a Valentinč ič University of Ljubljana, School of Economics and Business, Ljubljana, Slovenia Follow this and additional works at: https://www.ebrjournal.net/home Part of the Behavioral Economics Commons, and the Finance Commons Recommended Citation Recommended Citation Ferjanč ič , U., Bajrović , F., & Valentinč ič , A. (2024). Effects of Neuroticism–Anxiety and Sociability Personality Traits on the Relationship Between Testosterone and Risk Propensity in Finance. Economic and Business Review, 26(3), 184-195. https://doi.org/10.15458/2335-4216.1341 This Original Article is brought to you for free and open access by Economic and Business Review. It has been accepted for inclusion in Economic and Business Review by an authorized editor of Economic and Business Review. ORIGINAL ARTICLE Effects of Neuroticism–Anxiety and Sociability Personality Traits on the Relationship Between Testosterone and Risk Propensity in Finance Urša Ferjanˇ ciˇ c a, * , Fajko Bajrovi´ c b,c , Aljoša V alentinˇ ciˇ c d a University of Ljubljana, School of Economics and Business, PhD Student, Ljubljana, Slovenia b University Medical Centre Ljubljana, Department of Vascular Neurology and Intensive Neurological Therapy, Ljubljana, Slovenia c University of Ljubljana, Faculty of Medicine, Institute of Pathophysiology, Ljubljana, Slovenia d University of Ljubljana, School of Economics and Business, Ljubljana, Slovenia Abstract Risky nancial decisions, dened as rational calculations between expected risk and reward, are subject to vari- ous psychological and neurobiological mechanisms. In this context, the relationship between testosterone levels and risk propensity has been investigated, but the results are inconsistent. Here, the effects of some personality traits, neuroticism–anxiety and sociability, on the relationship between testosterone levels and risk propensity were examined in decisions under risk (GDT) and under uncertainty (BART). In a mixed-sex sample of 100 graduate students and experienced decision makers, we found that basal testosterone levels were positively correlated with risk propensity for decisions under risk in males with low neuroticism–anxiety scores, whereas they were negatively correlated with risk propensity for decisions under risk in males with high neuroticism–anxiety scores. However, they were not correlated in (i) decisions under uncertainty in males, independent of neuroticism–anxiety, (ii) decisions under risk or under uncer- tainty in males, independent of sociability, and (iii) decisions under risk or under uncertainty in females, independent of sociability and neuroticism–anxiety. These results indicate that neuroticism–anxiety, but not sociability, may affect the relationship between testosterone levels and risk propensity only in decisions under risk and only in males, and provide evidence for the complexity of this relationship in males. Keywords: Risk propensity, Testosterone, Sociability, Neuroticism–anxiety, Personality traits JEL classication: G41 Introduction F inancial decision making is a complex process in which the expected rewards are weighed against the associated risks (Berk & DeMarzo, 2020). Recent neuroeconomic studies suggest that nancial deci- sion making is inuenced by various psychological constructs (Welker et al., 2019), social context (Zili- oli & Watson, 2014), and biological factors such as hormones (Nofsinger et al., 2018), and not only by a rational cost–benet analysis, as suggested by tradi- tional economic decision-making theories (Tobler & Weber, 2014). One hormone that has received attention in the context of nancial decision making is the steroid hormone testosterone (Apicella et al., 2008; Herbert, 2018), which plays an important role in reproductive physiology and development, modulating a num- ber of behavioral processes relevant to survival and reproduction, particularly in males (Apicella et al., 2015). Testosterone affects brain regions related to reward processing by increasing reward sensitiv- ity (Welker et al., 2015), decreasing impulse control (Mehta & Beer, 2010), altering risk perception, and increasing dominance behavior (Mehta & Josephs, 2010). These effects may encourage individuals to Received 9 July 2024; accepted 19 July 2024. Available online 16 September 2024 * Corresponding author. E-mail address: ursa.ferjancic@ef.uni-lj.si (U. Ferjanˇ ciˇ c). https://doi.org/10.15458/2335-4216.1341 2335-4216/© 2024 School of Economics and Business University of Ljubljana. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/ licenses/by-nc-nd/4.0/). ECONOMIC AND BUSINESS REVIEW 2024;26:184–195 185 take more risks, as the potential rewards become more attractive, and the perceived risks are minimized. Studies generally suggest that higher basal levels of endogenous testosterone or administered exogenous testosterone are associated with riskier nancial deci- sions in the laboratory and in real life (Apicella et al., 2008; Coates & Herbert, 2008; Cueva et al., 2015; Nof- singer et al., 2018; Stanton, Liening, & Schultheiss, 2011; Van Honk et al., 2004). However, the results of studies are not consistent for both sexes and for all risk measures (Apicella et al., 2015). Furthermore, in one study, individuals with both lower and higher testosterone levels were more likely to make risky de- cisions (Stanton, Mullete-Gillman, et al., 2011). Taken together, these observations suggest a more complex relationship between testosterone and nancial risk taking that is dependent on other neurobiological and psychological systems. Risk-taking behavior has been shown to be related to personality traits such as sensation seeking, aggres- sion, power motivation, sociability, and