Alternative data (or ‘Alt-Data’) refers to data that is derived from a non-traditional source covering a whole array of platforms such as social media, newsfeeds, satellite tracking and web traffic. There is vast amount of data in cyber space which, until recently remained untouched. Here we shall look at the role of these unstructured data sets.
Information is the key to the success of any investment manager and information that can give the investor the edge is by no means a new phenomenon. Traditional financial data, such as stock price history and fundamentals has been the standard for determining the health of a stock. However, alternative data has the potential to reveal insights about a stock’s health before traditional financial data. This has major implications for investors.
If information is power, then unique information sourced from places not-yet-sourced is giving those players the edge in a highly competitive market. Given that we’re in what we like to call a data revolution, where nearly every move we make can be digitized, tracked, and analysed, every company is now a data company. Everyone is both producing and consuming immense amounts of data in the race to make more money. People are well connected on social media platforms and information is available to them is many different forms. Add geographical data into the mix and that’s a lot of data about whose doing what and why. Take Twitter, it is a great tool for showing what’s happening in the world and what is being talked about. Being able to capture sentiment as well as data is a major advance in the world of data analytics.
Advanced analytical procedures can pull all this data together using machine learning and cognitive computing. Using this technology, we can take the unstructured data and transform it into useable data sets at rapid speed.
Hedge funds have been the early adopters and investment managers have now seen the light are expected to spend $7bn by 2020 on alternative data. All asset managers realise that this data can produce valuable insight and give them the edge in a highly competitive market place.
However, it could be said that if all investment managers research data in this way, then that will put them all on the same footing and the competitive advantage is lost. Commentators have suggested that given the data pool is so vast and the combinations and permutations analysis is of data complex, it is still highly likely that this data can be uncovered that has not been uncovered by someone else. It all depends on the data scientist and where they decide to look. Far from creating a level playing field, where more readily available information simply leads to greater market efficiency, the impact of the information revolution is the opposite. It is creating hard-to access pockets for long-term alpha generation for those players with the scale and resources to take advantage of it.
Which leads us to our next point. A huge amount of money and resource is required to research this data, and this will mean only the strong survive. A report last year by S&P found that 80% of asset managers plan to increase their investments in big data over the next 12 months. Only 6% of asset managers argue that it is not important. Where does this leave the 6%?
Leading hedge fund bosses have warned fund managers they will not survive if they ignore the explosion of big data that is changing the way investors beat the markets. They are
Investing a lot of time and money to develop machine learning in areas of its business where humans can no longer keep up.
There is however one crucial issue which all investors should be aware of and that is the area of privacy. Do you know where that data originates from? Did that vendor have the right to sell the information in the first place? We have seen this illustrated over the last few weeks with the Facebook “data breach” where Facebook sold on some of its users’ data to Cambridge Analytica without the users’ knowledge. This has wiped $100bn off the Facebook value so we can see the negative impact of using data without the owner’s permission.
The key question in the use of alternative data ultimately is, does it add value? Perhaps too early to tell. Watch this space!
