Inside Your Asset Manager’s Brain | Chief Investment Officer

Does your asset manager have the mental ability to outperform in their investments?

Researchers from the University of Zurich and Yale School of Management have suggested that success in asset management requires two kinds of intellectual strengths: analytical and ‘mentalizing’.

Analytical ability refers to a “person’s grasp of the quantitative aspects of a decision problem,” including “logical reasoning and mathematical or probabilistic calculations,” explained Andreas Hefti, Steve Heinke, and Frédéric Schneider. ‘Mentalizing’ capability, meanwhile, is rooted in empathy and psychology: It explains the ability to “understand others’ beliefs and intentions, which helps to predict their actions.”

Both, the authors argued, are necessary for high performance in investing.

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“To correctly understand the fundamental value of an asset, a trader needs analytical ability, and to correctly judge market sentiments, she needs ‘mentalizing’ ability,” they wrote.

To prove this theory, the researchers divided managers into classifications depending on their ability in each of the two areas: “technocratic” investors—highly analytical with low ‘mentalizing’ capability; “semiotic” types—“keenly aware of others’ behavioral patterns” but lacking “a conceptual understanding of the decision situation”; and “sophisticated” investors—strong both analytically and behaviorally. The fourth group—“featureless”—was weak in both areas.

These investors then made trades over 15 periods of an asset-market game which eventually resulted in a price bubble.

The technocrats largely traded on fundamentals—buying cheap and selling high. While these investors made money from the dividend, they “miss out on the profits from speculating on the bubble,” the authors noted.

Semiotic investors, meanwhile, followed the rising asset price, with holdings peaking just after prices peaked.

“These types make the largest losses as they are unable to unload their shares profitably after the peak,” the paper said.

Sophisticates, who anticipated both the rising and the bursting of the bubble, made the most money by having the best market timing.

“A purely ‘fundamentalist’ approach to asset trading, without an understanding of the psychology of the market,” the researchers concluded, “may not yield maximum profits.”

Read the full report, “Mental Capabilities, Trading Styles, and Asset Market Bubbles: Theory and Experiment.”

Do environmental, social, and governance (ESG) considerations help or harm investment performance? Big data might have the answer.

In paper commissioned by the Environment Agency Pension Fund (EAPF), Henley Business School professor and data scientist Andreas Hoepner explored the effects of ESG investing—and divestment from “sin stocks” in particular—on the risk and returns of a portfolio.

“[Data science] is not only crucial for potential divestment of sin stocks, but also for investing purely in environmentally responsible firms.”“A core component of our responsible investment policy is to ‘apply evidence-based decision making in the implementation of responsible investment,’” wrote Faith Ward, responsible investment and risk chief at EAPF. “Financial data science can help investors consider the perennial and thorny question as to whether ESG integration in investment processes can be beneficial to returns and risk of their portfolio.”

Hoepner argued that data science offered the best insight into this question, because it involves “large scale, deep data, and advanced statistical analysis”—allowing researchers to identify what is happening in the real world as opposed to what should happen according to economic theory.

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“While both divestment campaigners and financial economists tend to argue on a normative (‘should happen’) level, modern technologies such as algorithmic learning and big data analytics allow financial data scientists to address crucial societal questions from a more descriptive (‘is happening’) level,” he explained.

His findings? ESG factors can be used to identify signals for higher return and reduced downside risk, so long as investors possess the “necessary sophistication.”

Even the exclusion of “sin stocks” like tobacco firms—supposedly high-performing equities—is actually beneficial to investment portfolios, Hoepner found. This is in direct contrast with recent research by Wilshire about the California Public Employees Retirement System’s tobacco divestment: The consultant reported that the fund missed out on roughly $3 billion in returns since exiting tobacco stocks in 2000.

“While one might, simplistically, consider tobacco firms as ‘safe’ value stocks, deeper analysis shows that they actually exhibit riskier growth stock characteristics within their industry, which itself is closely associated with value investing,” Hoepner wrote. “In other words, while consumer goods are likely a safer investment during economic downturns than the average industries, tobacco stocks are actually less likely safe than other consumer goods.”

Furthermore, when analyzing “realistic” value-weighted portfolios instead of the standard equal-weighted portfolio benchmark, Hoepner found no evidence of outperformance by sin stocks, either globally or in the US.

“[Data science] is not only crucial for potential divestment of sin stocks, but also for investing purely in environmentally responsible firms,” he concluded. “While financial economists would expect that this should increase portfolio risk, it is actually significantly reducing the worse case risk of investable pension fund portfolios.”

In a separate report, the BlackRock Investment Institute has argued that climate risks had been “underappreciated and underpriced because they are perceived to be distant.” The researchers added investors that engage with climate change research and technology will also be able to reap financial rewards.

Read the full paper, “Financial Data Science for Responsible Investors.”