social con- texts such as interpersonal competition (Welker et al., 2019; Zilioli & Watson, 2014; Zuckerman & Kuhlman, 2000). In nance, CEOs who are higher in extraversion and lower in conscientiousness are less likely to re- duce their rm’s strategic risk taking when the value of their stock options increases (Benischke et al., 2019). Individuals high in risk taking are often characterized by high extraversion and low neuroticism, agreeable- ness, and conscientiousness traits (Nicholson et al., 2005). Extraversion and neuroticism reect the under- lying neuropsychological mechanisms of approach and avoidance systems, which are related to reward processing (Corr, 2004; Krupi´ c & Corr, 2017; Welker et al., 2015) and are bidirectionally linked to testos- terone levels (El Ahdab et al., 2023; Enter et al., 2014). It is therefore possible that the relationship between testosterone and risk taking is affected by extraver- sion and neuroticism. However, we are not aware of any study that addresses the possible effects of par- ticular personality traits on the relationship between testosterone and decision making. Risk and uncertainty are related but distinct con- cepts (De Groot & Thurik, 2018). In situations involv- ing risk, the outcome is unknown, but the probability distribution for that outcome is known. Conversely, in situations involving uncertainty, both the outcome and the probability distribution are unknown. In both cases, preferences are determined by the probability distributions of the outcomes (Platt & Huettel, 2008). In the case of risk, these probabilities are considered objective, whereas in the case of uncertainty they are subjective. The conceptual distinction between un- certainty and risk is supported by psychology and neurobiology, which indicate that they are encoded differently in the brain (Blankenstein et al., 2017; Huettel et al., 2006; Schultz et al., 2008). For example, the response of cortisol, another hormone that has received attention in the context of nancial decision making, has been shown to affect decision making under risk, but not under uncertainty (Buckert et al., 2014). We are not aware of any study that addresses the possible differences in the relationship between testosterone and decision making under risk and de- cision making under uncertainty. The aim of this study was to examine the effects of personality traits, specically neuroticism–anxiety and sociability, on the relationship between basal testosterone levels and risk propensity in decisions under risk and decisions under uncertainty. We hy- pothesized that basal testosterone levels would be positively related to higher risk propensity in de- cisions under risk and decisions under uncertainty (1) only in individuals low in the neuroticism–anxiety personality trait (H1) and (2) only in individuals high in the sociability personality trait (H2). 1 Materials and methods 1.1 Participants Participants were recruited through the university and its alumni base, consisting of graduate students and experienced decision makers. Exclusion criteria were alcohol or drug abuse, eating, drinking, smok- ing, chewing, ossing their teeth, taking medicine, or engaging in physical activity within 30 minutes be- fore providing saliva samples. Participants were also required to provide signed informed consent prior to participating in the study. The research design and all related procedures were approved by the Committee for Ethics and Research at the School of Economics and Business of the University of Ljubljana and by the National Medical Ethics Committee of the Republic of Slovenia. 1.2 Study protocol Testing was conducted in several sessions between April and September 2022 at the same times from around 7:30 to 9:30 in the morning. The data col- lection was partially related to another study. The experiment was conducted in two parts, with a 20- minute break in between. After a 10-minute resting period, during which participants were asked to calm down and relax, saliva samples were taken to as- sess their basal testosterone levels. Participants then completed either the Balloon Analogue Risk Task (BART) (Lejuez et al., 2002) or the Game of Dice Task (GDT) (Brand et al., 2004) and, after the break, 186 ECONOMIC AND BUSINESS REVIEW 2024;26:184–195 the other task. The order of the tasks was randomly assigned to each testing group to ensure that task or- der had no effect on performance. After completing both tasks, participants completed a general ques- tionnaire about their sex, age, decision-making expe- rience, education, physical activity, medical history, and the Zuckerman-Kuhlman Personality Question- naire (ZKPQ) (Zuckerman, 2002) for the assessment of neuroticism–anxiety and sociability personality traits. To motivate real-life behavior in both tasks, one randomly selected participant from each test group received a voucher for a sports shop equal to their total earnings in BART. Participants were informed in advance about the possibility of receiving a nancial reward in the amount of their total earnings in BART. 1.3 Instruments and measures 1.3.1 Sociodemographic data A semi-structured sociodemographic questionnaire was used to obtain information on sex, age, decision- making experience (status: student or employed, short description of their work and job title), edu- cation, daily habits, including alcohol consumption (number of drinks per week), smoking (number of cigarettes smoked per day), sport activity (how often they practiced aerobic or anaerobic sports, when they had been physically active the last time and what kind of activity they had done), coffee consumption (coffee consumption on the testing day), and sleeping sched- ule on the day of testing (hours of sleep, wake up and bedtime). The information collected in this question- naire was used to obtain general sociodemographic data and to assess compliance with the inclusion cri- teria of the study. 