For all the data, analysis, and modeling in investing, one quietly powerful force often goes unexamined: the personality of the person making the decision. Two fund managers can look at the same set of forecasts and fundamentals, and still diverge wildly in their allocations. Why? A new study by Jiang, Peng, and Yan offers a compelling answer: personality traits—especially Neuroticism and Openness—consistently shape how investors perceive risk, form beliefs, and construct portfolios.
Investors high in Neuroticism tend to worry more, expect lower returns, and see greater downside risk. This isn’t just mood—it directly affects equity allocation, even when accounting for risk aversion or expectations. Meanwhile, those low in Openness—less inclined toward novelty or ambiguity—often steer away from equities not out of pessimism, but discomfort with uncertainty.
This raises a disquieting possibility: some investors aren’t optimising for return—they’re optimising for emotional comfort. And because personality traits are stable and often subconscious, these patterns can persist for years without being noticed, let alone challenged.
In a coaching context, this is where real leverage emerges. Coaching creates the space to surface these emotional undercurrents—not to pathologise, but to make them usable. Recognising when you’re avoiding a trade because of risk, versus because of internal noise, can be the difference between discipline and drift. It’s not about removing emotion from investing—it’s about knowing which emotions are driving the decision.
For seasoned professionals, this isn’t just self-awareness for its own sake. It’s a strategic edge. If your equity allocation is chronically conservative or if you find yourself echoing the market consensus too easily, the underlying driver might not be your model—it might be your mindset.
Are your decisions shaped by market dynamics—or by the need to feel safe in them?
Reference: Jiang, Z., Peng, C., & Yan, H. (2024). Personality differences and investment decision-making. Journal of Financial Economics, 153, 103776. https://doi.org/10.1016/j.jfineco.2023.103776
