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Tracking Investors' Dance Moves To Deliver More Alpha

Editorial Staff, Group Editor , London, 21 October 2020

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Harnessing insights from behavioural finance, and drawing ideas from sports and other fields, a transatlantic consultancy and analytics firm argues that it is possible to delve into what produces consistent market-beating returns.

What is the secret of a wealth manager’s success? That is a question that many who dream of great returns will ask. The business sections of bookstores, physical and online, are stuffed with guides on how to make money. And it is not just about finance: sports coaches, health and fitness trainers and self-help gurus extol success ideas.

Unpacking the process that creates investment success and spotting patterns of mistakes is becoming increasingly possible because of computers – they can harvest data on a previously unheard-of scale – and also thanks to the insights of behavioural finance. In the latter case, a whole discipline has arisen that tries to understand the hidden biases and urges that investors bring to the table.

Clare Flynn Levy, who founded Essentia Analytics in 2013 after a long career in asset management, thinks the process of investing can be analysed more closely so that people’s results can improve. She also thinks that far too many active investment managers haven’t used data correctly to weed out errors.

“This is not about telling the client what they have to do but rather about showing how to make good decisions,” she told this news service in a recent interview. 

The firm aims to unpack the strategies used by equity investment managers in their quest to achieve “Alpha”, to see what patterns of successful behaviour emerge, and what patterns of mistakes arise. This is like the data analysis now being used by professional sports teams to introduce small incremental improvements that lead to improved win rates. (The book Moneyball: The Art of Winning an Unfair Game, by Michael Lewis, is an example of how a sports team manager crunched performance stats of teams and worked out a winning formula for baseball – although eventually the success faded when rivals worked out his methodology.)

Once the analysis is made, Flynn Levy said, Essentia can develop a set of “nudges” that notify the fund manager when they are close to making a mistake as noted in previous analysis.

Flynn Levy gave the example of how her business can identify the point at which a given portfolio manager’s ideas tend to run out of steam (such as stop generating incremental Alpha), then nudge them to review any position that arrives at that point. The result is a reduction in “round-trip” investments, where the manager first does very well with the investment, then gives all the gains (and then some) back.

In a year when markets have been roiled by the global pandemic, as well as the 2020 Presidential elections, such insights have traction. And with equity yields squeezed by ultra-low interest rates and managers’ fees under pressure, the ability to deliver consistent returns is worth paying for. Clients include AllianceBernstein, growing mid-sized managers like Brown Advisory, and hedge funds like Black-And-White Capital. They’re prepared to pay Essentia’s fees because the insights can increase Alpha generation by an average of 150 basis points per annum. Compounded over portfolios holding billions of dollars, the impact is “huge”, Flynn Levy said. 

Essentia has built case studies which it says prove its value. In one example, in three years working with Essentia, a manager’s outperformance vs his benchmark rose from 25 basis points per annum to 93 bps - an extra 68 bps of alpha per year. That equates to $108 million for his investors. For the manager - “Karl” - that equates to an annual return on investment of 435 per cent on his Essentia investment. In a second case study, a long/short hedge fund called “John”, Essentia says that in 12 months working with it, “John’s” trading performance improved from 102 bps per annum to 451 bps per annum. That’s an extra 553 bps of extra performance gained from “John’s” understanding of his own behaviour and using technology to mitigate his biases, in the first year alone.
 

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