1.3.2 Decisions under uncertainty Decision making under uncertainty was assessed using BART, in which participants inate 30 balloons in a row and earn virtual ve cents for each successful ination (Lejuez et al., 2002). Each balloon can ex- plode at any time during the process, representing the risk of losing the accumulated gains. Participants are not informed about the probability of an explosion, which is determined by a random selection of num- bers from an array of 1 to 128. The selection of the number 1 indicates an explosion. Based on this algo- rithm, the average “explosion point” for each balloon is 64 pumps. To model excessive risk leading to de- creased gains and increased threats, each additional pump increases the potential loss and decreases the relative gain of additional pumps. The average num- ber of pumps on the balloons that did not explode (BART score) is used as the dependent variable for de- cisions under uncertainty, conceptualized as the risk propensity in decisions under uncertainty. A higher adjusted average number of pumps indicates a higher risk propensity in decisions under uncertainty. 1.3.3 Decisions under risk Decision making under risk was assessed using GDT (Brand et al., 2004), in which participants are asked to increase their imaginary starting capital (€1000) within 18 throws of a single virtual dice. Be- fore each throw, subjects have to guess which number or combination of numbers (2, 3, or 4 numbers) will be thrown. Each choice is associated with certain gains and losses depending on the probability of the choice’s occurrence (a single number with a winning probability of 1:6D €1000 gain/loss; a combination of two numbers with a winning probability of 2:6D €500 gain/loss; a combination of three numbers with a winning probability of 3:6D €200 gain/loss; a com- bination of four numbers with a winning probability of 4:6D €100 gain/loss). The gains and losses are ex- plicitly described in the test instructions. This allows participants to calculate the expected returns and the associated risks. The outcome of the throws is pseu- dorandomized to ensure that each of the six possible numbers occurs three times during the task perfor- mance, but in a balanced order. The maximum out- come is €19,000 (if the subject chooses a single number and is successful in each throw). The maximum decit is €17,000 (if the subject chooses a single number and is unsuccessful in each throw). To analyze the decisions, choices of one or two numbers (probability of winning is less than 50% and high gains but also high penalties) are classied as disadvantageous or risky choices. Conversely, the choices of three or four numbers (probability of winning is 50% or higher, low gains, but also low penalties) are classied as advan- tageous or safe choices. In GDT, the net score (GDT score) is commonly used as a measure of performance and as a dependent variable for risk propensity in the decisions under risk. It is calculated by subtracting the number of risky choices from the number of safe choices. The net score is a quantitative indicator of risk propensity, with a more negative score indicating a higher risk propensity in decisions under risk. 1.3.4 Personality traits Personality traits were assessed using the ZKPQ, which is based on the assumption that personal- ity traits have a strong biological–evolutionary basis and distinguishes between ve personality traits: ac- tivity, aggression–hostility, impulsive sensation seek- ing, neuroticism–anxiety (N–Anx), and sociability (Sy) (Zuckerman, 2002). N–Anx and Sy correlate with neuroticism and extraversion from the Big Five (DeYoung & Blain, 2020) and are used to measure ECONOMIC AND BUSINESS REVIEW 2024;26:184–195 187 individual differences in reward processing based on the underlying neuropsychological mechanisms of behavioral avoidance and approach systems, re- spectively (DeYoung et al., 2021). N–Anx describes being emotionally agitated, anxious, tense or worried, compulsively indecisive, lacking self-condence, and sensitive to criticism. Sy includes the number of friends one has, and the time one spends with them, outgoingness at parties, and preference for being with others rather than being alone or pursuing soli- tary activities, thus measuring extraversion (Aluja et al., 2002). Each participant can score between 0 and 10 on each personality trait scale. Higher scores on the N–Anx and Sy scales indicate higher levels of neuroticism–anxiety and sociability, respectively. 1.3.5 Testosterone assay Basal testosterone levels were determined in saliva samples collected after a 10-minute rest period prior to BART or GDT testing. Samples were analyzed ac- cording to standard procedures (Tecan, 2019). The certied laboratory used enzyme-linked immunosor- bent assay (ELISA) kits to test for free testosterone. The intraassay coefcient of variation averaged 5.6%, and the interassay coefcient of variation averaged 8.7%. 