Investor personality predicts investment performance? A statistics and machine learning model investigation

Investors use a wide variety of investment strategies, and the chosen strategy has a direct effect on the investor's individual performance. This study observes the personality attributes that affect an investor's investment patterns. We then analyze whether these attributes create significant differences in investors' financial performance, and determine which type of investment pattern is more profitable. Rather than using sentiment, a factor whose noise level makes performance predictions difficult, we use the investor's personality. We also apply statistics tests and machine learning algorithms as we investigate whether personality plays an important role in profitability. We find that the results provide strong evidence that investors' personality influences short-term and long-term trading performance. Using statistical models, the investors with personality traits such as conscientiousness, agreeableness, extraversion, and openness, as opposed to neuroticism, perform better over the long term. Our use of machine learning algorithms also reveals that investors with the traits of extraversion and openness are likely to invest more profitably in long-term condition. The results provide investors with insight that can help them choose future investment strategies.