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Area of Science:

  • Social network analysis
  • Behavioral finance
  • Organizational dynamics

Background:

  • Affective relationships significantly influence social organization and performance.
  • Understanding the dynamics of relationship change and its impact on performance is crucial.

Purpose of the Study:

  • To investigate the relationship between changes in affective relationships and trading performance among day traders.
  • To identify specific relationship configurations that resist change and their performance implications.

Main Methods:

  • Analysis of instant messaging data (>2 million messages) from 66 day traders over two years.
  • Correlation of inferred affective relations with trading performance metrics from profit and loss statements (>1 million trades).

Main Results:

  • Triads of relationships tend towards affective balance, with one configuration showing resistance to change.
  • Network balance positively correlates with trading performance, indicating a
  • hot hand
  • phenomenon.
  • Traders with balanced networks demonstrated consistent high performance streaks.

Conclusions:

  • Affective network structures play a critical role in determining trading performance.
  • Interventions aimed at balancing social networks may enhance financial trading outcomes.
  • Understanding and managing polarization within financial institutions is key to optimizing performance.