1.4 Data analysis Testosterone levels were standardized separately for men and women using z-scores (Mehta & Josephs, 2010). High testosterone levels in an individual indicate a high value relative to other individuals of the same sex. Personality correlates of the avoidance and approach systems, N–Anx and Sy, as well as the GDT and BART scores were transformed using a natural logarithm to better approximate the normal distributions. However, all log-transformed variables are given without the prex ln, except in the tables. The rst hypothesis (H1: testosterone is positively related to risk propensity in decisions under risk and decisions under uncertainty only in individuals low in the neuroticism–anxiety personality trait) was ana- lyzed using a moderated multiple regression model (Hayes, 2022). The dependent variables GDT and BART scores were used for the risk propensity in deci- sions under risk and under uncertainty, respectively. To avoid potential problems with high multicollinear- ity affecting the interaction term, we mean-centered the independent variable and the moderator and created an interaction term between standardized testosterone levels within sexes and N–Anx scores (Hayes, 2022). To interpret a signicant interaction, we used a simple slope analysis with the PROCESS macro for R software (Hayes, 2022). We used the mul- tiple regression model to plot risk propensity one standard deviation above (considered high testos- terone) and below (considered low testosterone) the means for testosterone levels (standardized within sexes) and N–Anx scores. We calculated simple slopes to examine the relationship between testosterone lev- els and risk propensity, one standard deviation above (considered high N–Anx score) and below (consid- ered low N–Anx score) the mean of N–Anx scores. To test the second hypothesis (H2: testosterone is positively related to risk propensity in decisions un- der risk and in decisions under uncertainty only in in- dividuals high in the sociability personality trait), we applied a similar approach. We mean-centered both predictors (standardized testosterone levels within sexes and Sy) to avoid potential problems with high multicollinearity associated with the interaction term. To interpret the signicant interaction, we followed the approach described in the previous paragraph. The data analysis procedure (testing H1 and H2) was repeated separately for female and male participants. In these additional analyses, the testosterone levels were log-transformed with a natural logarithm to bet- ter approximate a normal distribution. The level of signicance for all analyses was set at p < :05. 2 Results The data were collected from 104 participants. Four participants were excluded from the analysis because testosterone data was missing due to technical issues. No participants were excluded from the analysis for violating the study protocol or not meeting the inclu- sion criteria. The nal sample included 100 healthy participants (mean ageD 28.94C/ 7.77, range 21–49; 58 females), who were tested under two conditions: decisions made under risk and under uncertainty. Participants were further divided into two groups, students (nD 59, mean ageD 23.59C/ 1.98, range 21–33; 38 females) and decision makers (nD 41, mean ageD 36.63C/ 6.38, range 23 49; 20 females), based on their decision-making experience. Basic demographics, basal testosterone levels, and risk propensity scores for decisions under risk and under uncertainty by sex are shown in Table 1. Inde- pendent samples t-tests were conducted to compare risk propensities in decisions under risk and under uncertainty, personality traits, and basal testosterone levels between females and males. No signicant dif- ferences were found in Sy scores and in BART and GDT scores between females and males, although males appeared to have higher BART and GDT scores compared to females. Compared to females, males had higher basal testosterone levels (p < :001) and lower N–Anx scores (pD :017). 188 ECONOMIC AND BUSINESS REVIEW 2024;26:184–195 Table 1. Sample sizes (N), means (M) and standard deviations (SD) of age, basal testosterone levels, neuroticism–anxiety and sociability personality traits, and risk propensity scores for decisions made under risk (GDT score) and under uncertainty (BART score) by sex. Male Female Variable N M SD N M SD t (98) p d Age (years) 42 29.69 7.89 58 28.34 7.67 0.86 .394 0.17 ln(N–Anx score) 42 1.09 0.81 58 1.41 0.70 2.15 .017 0.44 ln(Sy score) 42 1.50 0.71 58 1.45 0.63 0.35 .728 0.07 Testosterone (pmol/L) 42 275.82 110.51 58 90.30 58.84 9.91 .000 2.20 ln(BART score) 42 3.62 0.44 58 3.47 0.53 1.42 .122 0.29 ln(GDT score) 42 3.11 0.93 58 2.86 1.00 1.27 .104 0.26 Note. N-AnxD neuroticism-anxiety; SyD sociability; BARTD Balloon Analogue Risk Task; GDTD Game of Dice Task. 0 0.5 1 1.5 2 2.5 3 3.5 LowT HighT GDTscore LowNAnx HighNAnx Fig. 1. Risk propensity in decisions under risk (GDT score) as a function of basal testosterone, standardized within sexes (T) and neuroticism–anxiety (N–Anx score) for the entire sample of subjects. Note. Plotted points represent conditional low and high values (C/ 1 SDs) of T levels, standardized within sexes, and N–Anx scores. GDT scores and N–Anx scores are log-transformed using a natural logarithm. 2.1 Hypothesis 1 The rst hypothesis states that basal testosterone levels are positively related to higher risk propensity in decisions under risk and under uncertainty only in subjects low in the neuroticism–anxiety person- ality trait. In the entire sample of subjects for deci- sions under risk, a signicant interaction effect was found between testosterone levels and N–Anx scores (bD 0:35; pD :017). The simple slope analysis re- vealed a signicant association between testosterone levels and GDT scores only in subjects with low N–Anx scores (bD 0:33; pD :032, see Fig. 1, solid line) and that testosterone levels and GDT scores were not associated in subjects with high N–Anx scores (bD 0:20; pD :156, see Fig. 1, dashed line). Further analysis of the male and female subsamples revealed a signicant effect of the N–Anx score on the association between testosterone levels and GDT scores only in