The experiment was designed to probe one of the most persistent ambiguities in behavioral finance: do emotions influence financial performance directly, or do they operate through the behavioral mechanisms that produce performance? Decades of research have established that affective states shape judgment under uncertainty, altering attention, confidence, risk perception, and action tendencies. Prospect theory demonstrated that decision-making under risk systematically departs from rational choice assumptions, while the affect heuristic literature suggests that people often rely on immediate positive or negative feelings when evaluating risky options. This implies that emotional tone may shape investment behavior even before any trade is made. But whether these pre-trading emotional states ultimately determine returns, or simply organize how investors expose themselves to the market, has remained unclear.

To disentangle these possibilities, the researchers placed participants in a four-hour stock market simulation using the ABC Bourse platform. Each participant received virtual capital of EUR 100,000 and could trade only CAC 40 equities under realistic conditions, including transaction costs of 0.2 percent. Short selling was not allowed, but participants faced no constraints on the number of trades or position sizes. They were free to trade actively, occasionally, or remain largely in cash. The simulation incorporated an academic incentive scheme based on final portfolio value, with the best-performing participant receiving two bonus points and all others receiving at least half a point. Rankings and performance feedback were available throughout the session, introducing a tournament-like competitive element. During the four hours, the CAC 40 index rose by approximately 0.30 percent, from 8,061.40 to 8,085.76 points, meaning the market environment was broadly favorable but relatively flat.

Before the simulation began, participants completed questionnaires measuring their emotional predispositions on five-point Likert scales. The researchers constructed six composite indices: positive and negative pre-trading emotional tone measured through PANAS items, positive and negative simulation-specific emotional expectations tied to the upcoming trading task, and two broader global composites aggregating the corresponding positive and negative dimensions. All six indices displayed strong internal consistency, with Cronbach’s alpha values ranging from .851 to .933. Importantly, the positive and negative poles were only weakly correlated with each other, suggesting that participants could simultaneously report high levels of one and low levels of the other, or various combinations in between. This justified retaining both poles as distinct dimensions rather than treating them as statistical mirror images.

The empirical strategy proceeded in two stages. First, the researchers examined direct associations between each of the six emotional predisposition indices and portfolio return, calculated as the percentage change between final and initial portfolio value. Second, they conducted exploratory mediation-style analyses testing whether each index was statistically connected to return through four behavioral indicators: total number of transactions, average transaction volume, portfolio standard deviation, and average cash holdings relative to initial capital. These models retained the formal structure of mediation analysis but were interpreted as exploratory rather than causal, because the behavioral indicators resulted from participants’ own trading decisions rather than random assignment. Bootstrap confidence intervals based on 5,000 resamples were used to assess estimated indirect paths.

The results were unambiguous on the performance side. None of the six pre-trading emotional predisposition indices was significantly associated with portfolio return, and no significant estimated indirect path emerged through any of the four behavioral indicators. The strongest bivariate correlation between an emotional index and return was weak and non-significant. This finding persisted even after the researchers applied a Benjamini-Hochberg false discovery rate correction across the 30 primary associations and after re-estimating models with participant-level controls including gender, age, prior stock-market experience, and the five OCEAN personality traits. The absence of significant return associations should be interpreted cautiously, however, given that the simulation lasted only four hours and portfolio returns were highly compressed around zero, with a mean return of -0.001 and a standard deviation of only 0.003.

By contrast, the emotional indices were consistently and significantly associated with trading-style indicators. Positive simulation-specific emotional expectations were significantly associated with larger average transaction volume, greater portfolio standard deviation, and lower average cash holdings, fully supporting the hypothesis that positive predispositions orient participants toward a more exposed trading style. Negative pre-trading emotional tone was significantly associated with smaller average trades, lower portfolio variability, and higher cash retention, fully supporting the corresponding defensive hypothesis. The global negative emotional predisposition composite showed the same pattern, correlating at -.236 with average transaction volume, -.263 with portfolio standard deviation, and .328 with average cash holdings. These associations point toward two contrasting configurations of market engagement: positive predispositions seem to organize a more engaged posture characterized by stronger capital commitment and greater willingness to accept variability, while negative predispositions organize a more defensive posture marked by smaller positions and a stronger tendency to preserve cash.

One behavioral indicator did carry a directional expectation regarding performance, and it was confirmed. The number of transactions was significantly and negatively associated with portfolio return, making trading intensity the most stable performance-related result in the study. This finding aligns with prior research showing that greater trading activity is not associated with better outcomes among individual investors, as more active investors tend to underperform. However, none of the six emotional predisposition indices significantly predicted the number of transactions, meaning that emotions did not explain why some participants traded more frequently than others. The behavioral indicators most closely associated with pre-trading emotional predispositions, such as position size and cash retention, did not significantly predict return, which helps explain why the mediation-style analyses did not reveal significant indirect paths.

From a psychological perspective, the researchers interpret this distinction in terms of action readiness. Positive pre-trading emotional climates appear to be associated with engagement and exploratory, approach-oriented behavior, consistent with the broaden-and-build theory of positive emotions. Negative pre-trading emotional climates appear to be associated with caution and defensive orientations, consistent with appraisal theories showing that different negative emotions produce distinct behavioral consequences. This does not imply that positive emotions necessarily improve decision quality, nor that negative emotions necessarily reduce it. It suggests that these states orient investors toward different ways of confronting uncertainty. Because the participants were novice investors with limited prior market experience, they were less likely to rely on established trading routines and more likely to express their psychological orientation directly through their behavior, making pre-trading emotional predispositions visible in trading style rather than neutralized by habit.

The study’s conclusions are bounded by several limitations. The simulation environment simplified some features of real financial markets, the participants were undergraduate students rather than professional traders, and the four-hour horizon may be too short for broad emotional predispositions to produce stable performance effects. The study was also powered to detect moderate associations but may have been insufficient to detect small ones, particularly in the exploratory mediation-style analyses. The academic bonus points and live rankings may have amplified competitive behavior and social comparison. Nevertheless, the central contribution stands: pre-trading emotional predispositions are more closely associated with how novice investors engage with the market than with the returns they eventually achieve. The findings suggest that greater attention should be paid to how emotions organize the style, intensity, and risk profile of trading behavior, rather than focusing only on whether they improve or reduce performance. In the early formation of investor psychology, it seems, feelings write the posture before they write the profit.

Subject of Research: Trading style rather than return: the role of pre-trading emotional predispositions in a stock market simulation

Article Title: Trading style rather than return: the role of pre-trading emotional predispositions in a stock market simulation

Article References: Finet, A., Kristoforidis, K., & Laznicka, J. (2026). Trading style rather than return: the role of pre-trading emotional predispositions in a stock market simulation. Frontiers in Behavioral Economics, 5, Article 1836906. https://doi.org/10.3389/frbhe.2026.1836906

Image Credits: AI Generated

DOI: 10.3389/frbhe.2026.1836906

Keywords: Trading, style, rather, than, return, role, pre-trading, emotional, predispositions, stock, market, simulation