Using Structural Balance to explain traders’ performance
https://www.sciencedaily.com/releases/2019/06/190617125133.htm
This article discusses the findings of a study that sought to understand how the relationships between day traders in a professional network affects decision making and performance. Researchers analysed the instant messages between the traders over a 2 year period to determine the nature of the traders’ traders relationships to each other and also gathered data about each traders performance. Using the findings, they were able to conclude that traders that were part of balanced networks had the highest trading performance, regardless of their level of skill or talent. They also found that over time, workers tended to gravitate towards being part of structurally balanced networks.
The try to understand these results, we can look to the Structural Balance Property. For instance, in a given network, if 3 traders were to be in a triangle with 3 negative edges, this would mean that the 3 traders are all “enemies”. In this situation, there may be a lot of hostility and conflict between the traders. Being in this dissonant environment might lead to a lot of mental stress and tension, which may result in traders making poor high-risk trades. Similarly, lets consider an unbalanced triangle with traders A, B and C where A has a forms a positive edge with both B and C, but there is a negative edge connecting B and C. This would mean that one trader is ‘friends’ with the other two traders, but the two traders are not friends themselves. This could lead to a lot of stress for Trader A, who would try to push traders B and C to get along. This psychological dissonance may lead to A experiencing a lot of stress at work, and therefore might make poor decisions in his trades.
We can also use the structural balance property to explain why performance was better for individuals part of balanced triads. Let’s suppose there is a balanced triangle with 3 positive edges. In this network, the 3 traders would ‘friends’ with each other- and there would therefore be no conflict or hostility between the traders. This would cultivate a ‘stress free’ working environment and thereby enabling traders to have more “mental energy” when making high risk decisions, helping them perform better. The researchers also found that traders made better trades if they were part of a network whereby the ‘enemy of their enemy was their friend’. This triangle would be characterised by two negative edges and one positive edge. Since this triangle is balanced and natural, this could also lead to less psychological stress and tension for the traders in this triad and enable them to make better trades and have a better overall work performance. The structural balance property therefore explains why trader’s performance were better for traders that were part of balanced networks.
Another key finding from the study was that over time, traders also gravitated towards being part of more balanced relationships in the workplace. Again, if we look to structural balance theory, it reasons that people try to minimise unbalanced triangles in their relationships, and so they are far less common than balanced triangles. In line with this, traders would be constantly reassessing their likes and dislikes of one another and strive to be a part of structurally balanced networks so they can reduce sources of emotional stress and dissonance in the workplace. This can explain why over time, it was found that these unbalanced networks became less and less common in the workplace.