males. Testosterone levels were nega- tively related to GDT scores in males with low N–Anx scores (bD 0:99; pD :019) and positively related in males with high N–Anx scores (bD 0:97; pD :050), as is shown in Fig. 2. No signicant main effects or effects of decision-making experience were observed. No signicant effects were observed in the female subsample. For decisions under uncertainty, we found no sig- nicant main effects of testosterone levels and N–Anx scores on BART score. Effects of the control variables (sex and decision-making experience) and the interac- tion between the two predictors were not signicant. Furthermore, when analyzing female and male sub- samples, no signicant main effects or effects of the control variable (decision-making experience) were observed. ECONOMIC AND BUSINESS REVIEW 2024;26:184–195 189 0 0.5 1 1.5 2 2.5 3 3.5 4 LowT HighT GDTscore LowNAnx HighNAnx Fig. 2. Risk propensity in decisions under risk (GDT scores) as a function of basal testosterone levels, standardized within sexes (T) and neuroticism– anxiety (N–Anx scores) for males. Note. Plotted points represent conditional low and high values (C/ 1 SDs) of T levels, standardized within sexes, and N–Anx scores. GDT scores and N–Anx scores are log-transformed using a natural logarithm. 2.2 Hypothesis 2 The second hypothesis states that basal testosterone levels are positively related to higher risk propen- sity in decisions under risk and decisions under uncertainty only in individuals high in the sociability personality trait. In the rst model, the dependent variable was the GDT score. There were no signicant main effects of testosterone levels or Sy scores on GDT scores. No signicant interaction was found for deci- sions under risk. No signicant effects were observed when analyzing female and male subsamples. In the second model, the dependent variable was the BART score. Neither testosterone levels nor Sy scores had a signicant effect on risk propensity when the other predictor was conditioned on its mean. No signicant interaction was found for decisions under uncertainty. Control variables for sex and decision- making experience were included in both the risk and uncertainty models, and the effects were not sig- nicant. No signicant effects were observed when analyzing the female and male subsamples. 3 Discussion In this study, we evaluated the possible effects of certain personality traits, neuroticism–anxiety and sociability, on the relationship between testosterone levels and risk propensity under two conditions, deci- sions under risk and decisions under uncertainty. We found that basal testosterone levels were positively correlated with risk propensity for decisions under risk in males with low neuroticism–anxiety scores, whereas they were negatively correlated with risk propensity for decisions under risk in males with high neuroticism–anxiety scores. We found no effect of so- ciability on the relationship between testosterone and risk propensity in decisions under risk for males. In decisions under uncertainty, we observed no effect of neuroticism–anxiety or sociability on the relationship between testosterone and risk propensity for males. We found no signicant effects for females in either condition (decisions under risk or under uncertainty), regardless of the neuroticism or sociability personal- ity trait considered. A few studies examining the relationship between basal testosterone levels and risk propensity in deci- sions under risk have provided inconsistent results. One study of 21 healthy men using GDT to evaluate risk propensity found no correlation between the two (Goudriaan et al., 2010). In contrast, another study of 39 students pursuing master degrees in nance, using more real-life measures such as computerized simula- tions of nancial trading, found a positive correlation (Nofsinger et al., 2018). However, a third study of 208 subjects using the Holt and Laury Lottery Task (Holt & Laury, 2005) found a signicant relationship between basal testosterone levels and risk propen- sity in decisions under risk only in the gain domain (Schipper, 2023), suggesting the importance of the framing effect. The divergence in the results of these studies could be due to differences in the popula- tions studied, lack of statistical power due to small sample numbers in some studies, the differences in methodological approach (e.g., measures used to as- sess risk propensity and study protocols). The nding 190 ECONOMIC AND BUSINESS REVIEW 2024;26:184–195 of our study in 100 healthy graduate students and experienced decisions makers, using GDT, that the relationship between basal testosterone levels and risk propensity in decisions under risk was signi- cant only when the effect of neuroticism–anxiety was taken into account, supports the view of the complex- ity of this relationship in males. Testosterone has been associated with avoidant personality traits such as neuroticism (Peper et al., 2018). Since basal testosterone levels were negatively correlated with N–Anx scores in our study (see Appendix, Table A1), it would be possible that basal testosterone levels were positively correlated with risk propensity for decisions under risk in males with low neuroticism–anxiety scores only because of higher basal testosterone levels. This possibility, how- ever, is not supported by the negative correlation of basal testosterone levels with risk propensity for decisions under risk in males with high neuroticism– anxiety scores. Therefore, the mechanism of the effects of neuroticism–anxiety on the relationship between basal testosterone levels and risk propensity for deci- sions under risk must be more complex. Interestingly, neuroticism