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This paper investigates whether personality traits, affects, and anticipated emotions measured before a stock market simulation explain participants’ trading style. The study relies on a sample of 133 undergraduate students from the University of Mons, Belgium, who participated in a four-hour CAC 40 trading simulation with a virtual portfolio of EUR 100,000. Regressions were estimated on several dimensions of trading style: number of transactions, minutes per order, average transaction size, average cash holdings, and portfolio volatility. The results show that psychological variables explain little of trading frequency or pacing but are informative about the structure of market exposure. Negative affect is associated with higher cash retention, whereas positive anticipated emotions are associated with lower cash holdings. Gender and openness also predict position size, while gender, age, and openness are significant predictors of portfolio volatility. Overall, the findings suggest that psychology explains less how much individuals trade than how they structure their market exposure.

Through a thematic analysis, we analyze the evolution of cognitive biases among eight participants (students) during a three-day trading simulation in a market that was perceived as unfavorable. The biases studied include overconfidence, representativeness, anchoring, herd behavior, availability and prospect theory. Prospect Theory, particularly through loss aversion, is strongly present and dominates the experience of most participants. It is perceived as ‘difficult’ even with virtual money. Some manage loss aversion with strict stop losses, while others, when confronted with losses, may take more risks in order to try to ‘recover’. Gains generate moderate satisfaction rather than euphoria. Virtual money seems to reduce the emotions connected with gains and losses for some participants. The Availability Bias is widespread. The participants focus on easily accessible information such as graphs, well-known company names, basic news and widely used indicators. Fundamental analysis is often rejected as too complex, time-consuming or irrelevant.  Anchoring Bias is variable. Some participants use specific limits as reference points. Representativeness bias is generally stable throughout the experiment. It involves using familiarity with companies as a decision-making criterion, or applying principles perceived as effective, such as using well-known technical indicators. Overconfidence varies considerably from one participant to another, influenced by previous experience and results achieved. It can be very low at the beginning, grow with confirmed intuition, or decrease in response to an unfavorable market. In the context of the study, Herd Behavior corresponds to a desire to find comfort in the group of participants in order to overcome a feeling of isolation, rather than a desire to copy behavior. The key findings of our research demonstrate a strong aversion to loss (prospect theory).   

<p><em>This paper proposes an empirical analysis of the role of memory in determining the size of credits granted by the European Bank for Reconstruction and Development (EBRD) during 1991–2003. We first build an original database from information associated with the number and contract types granted by clients, after which we develop an empirical strategy for capturing the role of memory, namely by defining three different indicators to approximate each client’s reputation. These indicators rely on the client’s identity and, when available, information associated with previous EBRD-financed investment projects. With the fixed-effects estimation technique, our results unambiguously show that the value of the first investment project financed by the EBRD, as a proxy for reputation, is the most effective indicator for established clients to determine the size of the credits they receive to finance further investments.</em></p>

This paper proposes an empirical analysis of the role of memory in determining the size of credits granted by the European Bank for Reconstruction and Development (EBRD) during 1991–2003. We first build an original database from information associated with the number and contract types granted by clients, after which we develop an empirical strategy for capturing the role of memory, namely by defining three different indicators to approximate each client’s reputation. These indicators rely on the client’s identity and, when available, information associated with previous EBRD-financed investment projects. With the fixed-effects estimation technique, our results unambiguously show that the value of the first investment project financed by the EBRD, as a proxy for reputation, is the most effective indicator for established clients to determine the size of the credits they receive to finance further investments.