Big Data, Machine Learning, AI… Blah Blah Blah! (Gravitas)

KEYWORDS: AI, Machine Learning, Big Data, Algorithmic Trading, technology


Jayesh Punater, founder and CEO, Gravitas

  • Gravitas


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.

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.” Leading quant funds, the “big boys”, 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. 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). The top quant funds 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.

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

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