has not been related to risk propensity for decisions under risk (Buelow & Cayton, 2020) or other general risk-taking behaviors such as drinking, smoking, gambling, drugs, and sex (Zuckerman & Kuhlman, 2000), but only to risk propensity in de- cisions under risk for the gain domain (Lauriola & Levin, 2001). These discrepancies could be due to dif- ferences in methods used to measure the neuroticism trait as some studies employed the Big Five per- sonality questionnaire (e.g., Buelow & Cayton, 2020) and others employed the Zuckerman–Kuhlman per- sonality questionnaire (e.g., Zuckerman & Kuhlman, 2000). Taken together, these observations support the hypothesis that the relationship between basal testosterone and risk propensity is complex and depends on other neurobiological systems such as the hypothalamic–adrenal axis (Mehta et al., 2015) and mesolimbic dopaminergic system (Welker et al., 2015), social context such as interpersonal competi- tion (Zilioli & Watson, 2014), psychological constructs such as self-construal (Welker et al., 2019), optimism about future price changes (Cueva et al., 2015), and personality traits, especially the neuroticism–anxiety trait, as is evident in our study. In contrast to the effects of neuroticism–anxiety on the relationship between basal testosterone levels and risk propensity for decisions under risk in males, in our study we found no such effect for decisions under uncertainty in males regardless of the neuroticism– anxiety score. We are not aware of any other studies that have examined the effects of neuroticism–anxiety on the relationship between basal testosterone levels and risk propensity in decisions under uncertainty. Studies of the relationship between neuroticism and risk propensity in decisions under uncertainty have provided inconsistent results. Peper et al. (2018) found a signicant relationship between neuroticism and risk propensity, while Buelow and Cayton (2020) found no signicant relationship. Both studies used BART to measure risk propensity in decisions under uncertainty. Therefore, the divergence in the results between these two studies could be due to differ- ences in the populations studied, as the rst study included participants from 8 to 29 years of age, and the second included students who ranged from 17 to 19 years of age. In contrast to the second study, the rst one was a longitudinal study. A few studies ex- amining the relationship between basal testosterone levels and risk propensity in decisions under uncer- tainty also provided inconsistent results. In a recent study, the relationship between basal testosterone lev- els and risk propensity in decisions under uncertainty, as measured by BART, was not signicant (Stanton et al., 2021). In addition, some other studies found a positive correlation between basal testosterone levels and risk propensity in decisions under uncertainty, as measured by BART (e.g., Goudriaan et al., 2010) and the Iowa Gambling Task (IGT) (e.g., Stanton, Liening, & Schultheiss, 2011; Van Honk et al., 2004). The diver- gence in the results of these studies could possibly be due to different tasks employed to evaluate risk propensity in decisions under uncertainty. Moreover, in IGT (Bechara et al., 1994), participants learn the probabilities of outcomes as they progress through the task, which makes it difcult to categorize IGT as a pure measure of risk propensity in decisions under uncertainty (De Groot & Thurik, 2018). In addition, differences in the studied populations, lack of statisti- cal power due to small sample sizes in some studies, or the statistical approach may have also contributed to discordant results. The differences in the effect of neuroticism–anxiety on the possible relationship between basal testos- terone levels and risk propensity between decisions under risk and decisions under uncertainty could be explained by the neurobiological differences in risk and uncertainty (De Groot & Thurik, 2018). One hypothesis suggests that uncertainty could activate distinct brain systems compared to risk. Risk has been shown to activate the orbitofrontal cortex, the stria- tum, the insula, and the (posterior) parietal cortex, while uncertainty engages the amygdala and parts of the frontal cortex such as the inferior frontal gyrus and the (dorsal) lateral prefrontal cortex (Bach et al., 2009; Huettel et al., 2006; Krain et al., 2006; Platt & Huettel, 2008; Schultz et al., 2008). Another hy- pothesis suggests that risk and uncertainty activate a ECONOMIC AND BUSINESS REVIEW 2024;26:184–195 191 common brain mechanism, albeit to different degrees, with stronger responses to decisions under risk or uncertainty. Activity in the orbitofrontal cortex and amygdala has been shown to be positively correlated with task uncertainty, while activity in the striatal sys- tem is negatively correlated (Hsu et al., 2005; Levy et al., 2010; Platt & Huettel, 2008; Schultz et al., 2008). In our study we found no signicant effects of the sociability personality trait on the relationship be- tween basal testosterone levels and risk propensity, either in decisions under risk or in decisions under uncertainty. We are not aware of any other studies that have examined the effects of sociability on the re- lationship between basal testosterone levels and risk propensity in decisions under risk and under uncer- tainty. However, some studies that have examined the relationship between sociability/extraversion and risk propensity in both conditions provide incon- sistent results. Some found a positive relationship between extraversion and risk propensity in nan- cial decision making under uncertainty (Nicholson et al., 2005), while