An investment decision has always been a wager that one has more knowledge and better insight into an investment opportunity than the next person. From the beginning of investable markets, this has been the case — the investor with his or her investment process and biases against other humans with their own unique criteria and biases.
Some of the more successful investors over time have used rules-based investment approaches, which involve selecting investments that meet specific valuation or financial criteria, including price-to-earnings ratios, growth rates and profitability ratios. A major benefit of a rules-based approach is the removal of some of the emotion and bias from investment decision making. From Benjamin Graham to Warren Buffett, many well-known investors have credited their successes to rules-based strategies.
In practice, rules-based investing can be difficult to implement effectively, as the strategies often work better in some market environments than in others. In addition, investors face the challenge of sifting through the thousands of public companies and collecting and analyzing each piece of important information.
Artificial Intelligence Is a Game-Changer in the Execution of Rules-Based Investment Strategies
Artificial intelligence is “the study and design of intelligent agents” in which an intelligent agent is a system that perceives its environment and takes actions that maximize its chances of success.1
The evolution of artificial intelligence in the 1990s was a big step toward the mastery of this challenge. Capabilities generally recognized as AI include speech and image recognition, playing strategic games, and interpreting complex data. Many of us are familiar with AI through our interactions with Apple’s Siri or Amazon’s Alexa. Facebook also uses AI to identify our friends’ faces so that we can “tag” them, and banks use it to decipher our handwritten checks.2
Machine learning, a subset of AI, proved to be a powerful tool when applied to the investment strategy process. According to Andrew Dassori, founding partner and chief investment officer at Wavelength Capital Management, machine learning takes place when a system processes data to determine its ability to accurately anticipate unseen information and, applying its findings, enhances its development further for better outcomes in the future.3 Machine learning took static rules-based strategies and made them adaptive. As market conditions changed, investment success could be monitored continuously, and adjustments could be made on the fly to improve results. The next big step was to optimize the data set.
Big Data Revolutionizes Information Gathering and Enables Rapid Response
Big data are extremely large data sets that may be analyzed computationally to reveal patterns, trends and associations, especially relating to human behavior and interactions.4
Big data represents a broad spectrum of activity-generated information from a multitude of sources, including website visits, social media posts and cable television boxes. It also includes social influencer activity and public domain resources, such as Wikipedia and SEC/Edgar.5
Investment firms and hedge funds utilize a wide variety of “big data” sets — including weather, geopolitical events and satellite imagery — as inputs to their analyses. By obtaining a few minutes of lead time on a potential news story, measuring foot traffic at a restaurant or finding out how full the parking lots are at shopping malls, data analysts hope to gain a slight edge.
Rules-based strategies stand to benefit greatly from this development. In addition to revenues and earnings numbers and derived valuation measures from financial statements, mountains of additional information affecting thousands of potential investments can now be quickly processed and analyzed by computer.
The Human Advisor Is Not Going Away Anytime Soon
Twenty-some years into the big-data revolution, humans are still integral in the investment process. AI managed funds have been around long enough to develop a track record, but the results are mixed. The Eurekahedge AI Hedge Fund Index, which tracks 12 AI-managed investment pools, has outperformed hedge fund peers since 2013 but trailed the S&P 500 Index.6
The extension of the use of AI to the actual trading process has been mixed, as well, as disaster can sometimes strike quickly. Knight Capital, a high-frequency trading firm, collapsed in 2012 when its computers “ran amok,” essentially losing $10 million a minute in what proved to be a rather destructive 45-minute trading blitz.7 This was only one example of the potential consequences of taking the human trader or analyst out of the loop, but there are certainly a multitude of scenarios that would be detrimental with technology as the sole means of performing the necessary work.
An important contribution of the application of AI has been the advent of robo-advisors, which compile client data and build low-cost exchange-traded fund (ETF) portfolios for clients. Initially seen as a threat by advisors, they now are recognized as powerful tools to automate and streamline planners’ practices, giving advisors more time to interact with clients. In addition, robo-advisors have been found to appeal to younger, more tech-savvy clients.8
What technology can do is sift through thousands of data points and build a case for or against an investment or build portfolios for clients, taking into account mean-variance analysis as well as the objectives and preferences of the clients. The challenge for investment firms today is to successfully combine the information processing power of AI with the human abilities of intuition and communicating and empathizing with clients.
We know from the world of Chess that a computer can beat the best human players but also that a human-computer team can beat the best computer.9 This may help to define the role of AI in the investment industry going forward — firms will likely increasingly adopt it as a tool set to help investment professionals make better informed investment decisions or to perform routine portfolio management tasks. However, the task of sitting across the table from a client and talking him or her out of an emotional reaction to a difficult period in the market is something still best left to a human advisor — at least for now.
1 Definition taken from ScienceDaily
2 Guatam Narula. “Everyday Examples of Artificial Intelligence and Machine Learning.” TechEmergence, Feb. 14, 2017.
3 Andrew Dassori. “Artificial Intelligence for Investing.” Enterprising Investor, May 31, 2017.
4 Definition taken from Oxford Living Dictionaries
5 Andrew Brust. “Top 10 categories for Big Data sources and mining technologies.” ZDNet, July 2012.
6 Nishant Kumar. “Former Cohen Trader Trains Computer to Copy His Brain.” Private Wealth (FA Magazine), June 28, 2017.
7 Robin Wigglesworth. “Fintech: Search for a super-algo.” Financial Times, Jan. 20, 2016.
8 John Rubino. “My Favorite Robot.” CFA Institute Magazine, September 2016, Volume 27, Issue 3.
9 Milo Jones and Philippe Silberzahn. “Chess, Centaurs and Your Future As an Investor in an Age of Machine Intelligence.” Forbes, July 2015.
Rick Spencer is a fixed-income trader for the Capital Markets Group at 1st Global. In this role, he partners with affiliated advisors to apply his fixed income expertise to discover and create solutions that meet the clients’ needs.
The Capital Markets Group at 1st Global is a team of professionals with backgrounds and experience from large banks and broker-dealers in the industry. These individuals have the capabilities, knowledge and market relationships to provide timely trading, research and consulting to enable our advisors to service and nurture their business relationships with their clients.
All opinions expressed and data provided are subject to change without notice.
Some of these opinions may not be appropriate to every investor. Past performance is no guarantee of future results.
Asset allocation/diversification of your overall investment portfolio does not assure a profit or protect against a loss in declining markets.
Securities offered through 1st Global Capital Corp. Member FINRA, SIPC. Investment advisory services offered through 1st Global Advisors, Inc.