How hedge funds are leveraging alt data to gain a competitive advantage over markets

One of history’s most volatile years in capital markets is driving investment houses to seek out alt data sets – from Chinese ship container movement to changing consumer energy consumption patterns
In this article we will talk about:
What role alt data played for yield-hungry investors during coronavirus
As the economy takes turns and twists during the hurdles that the novel coronavirus has thrown at world economies, many hedge funds feel that they can no longer rely on traditional data sets. This is due in large part to the speed with which traditional data is produced and delivered to decision-makers. On the other hand, alt data is delivering real-time insights into
- Economic trends
- Corporate profitability
- Production and delivery cycles
- Consumer sentiment and spending habits
Hedge funds have reportedly spent 50% more over the course of 2020 on alternative data collection when compared with 2019 spending levels.

The speed at which the economy is changing can be seen by the volatility of capital markets over the last year.
Here is a chart comparing the volatility of financial markets since the start of the pandemic in comparison with how other crises in recent history have affected market volatility:

And with volatility comes a desire to know what is happening next, especially for firms managing sovereign wealth funds with billion-dollar valuations.
Covid-19 alt data use cases
Now that we have established that there is increased market volatility which is driving hedge fund appetite for real-time financial data. One wonders how hedge funds have practically leveraged alternative data sets in their mission to get a handle on markets and navigate funds to profitable safe havens during stormy financial weather.
Here are a handful of the most notable instances that can illustrate the edge that certain funds gained over markets by using alt data to their advantage during COVID-19:
Chinese alt data drove profitability for Accenture
Accenture Consultancy collected social media posts, and government statements throughout the Middle Kingdom as well as Chinese ship container movement throughout the pandemic.
These data sets enabled them to gauge things such as:
- Chinese consumer sentiment
- When governments were planning closures so that they could anticipate changes in the retail, travel, and restaurant industries
- How coronavirus was affecting exports on a daily basis which had effects on supply chains throughout the west including consumer prices and distributor profitability
Paribas Asset Management increased alt data spending by 10%
Paribas Asset Management (PAM), a firm that is responsible for managing upwards of 400 billion Euros has actually increased its spending by a significant 10% over the past year in order to gain access to new, alternative data sources. During Covid they were especially vigilant of two main alternative data sets:
- Coronavirus infection indicators – This includes a host of data including the ‘R’ / reproduction number of the virus, new cases, vaccination rates, geospatial data of unique instances where mass public crowding was observed such as political rallies in the US. The latter for example could enable them to identify an area where infection rates would rise over the following two-week period, thereby harming local businesses and industries. When pieced together, this data could very much serve as an indication of when to sell certain stocks and when to pickup others at rock bottom prices.
- Real-time energy consumption – The way people have consumed energy globally has changed drastically from the onset of the pandemic. Working from home combined with cross-the-board lockdowns have lead to little to no commuters and limited public transportation. The fact that most people are at home most of the day has led to a decline in energy consumption in commercial spaces such as offices, shopping malls, gyms, and the like. Following consumer energy consumption is extremely important for knowing where to invest today and tomorrow. For example, companies that are building smart house systems, solar panels for private homes, and similar private energy cost-efficiency-drivers may see increased demand, whereas public electric companies may lose market share in the near term.
Unigestion’s news-reading algorithms improved equity portfolio performance models
The Swiss-based investment firm started collecting ‘public sentiment data’ from news reports published across the internet. It, in turn, fed this data to its investment portfolio performance models which enabled them to perform better.
The real value was achieved in that they could buy equities based on positive news and sell equities based on negative news, much quicker than was previously possible. This elimination of latency from a matter of hours or days to a matter of minutes and seconds gave them the ability to act swiftly and confidently.
This new system of collecting ‘alternative news data’ and implementing it into their investment models was mainly a product of the need to keep up with government and monetary changes implemented in response to coronavirus outbreaks and developments. But since seeing the increased profitability, it looks like Unigestion has been catapulted 10 years ahead of schedule into a world of data-driven algorithmic trading.
Summing it up
As the markets continue to rise and fall on the whims of a persisting coronavirus, the hedge fund-driven demand for alternative data and market indicators will continue to grow. Institutional investors who on the one hand are looking to protect shareholder capital while still being able to produce meaningful gains will surely continue searching for unique data sets that can be used to predict what consumers want and where markets are headed.