others found no signicant rela- tionship between extraversion and risk propensity in decisions under risk (measured with GDT) and un- certainty (measured with BART) (Buelow & Cayton, 2020). However, sociability has been found to be re- lated to other risk-taking behaviors such as drinking and gambling (Zuckerman & Kuhlman, 2000). The divergence in the results of these studies could pos- sibly be explained by the use of self-reported versus behavioral measures of risk propensity in decisions under uncertainty or decisions under risk in some studies. Self-reported measures are known to suf- fer from a number of limitations such as response biases (Wetzel et al., 2016), which could be the rea- son for inconsistent results. Furthermore, scores on the self-reported measures of risk propensity for de- cisions under uncertainty used by Nicholson et al. (2005) do not correlate with scores on BART, an es- tablished behavioral measure of risk propensity in decisions under uncertainty (Cruz-Sanabria et al., 2024). Moreover, testosterone levels have been posi- tively associated with the approach system (El Ahdab et al., 2023) and extraversion (Smeets-Janssen et al., 2015), but negatively associated with neuroticism in males (Peper et al., 2018). Accordingly, we found a negative relationship between neuroticism–anxiety and basal testosterone levels. However, we did not nd a signicant association between basal testos- terone levels and sociability (see Appendix, Table A1). Therefore, it is possible that the lack of a signicant effect of sociability on the relationship between basal testosterone levels and risk propensity in decisions under risk and under uncertainty in our study was due to the lack of signicant associations between so- ciability and basal testosterone levels. Overall, these ndings do not support the hypothesis that the so- ciability trait may play a signicant role in affecting the relationship between basal testosterone levels and risk propensity in both, decisions under risk and un- der uncertainty. In an additional analysis of a subsample of only female participants, we found no signicant effects of the neuroticism–anxiety trait on the relationship between basal testosterone levels and risk propensity for decisions under risk. We are not aware of any study comparing the effects of neuroticism–anxiety on the relationship between basal testosterone levels and risk propensity for decisions under risk between the sexes. The few studies that have examined the re- lationship between basal testosterone levels and risk propensities in decisions under risk in both sexes have provided inconsistent results. One study found that basal testosterone levels are positively associated with risk propensity in decisions under risk only in females (Sapienza et al., 2009), while another study found a signicant positive association between the two for males and for gains only (Schipper, 2023). Yet, another study found a nonlinear relationship be- tween basal testosterone levels and risk propensity in decisions under risk for both sexes (Stanton, Mullete- Gillman, et al., 2011). The divergence in the results of these studies could be possibly explained by ndings from animal studies, which have shown that females are less responsive to androgens (e.g., testosterone) than males in terms of neuroendocrine function and sexual behavior (Yellon et al., 1989). Additionally, fe- males produce signicantly less testosterone in their bodies compared to males and exhibit less variability in testosterone levels (Wood & Newman, 1999), which was also observed in our sample (see Table 1). Fur- thermore, smaller variability of testosterone levels in females may reduce the statistical power to detect the psychological and behavioral effects of testosterone in females (Cohen, 1988). Given that testosterone is pre- dominantly considered a male sex hormone, female sex hormones such as estrogen and progesterone may have a more signicant impact on risk propensity in decisions under risk and under uncertainty in females than testosterone. Both estrogen and progesterone, like testosterone, affect reward processing in the brain, which could affect risk-taking behavior (Dreher et al., 2007). Although some studies have investigated these effects, the ndings remain mixed (Derntl et al., 2014; Diekhof, 2018; Zethraeus et al., 2009). Taken together, these observations suggest that sex differ- ences in hormonal responsiveness and testosterone levels may account for the inconsistent ndings regarding the effect of the neuroticism–anxiety trait on the relationship between testosterone levels and 192 ECONOMIC AND BUSINESS REVIEW 2024;26:184–195 risk propensity in decisions under risk and uncer- tainty. 3.1 Limitations To our knowledge, this is the rst study exam- ining the effects of personality traits, specically neuroticism–anxiety, on the relationship between basal testosterone levels and risk propensity in de- cisions under risk and decisions under uncertainty. There are several strengths to our study. First, we examined the effects of certain personality traits on the relationship between basal testosterone lev- els and risk propensity in decisions under risk and uncertainty, which had not been done before, al- though there are theory-driven reasons for doing so (Welker et al., 2015). Second, following the eco- nomic distinction (Knight, 1921), we appropriately distinguished between risk propensity in decisions under risk and risk propensity in decisions under uncertainty. Furthermore, we used appropriate mea- sures to evaluate decisions under risk and decisions under uncertainty, which is generally not done ad- equately in the existing literature (for