Trader Intuition and Decision-Making Dataset
Description
Description: This dataset was collected to analyze the role of intuition in trading decisions. It contains survey responses and performance data from traders, capturing various aspects such as experience, risk-taking ability, historical returns, reliance on news feeds, and the use of intuition or gut feelings in trading. Additionally, it includes detailed performance metrics on correct and incorrect trading decisions across different time frames. The dataset is structured to facilitate research on behavioral finance, decision-making processes, and the impact of intuition in financial markets. Key Variables: Demographics & Experience: Respondent ID, experience level, risk-taking ability Trading Behavior: Highest return on capital, maximum drawdown, type of trades Cognitive & Intuitive Factors: Importance of news feeds, reliance on past trade history, use of intuition Performance Metrics: Correct and incorrect trade classifications, calculated intuition scores, t-test values Usage: This dataset can be utilized for behavioral finance research, trading psychology analysis, and machine learning applications in financial decision-making. Format: Excel (.xlsx)