Chris Natividad is CIO and Co-Founder of EquBot. Mr. Natividad brings more than 15 years of experience in the institutional investment management industry.
Previously, he was an Investment Portfolio Manager for Gilead Sciences and Apple Inc.’s Braeburn Capital and was responsible for managing multi-billion-dollar onshore and offshore investment portfolios.
Mr. Natividad’s previous experience also includes investment management and analysis across a variety of asset classes for several financial service firms including Goldman Sachs and Franklin Templeton. He holds an MBA, B.S. and B.A. from UC Berkeley.
In this 3,367 word interview, Mr. Natividad describes the AI based mutual fund powered by IBM’s Watson that he and his colleagues have created.
“AIEQ is the ticker, and it is the first AI-powered equity ETF. It was done in collaboration with IBM Watson and ETFMG. It is combining the growing amount of structured and unstructured investment data.
Working around the clock, the system analyzes over 5,000 U.S. companies to determine a set of securities it will invest actively in each day.
To take a step back one second, our partners at IBM say 90% of the world’s data was created in the past two years. At EquBot, we believe we are going to be saying this every two years from now.
The data is absolutely growing from a volume perspective. The variety, veracity, and velocity of the data is causing this boom. Our mission at EquBot is to transform data into better investment outcomes with artificial intelligence.
We saw that, looking at the data, there has been a tremendous movement towards ETFs. Investors want more transparency and liquidity.
So, we decided to launch AIEQ, the ETFMG AI Powered Equity ETF, just over three years ago, and it has done quite well. It has outperformed its benchmark.
From our system perspective, we continue to see it learn and grow from every single trade.
The way we tend to characterize our operating system is it’s like an army of research analysts, traders and quants working around the clock to help figure out what we should be investing in and when we should be investing in it.”
The AI stock picking incorporates the global data flow:
“When we think about AI in the highest sense, it is about using a technology to replicate human behavior, so to speak. In our instance, the system is autonomously managing a portfolio for AIEQ that is looking at the thousands of U.S. publicly traded companies and creating a portfolio.
To do that, we can take a look at the traditional asset manager framework. We ingest millions of news articles, market signals, things from pricing to volume data daily, and we utilize an ensembled architecture. That’s important for us because we need to have observability into what we are investing in, and why we are investing in it…
To do this, we utilize IBM Watson’s natural language processing as it’s one of the top in this field.
Most people know IBM Watson through beating Deep Blue in chess or beating the “Jeopardy” champions. The reality is, it’s not just the English language. We are processing dozens of different languages.
The analogy I like to provide is: All of these different investment data points is similar to a single pixel.
A decade ago, right, when we’d have video conference calls or something, or even images online, they’d be quite granulated. Sometimes you’d kind of scratch your head and say, what am I really looking at here? Well, fast forward to today, we have high definition and pictures with increasing amounts of detail and speed.
That is the analogy I connect with using our system. We are connecting and adding more pieces of the puzzle to understand what that market picture is and where it is headed.
For AIEQ, we are benchmarked against the broad U.S. market. Retail investors like to compare it to the S&P 500.
Year to date, it has done quite well. We are in the top two percentile. When we look at the one-year time period as of this past Monday…we were outperforming the S&P 500 by north of 20%.
But again, it’s not like the system we just turned it on and said, OK, what do we invest in? It needs to grow over time. What’s increasingly compelling and what we like to talk with many of our institutional investors and institutional clients about is the excess return each year.
The first year we slightly underperformed. The second year, we beat our benchmark. Going to third year, that spread continues to improve.”
The AI stock picking is continually evaluating and re-evaluating the data for appropriate equities to own:
“To provide some context, a quite interesting time for fun was the beginning of the pandemic. We would actually be ingesting information related to coronavirus and the COVID pandemic back in December of 2019. But, if we think about artificial intelligence, at the highest level, it is pattern recognition.
The system at the time was diversifying into consumer staples, so names like Costco (NASDAQ:COST), Walmart (NYSE:WMT), and getting active and increasing exposures into a variety of the different pharmaceutical names that we’re approaching like Gilead (NASDAQ:GILD), Moderna (NASDAQ:MRNA) and Johnson & Johnson (NYSE:JNJ).
These are names with strong balance sheets and they had performed quite well during historically volatile periods.
Now, it didn’t get it 100% correct because the magnitude had never been experienced, meaning the system had never seen something as drastic as the coronavirus. We had only had SARS and MERS, with muted market downturn. Again, the lesson or the magnitude associated with these types of downturns now becomes part of the system and part of that pattern recognition that we’re going through.
We take a deeper dive into the system and we can see that it is scouring clinicaltrials.gov and then, I believe, in March we saw that it was looking at north of 3,000 different clinical trials associated with COVID vaccines, testing and treatment.
There was a selecting of some of the different names with positive sentiment and positive business operating structures to become part of the portfolio in addition to the technology and some of those stable value names.”
To get the complete interview on this AI stock picking innovator, read the entire 3,367 word interview exclusively in the Wall Street Transcript.
CIO & Co-Founder