more details, see De Groot & Thurik, 2018). Decisions under risk and uncertainty are characterized by known and unknown probabilities, respectively (Knight, 1921). GDT allows participants to calculate expected re- turns and associated probabilities, which makes it an appropriate measure of risk propensity in decision making under risk. In contrast, in BART, partici- pants cannot predict when each balloon will explode and are thus unable to calculate expected returns and associated probabilities. This makes BART an appropriate measure of risk propensity in decisions under uncertainty. Finally, in contrast to prior re- search on the relationship between basal testosterone levels and risk propensity in decisions under risk and uncertainty, which has predominantly used sam- ples of undergraduate students (Stanton, Liening, & Schultheiss, 2011) or exclusively male samples (Apicella et al., 2008), we used a mixed-sex sample of graduate students and experienced decision makers to ensure better generalizability and validity for both sexes. However, there were some limitations in the present study. First, due to nancial constraints, we were not able to offer participants real monetary rewards equivalent to the amounts simulated in the BART and GDT. This limitation impacts the ecological validity of our ndings, as the simulated monetary rewards may not accurately reect participants’ real-life decision- making process under risk and under uncertainty in the nancial context. Consequently, the gener- alizability of our results is restricted to laboratory settings and may not translate to real-life nancial contexts. To address this limitation, future research should aim to externally validate BART and GDT by using real monetary incentives that mirror actual nancial stakes. This approach would improve the applicability of these measures to real-life nancial decision making and provide a more robust under- standing of how individuals assess and respond to risk and uncertainty in nancial contexts. Second, the present study tested only the associations be- tween endogenous testosterone levels, personality traits, and risk propensity. We were therefore un- able to draw any conclusions about causality. Future studies should examine the effects of exogenously ad- ministered testosterone to determine causality. Third, the study was limited to examining the effects of a single hormone, testosterone. However, it is possi- ble that estradiol could play a role in risk taking in women (Bröder & Hohmann, 2003; Peper et al., 2018). Finally, the sample size was relatively small, which may have contributed to the non-signicant results. Future studies should aim to replicate these ndings in larger sample sizes. Nonetheless, we were able to partially conrm the rst hypothesis and show that the neuroticism–anxiety trait affects the relationship between basal testosterone levels and risk propensity in decisions under risk, supporting the hypothesis that decision making under risk is a complex process that depends on neurobiological and psychological systems (Mehta et al., 2015; Welker et al., 2015, 2019). 4 Conclusion The present study aimed to investigate the effects of certain personality traits (neuroticism–anxiety, socia- bility) on the relationship between basal testosterone levels and risk propensity in decisions under risk and decisions under uncertainty in a mixed-sex sample of graduate students and experienced decision makers. We found that the relationship between testosterone levels and risk propensity in decisions under risk was affected by neuroticism–anxiety in males. Specically, testosterone levels were positively related with risk propensity in males low in the neuroticism–anxiety trait, whereas they were negatively correlated in those with a high neuroticism–anxiety score. However, in males, no signicant correlations were observed be- tween testosterone levels and risk propensity in deci- sions under uncertainty, or in females in both risk and uncertainty conditions, regardless of neuroticism– anxiety and sociability scores. These results suggest that the interaction between neurobiological factors and personality traits is important in decision making under risk in males. Furthermore, the lack of sig- nicant ndings in females and in decisions under ECONOMIC AND BUSINESS REVIEW 2024;26:184–195 193 uncertainty may indicate sex differences and context- specic effects in the neurobiological and psycholog- ical determinants of risk propensity. 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Journal of Personality, 68(6), 999–1029. https://doi.org/10.1111/1467-6494.00124 ECONOMIC AND BUSINESS REVIEW 2024;26:184–195 195 Appendix Table A1. Pearson correlations between variables (Sex, Age, Decision-making experience, T (pmol/L), T (z-score), ln(Sy score), ln(N–Anx score), ln(BART score), and ln(GDT score)). Variable N M SD 1 2 3 4 5 6 7 8 9 1. Sex 100 0.58 0.50 – 2. Age 100 28.91 7.75 .09 – 3. Decision-making experience 100 0.40 0.49 .17 .83** – 4. T (pmol/L) 100 0.00 0.10 .74** .05 .01 – 5. T (z-score) 100 168.22 124.57 .00 .07 .07 .64** – 6. ln(Sy score) 100 1.47 0.66 .04 .06 .07 .16 .16 – 7. ln(N–Anx score) 100 1.28 0.76 .21* .36** .36** .22* .07 .22* – 8. ln(BART score) 100 3.53 0.49 .14 .17 .06 .06 .04 .06 .05 – 9. ln(GDT score) 100 2.96 0.98 .13 .00 .03 .05 .05 .07 .03 .02 – Note. TD testosterone; SyD sociability; N–AnxD neuroticism–anxiety; BARTD Balloon Analogue Risk Task; GDTD Game of Dice Task. Sex is coded such that 0 represents males and 1 represents females. Decision-making experience is coded such that 0 represents students and 1 represents decision makers. Signicance is displayed at p < :05( ) and p < :01( ).