According to a new study in the INFORMS journal Management Science, the hectic world of Wall Street, dominated almost entirely by men, there is a strong link between male hormone, testosterone, and the way the shareholders manage business.
An international team of researchers recruited 140 young males to participate in experimental asset market simulation. Prior to the simulated trading period, the participants were given a topical gel containing testosterone or a placebo. The experiment's results - shared this week in the INFORMS journal Management Science - revealed more inflated price bubbles among markets inhabited by traders hopped up on testosterone.
The financial institutions that do work trading on the New York Stock Exchange are predominantly, perennially staffed by men. And now, a new study from the University of Western Ontario, University of Oxford and Claremont Graduate University, published in the INFORMS journal Management Science, has found that testosterone, the hormone found more so in men than in women, can be linked to the decisions that lead to stock market destabilization and crashes.
According to a study published in the INFORMS journal Management Science, entitled The Bull of Wall Street: Experimental Analysis of Testosterone and Asset Trading, testosterone contributes to fluctuations and in particular leads to overestimating values and building dangerous bubbles and consequently leading to financial crackdowns.
Data scientists are in high demand, taking the coveted number 1 spot on Glassdoor's Best Jobs in America list in both 2016 and 2017. INFORMS is an international organization where those interested in exploring this field can seek out information about the profession as well as certification and training solutions.
Ashley Smith
Public Affairs Coordinator
INFORMS
Catonsville, MD
[email protected]
443-757-3578
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Can we really trust AI to make better decisions than humans? A new study says … not always. Researchers have discovered that OpenAI’s ChatGPT, one of the most advanced and popular AI models, makes the same kinds of decision-making mistakes as humans in some situations—showing biases like overconfidence of hot-hand (gambler’s) fallacy—yet acting inhuman in others (e.g., not suffering from base-rate neglect or sunk cost fallacies).
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