Covid-19 strengthens the case for AI in fund management - study

Covid-19 strengthens the case for AI in fund management - study
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The coronavirus pandemic has provided some evidence of the effectiveness of the use of artificial intelligence (AI) as a predictive tool in fund management, according to the latest issue of The Cerulli Edge - Global Edition.

The cumulative return of AI-led hedge funds was almost three-times higher than that of the overall hedge fund universe during this period: 33.9% compared to 12.1%. Despite this, AI-led hedge funds' net new flows fell slightly last year, before dropping sharply between January and April. 

Analysis by Cerulli Associates of the assets under management (AUM) and net new flows of Europe-domiciled AI-led funds from 2013 to April this year shows strong AUM growth from 2016 to 2019.

European AIEuropean AI-led active equity funds grew at a faster rate than other active equity funds from January to April this year and showed a less-pronounced decline in March.

"There has long been suspicion of the ability of AI to react to unexpected events, such as the coronavirus pandemic, but there is now a sense that the technology has advanced to the point where it is better able to adapt to unforeseen scenarios via the ever growing amount of market data available," according to Justina Deveikyte, associate director, European institutional research at Cerulli.

Machine learning

Most of the machine-learning algorithms used in finance are supervised, meaning that the model learns to recognize patterns by analyzing historical examples. With the pandemic-led global lockdown being a new and unforeseeable event, it is extremely difficult for the models to adapt to the various scenarios dynamically, explains Cerulli.

The training of algorithms able to model and predict regime changes remains challenging for two main reasons:

  • The short and sparse history of financial data—only the past few decades can serve as a training example and a large part of human history (such as previous pandemics) is unknown to the algorithms.
  • The non-stationary nature of financial markets that can be impacted by an unprecedented set of events.

Cerulli added that until the turmoil caused by the pandemic is over, it is not possible to draw fully accurate conclusions on the effectiveness of AI during the period.

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