Hedge funds appear vulnerable headed in to 2020. Portfolio gains have been sluggish, fees are at their lowest levels since tracking began, and 2019 ended a five-year period when investors pulled out more money than they invested in the industry. This all took place amid increased geopolitical risk resulting from China trade tensions and, most recently, military action against Iran has only added to the uncertainty.
It leaves many investors questioning the long-term sustainability of hedge funds. And it leaves hedge funds, especially those in the middle market, looking for new ways to gain a market edge.
The traditional approach of using corporate earnings reports, poring over regulatory filings and mining census data is not enough anymore. Instead, hedge fund managers are looking to alternative sources of information like web-scraped data, satellite imagery, credit card tracking and social media sentiment, all of which can provide an advantage for early middle market adopters. It’s known as digital exhaust, the kind of data that everyone leaves behind as they go about their daily lives. The promise is that this alternative data can provide unique and timely insights into new or different investment opportunities.
Larger hedge funds have been using this approach in recent years. It’s no guarantee of higher returns, but there are success stories. For example, Bloomberg reported that Point72 Asset Management, the $14 billion fund run by Steven Cohen, successfully shorted two publicly traded companies based in part on web search data and store traffic patterns.
But funds in the middle market – those with $100 million to $1 billion of assets under management – are left with a choice: make the necessary investment – data mining isn’t cheap – or risk being left behind in an ever more competitive industry.
According to RSM’s Middle Market Business Index, 46% of middle market executives indicated capital expenditures increased during the current period (and expect them to increase over the next six months), the lowest since the first quarter of 2017. Alternative data sets are large and complex and managers either purchase software to mine its own data or subscribe to alternative data sources; either way this is costly for middle market funds, and requires significant people or financial resources that they often times lack. What’s more, it’s no guarantee of better investment returns.
But without it, middle market hedge funds have struggled to differentiate their products and as a result are entering the market with less money, particularly in the $100 million to $1 billion category. This creates an environment with more middle-market losers than winners.
According to JP Morgan Capital Advisory Group, hedge fund launches declined most dramatically in two categories – those with $100 million to $250 million under management, and those with $250 million to $500 million — from 2018 to 2019, proving that middle market funds are struggling to keep up.
Source: JP Morgan Capital Advisory Group via Bloomberg
Fund managers will need to keep looking for new data sets or innovative ways to use them. Firms that leverage artificial intelligence and big data most are often able to create programmed algorithmic instructions using alternative data that creates downside risk protections that may benefit investors in a possible downturn.
The Eurekahedge AI Hedge Fund Index shows significantly less one-day pricing volatility than the Hedge Fund Research Global Hedge Fund Index, which includes firms that don’t self-identify with an AI strategy. Over the past two decades, the Eurekahedge index’s one-day pricing change has been far less and could be a good option for those middle market firms who are fearful or a slowdown.
