BIG DATA, MACHINE LEARNING, AI…blah blah blah!

It’s been a tough year for performance and it’s been equally difficult to find alpha. The demise of active asset management has been predicted and the move to Exchange-Traded Funds (ETFs) and robo-advisors is now imminent. (1)

In the wake of these large shifts, many funds are beginning to look for new ways to leverage data and uncover insights throughout the investment process to recapture their “edge.”  The “big boys” like Two Sigma, Bridgewater, Point72, and Renaissance have been at it for years – so how is the rest of the industry going to catch up? 

To better understand the current situation, Gravitas has been speaking to many industry participants and uncovered the following:

  1. More and more funds are looking to get a better handle on structured data (market data, corporate actions, re-orgs, etc.). By using data mining and analytical tools/services, such as Eagle Alpha and Arcadia, funds are gaining insights that may support or disprove a fundamental investment thesis. Even the Trump campaign employed a data analytics group, Cambridge Analytica, to help them appropriately target the swing states. (2) 
  2. There is a move toward gaining access to “unstructured” data such as parking tickets, credit card information, railway track information, satellite images, clicks and ticks on websites, etc. to gather the reality of consumer behavior from third party providers like Yodlee and Adaptive Management.
  3. Some funds are leveraging machine learning to look for intelligence within these data sets. Analyzing the gathered information, patterns, and insights provides intel that professional human investors may not be able to see (certainly not as rapidly or accurately as with algorithms). Bridgewater, Point 72, Renaissance, and Two Sigma all use forms of AI during their investment processes. (3)
  4. The insights derived from AI create recommendations upon which funds are eventually able to make investment decisions. In some cases, AI trading technology is completely autonomous from human help, such as the technologies developed by Sentient Technologies. (3)

This newfound role of Big Data begs the question: will portfolio managers eventually be replaced with AI?

No, I don’t believe this will happen in the next twenty years. However, the move towards utilizing data analytics together with many new sources of data to assist with investment decisions is upon us. The shift towards technology is already being embraced in the investment world. In-house teams and startups are creating more functionality of data, which leads to different roles in the investment process. Anything from satellite data to shipping bills of landing to IP addresses by smart phones are being sold and leveraged, and the trend is rapidly growing.

In fact, my assumption for 2017 is that the use of big data and analytics in the front office to generate alpha will dwarf any other manager initiative. This new focus will create countless opportunities for firms providing data tools and an unlimited appetite for voracious consumers open to new tools that will give them an edge!

As a middle office and technology provider, Gravitas is actively looking at service models to help clients and industry leverage these trends.

 

Works Cited

(1) Foley, S. (2016). Asset Management: Actively Failing. Financial Times, 1. 

(2) Hope, B. (2016). Inside Donald Trump's Data Analytics Team on Election Night. The Wall Street Journal, 1.

(3) Metz, C. (2016). The Rise of The Artificially Intelligent Hedge Fund. Wired, 1.