While artificial intelligence (AI) is viewed as key to the future of the investment industry, hedge funds with a high reliance on AI strategies have struggled to perform in today’s volatile markets.
Data from Eurekahedge, a firm that tracks hedge fund performance, shows that AI-led funds have returned just 2.77 percent this year up to the end of July, compared with a return of 6.36 percent for the wider hedge fund universe.
Long-term performance tells a different story, however. While AI-focused hedge funds have lagged their peers over the last two years, they show strong outperformance on an annualized five-year basis.
Nicky Indradi, a hedge fund analyst at Eurekahedge, tells IR Magazine that the results must be viewed with caution because the AI hedge fund index has few constituents – around 30 at the time of writing – and is sensitive to outliers.
While many funds use AI to some extent, only a small number hand a significant part of the portfolio management over to AI or machine learning algorithms, he says.
Asked what could be contributing to weak recent performance, Indradi picks out several factors. For fund managers relying on alternative datasets, such as social media or satellite imagery, there may be a lack of historical data, which is needed to train the AI models, he says.
Indradi also notes the learning curve for fund managers switching over from traditional systematic strategies, as well as the volatile market conditions of recent years, rocked by trade wars and presidential tweets. ‘There’s going to be a period of learning for these AI models to get used to the new kind of market,’ he explains.
AI technologies are being broadly adopted across the investment industry as fund managers search for ways to cut costs and uncover new sources of alpha. Underscoring the trend, last year BlackRock set up a new center in California focused on research into AI.
IR departments are also starting to reap the benefits of AI as various firms roll out new tools targeted at the IR community, helping with tasks such as shareholder targeting and investor-sentiment analysis.
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