What your portfolio says about you
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The Insightful Leader Logo The Insightful Leader Sent to subscribers on October 25, 2023
What your portfolio says about you

What’s in your portfolio? Are you betting big on lots of high-risk, high-reward stocks, or are you mostly playing it safe with U.S. treasury bonds?

How you answer this question likely reveals something important about your personality, according to some interesting new research by Kellogg associate professor of finance Zhengyang Jiang. Jiang and his coauthors found that the Big Five personality traits—agreeableness, conscientiousness, extroversion, openness, and neuroticism—have a meaningful impact on our investment decisions.

Two traits in particular—neuroticism and openness—stand out for their role in shaping how investors play the stock market (or don’t). Nervous Nellies, it turns out, steer clear of equities, while openness is correlated with more stock investing and lower risk aversion.

This week, in addition to exploring the intersection of personality and portfolio, we’ll also explain why your next presentation may not benefit from a big reveal.

The power of personality

Jiang’s research involved surveying the 150,000 members of the American Association of Individual Investors (AAII), a nonprofit organization that teaches individual investors how to successfully build investment wealth.

The study’s key innovation was to combine questions about the process of investment decision-making with a 20-item questionnaire that aimed to determine each respondent’s personality traits using the Big Five model. Another set of questions focused on equity allocation—specifically, how much money each respondent had invested and what percentage was in stocks. The survey also sought to ascertain attitudes toward risk.

Analyzing the survey data, Jiang and his coauthors found that individuals with high openness and low neuroticism tended to invest more in equities—including individual stocks and stock funds.

Many of the connections the researchers identified are intuitive. The data showed, for example, that highly neurotic investors are much more concerned with downside risk. Investors with high conscientiousness and extroversion, by contrast, expect a lower probability of a market crash. And people scoring high on openness are more willing to entertain the possibility of either an upside or downside.

So take a look at your portfolio. What does it say about you? And with this in mind, is there anything you should be doing differently? You can read the whole article here.

No surprises necessary

Now, as promised, here’s the big reveal about big reveals. You know the moment: that point in the presentation when you dramatically present your view of a business problem—as well as the solution—and wait for the praise to roll in.

Joel Shapiro, a clinical associate professor of managerial economics and decision sciences at Kellogg, is not a fan.

“[B]ig reveals” are a bad practice—in danger of backfiring,” Shapiro writes in Harvard Business Review. “Too much surprise in a final presentation can put the audience on the defensive. The reason? Surprising results often prompt people to start questioning the underlying data and methods.”

Shapiro is writing about data scientists in particular, but his advice seems relevant to anyone looking to solve a tough problem in a large organization.

Instead of holing up in your office trying to find the solution on your own, he advises what he calls “problem-shepherding,” where you provide regular (preliminary) updates to other interested parties, hashing out debates about how the data should be interpreted and analyzed in real time. He suggests asking questions like, “Are these initial results of interest?” and “Are we defining terms correctly?”

You can read more of his advice to aspiring data scientists here.

“AI in general, and generative AI more particularly, is the shiny object that everybody’s chasing. And when clients chase shiny objects, consultants chase clients.”

Mohanbir Sawhney, in Business Insider, on consulting firms’ race to develop AI expertise.

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