Morgan Stanley on what makes crowds wise: 3 key conditions explained

A Morgan Stanley report details three conditions for 'wise crowds': cognitive diversity, effective information aggregation, and incentives. It says these factors allow groups to be highly accurate in financial and prediction markets.

Diverse views, effective aggregation of information and incentives for participants to act on their knowledge are the three key conditions needed for crowds to make better decisions, according to a Morgan Stanley report.

"Wisdom is accompanied by specific conditions," it said, identifying cognitive diversity, aggregation and incentives as the three key factors.

The Three Pillars of Crowd Wisdom

The report examined how collective intelligence works across prediction markets and financial markets. It noted that crowds can be highly accurate when these conditions are present, but can also make poor decisions when one or more of them break down.

Cognitive Diversity

According to the report, cognitive diversity is not simply about differences in social characteristics but about differences in participants' information, knowledge, approaches and mental models. Such differences allow a group to draw on a wider range of information and perspectives. The report said collective error tends to be smaller when participants are cognitively diverse and their views are properly aggregated. It identified diversity as the condition most likely to be violated in financial markets, where investors can influence one another and develop correlated views, potentially contributing to market booms and busts.

Aggregation of Information

Aggregation is equally important because having diverse information alone does not ensure a good outcome. The report said markets use different mechanisms to combine information and arrive at a measure of the likelihood or value of an outcome. It noted that even simple methods such as averaging forecasts can improve accuracy, while weighted averages and other techniques can provide further gains.

Incentives for Accuracy

The third condition, incentives, refers to rewards for being right and penalties for being wrong. In markets, these incentives can be measured through monetary gains and losses. The report said participants with a well-founded view that differs from the market can have an incentive to act on that information.

Application in Prediction Markets

Morgan Stanley also examined prediction markets, saying they can provide real-time probabilities that may be useful for forecasting. It noted that such markets have generally been found to be more accurate than polls, although the advantage is not always clear-cut. In one example, the Iowa Electronic Markets had an average forecast error of 1.5 percentage points one week before US presidential elections, compared with 2.1 percentage points for the final Gallup poll in the elections studied.

Broader Applications and Future Outlook

The report further added that these principles of collective intelligence could have applications beyond markets, including hiring, employee training, meetings and organisational decision-making. It also noted that large language models could reach parity with superforecasters at some point in 2027. (ANI)

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