By Susan Barreto, Editor of Alternatives Watch
There are hundreds of so-called alternative data/big data providers that have sprung up in recent years at the ready to help hedge fund managers make millions.
Practitioners though are sharpening their analysis skills of the data as reliance in the hedge fund industry has proliferated in recent years.
Qaisar Hasan, portfolio manager for the 1798 Q Fund at Lombard Odier Investment Management and developer of Point 72’s data-driven long/short investment strategy, recalls a lightbulb moment that he had around 10 years ago.
He saw the trends driving big data such as decreased storage costs, arrival of Google Trends and an increase in computing power. It all suggested that data outside of stock prices and charts was set to grow.
Hasan said it continues to grow today at an exponential rate with more than 5,000 data sets to choose from as he speaks to about 100 data vendors each year.
“Generating data is becoming easier and cheaper and secondly there is more of an appetite for this data,” Hasan added.
According to a recent industry survey conducted by AIMA, the number of alternative data providers has grown from about 20 in 1990 to just over 400 in 2018. Hasan estimates there are likely about 700 vendors in the marketplace right now.
The International Data Corporation estimates that the size of the global datasphere in 2025 will reach 175 zettabytes, which is an increase of about 4.3 times from 2019.
Included in that universe is alternative data, which is the data sets often used by managers such as Hasan to access trends by looking at satellite imagery, social media trends and consumers’ shopping habits.
Of the 100 hedge fund managers surveyed by AIMA, managing a total of about $720 billion, roughly 53% said they were relying on alternative data to inform trading decisions. Another 14% told the trade organization that they were trialing data sets.
Among the most popular data sets used by hedge funds include web crawled data and data sourced from expert networks in addition to the traditional consumer data and social media/online sentiment.
Still with so much data at fund managers’ fingertips, the decision about what is useful and how to use it is not easy.
At the roughly $250 million 1798 Q fund, Hasan considers what the problem is he is trying to solve for. He spent much of his career covering TMT sectors in the U.S. and Asia and so he drills down how certain sectors behave in certain environments. If he is able to ‘crack the code’ for a certain type of business model that is how he is able to profit from the data available.
“Roughly 90-95% of the data we come across gives you false signals, so you need to have very strong filters,” Hasan said. For LOIM it is about looking back at cycles and if the data set captured a past business trend. Then the firm uses quantitative and qualitative ventures in analyzing at vendors.
Using the data, is a much different story for each firm. At 1798 Q, machine learning is used in the data normalization process and working with alpha numerical texts to data mapping and data cleansing. The data is essentially for the purposes of investment research.
How data is used depends on a manager’s investment style.
Olga Kokareva of Quantstellation, a multi-asset multi-horizon quantitative investment firm, said in a published interview that usage of alternative data differs between fundamental investment strategies and quantitative hedge fund strategies.
“Fundamental hedge fund managers normally use alternative data to reinforce their investment thesis that they derived from their regular research process,” Kokareva said. “For example, a manager can hold a long position in a retailer and they are thinking about closing it, but they are not sure. So, instead of waiting for the next quarterly report they can start looking at foot traffic data or credit card data. If the sales numbers are indeed going down, they might close this position earlier.”
He describes alternative data as an extension of the quantitative manager’s investment process.
AIMA found that managers often said they used alternative data in “helping to generate outperformance” and “researching investment opportunities” among other reasons.
AIMA’s survey was conducted prior to the COVID-19 related market volatility, where it may have been a help to some firms struggling to determine what trends were quickly emerging as society adjusted to a variety of new norms due to the virus.
At LOIM, officials had to pivot pretty quickly, Hasan said.
“Stock correlations went up, so we had to become much more forward thinking,” he added. The firm had to become more macro-oriented such as looking at vaccine developments or flattening the curve. More importantly, he had to look for new data.
Things the firm has eyed are looking for trends in the post-COVID world in how consumers behave, employees commute, travel risks, etc.
Much of the data they are now looking at is free including Johns Hopkins University data and that from the TSA on airline passengers. Then the team stitches together the information to construct a road analysis.
And still other pieces of data are now not as useful such as geo-location data as shopping malls were shut down in the early days of the pandemic.
The onus is still on the hedge fund manager to take the data and make it useful. But even Hasan admits the appetite is not as fast as the growth of the vendors.
Hasan said that the common misconception remains is that credit card details are useful, but in reality, they are only as useful in how you use the data. And even after eight years, he is still finding better ways to use the data.
For now, his strategy has done well and was positive for the year as of mid-June.
Officials at AIMA conclude that data is the big disrupter, adding that the pace of data collection is only likely to accelerate more as the opportunity set for investors becomes more compelling.
They point to one other statistic too that tells investors even more – 90% of the world’s data available as of earlier this year was only produced over the last two years.
And so it goes, in the increasingly quantitatively driven alternative investment world.
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