January 2018

Happy New Year.  The start of the year is always a good time to make predictions.  Here is mine.

Will the future of equity research be like this:

Like many other industries undergoing technological changes, equity research is another sector that is ripe for disruption.  Various asset managers and investment banks are already employing some form of artificial intelligence in their business.  In this insight, we will review and discuss the impact of artificial intelligence on the equity research industry.

What is AI?

Artificial intelligence (AI) is a branch of computer science that aims to create intelligent machines.  A core part of AI is machine learning – an engineering technique in which the software is not discretely programmed.  It involves statistical learning and analysing a large volume of data and relationships.  The software can only perform within its given set of parameters and is not capable of thinking outside the square.

AI will change the global industrial ecosystem. By transforming huge amounts of information into valuable insights and thus improving efficiency, not only will it be the main driver of the global economic growth in the future, but it will also be applicable in the equity research and investment process.  AI can be used in applications such as judging economic signals, monitoring the risk appetite of portfolios, or dynamically adjusting the investment portfolio to provide more tools for the investment team.  It can overcome human weaknesses such as subjectivity and memory deficiency, and process a large amount of data in a short period of time.  Also, a machine never sleeps or goes on holiday.

“Humans have biases and sensitivities, conscious and unconscious…It’s well-documented we humans make mistakes. For me, it’s scarier to be relying on those human-based intuitions and justifications than relying on purely what the data and statistics are telling you.” says Babak Hodjat, co-founder of Sentient and a computer scientist who played a role in Apple’s development of Siri.

According to PwC, global GDP is expected to be 14% higher in 2030 as a result of AI, meaning that an additional $15.7 trillion is expected to be added to the global economy.  Many of those who work in the financial sector are already speculating how AI will impact their jobs.

Robotic stocks outperform the broader market

Will a robot’s stock pick outperform the market?  Not long ago, this speculation became a fact. An artificial intelligence ETF called AI Powered Equity ETF (AIEQ) was launched in October 2017.  The AI ETF turned out to be a clear win over the Dow Jones Industrial Average (DJI), Nasdaq Composite Index (IXIC) and S&P 500 (GSPC) indices in the last month.

One Month Return of AIEQ and Market Indices Ending 11 Jan 2018

AIEQ was launched by the US EquBot Corporation and the ETF Managers Group.  The fund uses artificial intelligence and machine learning to analyze more than 6,000 listed companies in the US, acquire millions of data points and build numerous financial models, and conduct an in-depth analysis from the current economic situation, future trends and major events of each of the covered companies.  It then picks out a portfolio of 70 stocks, which are then used by the fund managers at ETF Managers Group for portfolio allocation.  According to the company, its strategy has been backtested but they have declinedto provide historical performance data due to compliance issues.

Notably, EquBot hired IBM supercomputer Watson to provide the last ten years of historical data for US public companies and real estate funds as well as recent economic data to help AIEQ perform fundamental analysis.  Essentially, EquBot AI works with Watson to create an equity research arm that is constantly analysing data and financials 24 hours a day, 365 days a year.  In this process, there is no artificial bias and downtime.

According to Art Amador, the co-founder of EquBot, the emergence of big data has created a huge challenge for portfolio managers and artificial intelligence can help solve these problems. The birth of AIEQ marks the beginning of how investment firms are exploring more efficient ways to invest and manage its human resources.  AI investing may become a mainstream investment category, sitting alongside passive and active investment in an investor’s diversified portfolio.

However, time will tell as to how an AI-powered equity ETF will perform over a longer time period, or whether it is more suitable for shorter-term trading opportunities.  Arguably, shorter-term investment calls are based on market sentiment and news, and an AI-powered fund would be able to process these pieces of information at a much faster rate and with better precision than an analyst.  On the other hand, forming a longer-term investment thesis requires critical thinking and judgement, both of which cannot be sourced from the current AI technology.

AI Goes Back A Long Time

AI has been around for at least a decade in the investment world, but mostly in trading.  In 2007, a New York-based company called Rebellion Research launched one of the first AI investment funds.  The company’s trading system is primarily based on Bayesian machine learning and predictive algorithms that continuously evolve in response to new external information and past experiences to effectively automate learning and successfully execute equities, fixed income, commodities and foreign exchange.  Rebellion successfully predicted the 2008 stock market crash and assigned an F rating to the Greek bonds in September 2009, a month earlier than the official downgrade from Fitch when they still had an A rating.

AHL Dimension Program, the largest investment fund managed by the British alternative investment management group The Man Group, manages $5.1 billion in assets.  Approximately half of the profit from that fund was generated from artificial intelligence.  Currently, Man Group already has four funds totalling $12.3 billion in assets that incorporate artificial intelligence technology.

Fast forward ten years, four of the top 20 hedge funds are heavily reliant on algorithms trading, according to a London-based fund of funds LCH Investment.  Recently we are also seeing AI moving into the equity research realm.  Wells Fargo developed its own AI analyst which is aptly called AIERA (Artificially Intelligent Equity Research Analyst).  According to the company, AIERA’s primary responsibility is to track stocks and formulate a daily, weekly, and overall view on whether the stocks tracked will go up or down.  It works around the clock and is trained to read millions of news stories and make calls on stocks.  In October last year, AIERA made a call to sell Facebook at a time when only two other brokerages gave it a similar rating. Even Ken Sena himself, the creator of AIERA and a veteran analyst at Wells Fargo, was recommending the stock with an outperform rating.  The investment call issued by AIERA turned out to be incorrect, at least in the short run.  On another front, Morgan Stanley has also developed its own AI to churn through thousands of earnings reports and investment data such that their analysts could focus on value-added work and spend more time in front of clients.  Other players such as BlackRock and Goldman Sachs are also exploring the benefits of AI within its businesses (you can read more about them in this article What AI Means for Investors).

AI vs Humans

While we are still very far away from the mind-numbing possibility of robots taking over our jobs as equity research analysts, latest technological developments have certainly made it possible to automate some parts of our job that does not require critical thinking.  It is entirely possible that tasks such as scanning news articles, analysing financials, gathering information, manipulating data and building models can be outsourced to our robots.  AI will become a powerful analytical tool for analysts in formulating investment calls.

In the future, we will see analysts doing less of the number crunching and scouring of news and financials, but focusing more on critical thinking, formulating investment strategies, spearheading the direction of research, talking to management and industry players, and more importantly, meeting clients and stakeholders.

Like other industries prime for AI disruption, we will see more data scientists being employed by investment firms and potentially move into the front office roles.  However, these talents are far and few between, and investment firms will be competing against the likes of Google, Apple, Microsoft and IBM for these data scientists.  As a result, the next generation of equity research analysts may be expected to code and make appropriate enhancements to their company’s AI software.

Source: pixabay.com

In 2018, we will continue to see robots taking over more ‘human’ tasks, and we expect that machine learning will become even better and faster in the coming years.  However, it is unlikely that AI will ever replace humans, at least not in the SkyNet sense.  Advanced machine learning will not evolve into real AI that is capable of having the level of sophisticated thinking, common sense and self-awareness that is found in humans.  Unlike an equity research analyst, it will never be able to think outside the square, provide opinions and make judgements beyond its available dataset.

AI may transform our responsibilities and change the skillsets required for an equity research analyst, but it will never replace us.