International financial markets operate at lightning speed and are continually being updated in real time with enormous quantities of global data. In this fast-paced environment, trying to stay ahead of the investing curve can be a daunting task.
Bobby Barnes, an engineer- turned-quantitative analyst with Fidelity Investments in Boston, answers questions about the industry and his enthusiasm for quantitative investing as an effective strategy in challenging times.
Q: What is quantitative investing?
Quantitative investing, also known as factor investing, is not new. Simply put, a factor is a characteristic that investors have always applied to understand a company’s stock value, such as the size of that company, its market capitalization, the strength of its brand value, and whether it has high or low profitability.
Every portfolio manager here has a stated investment philosophy they apply to the stocks they’re most attracted to, and ultimately decide they would like to buy. So we’ve always been doing factor investing. What’s new is that we’ve given the activity of looking for these characteristics an explicit name.
What is your role as a quantitative investment analyst?
It’s to support our broader investment organization. I do that by building stock selection models that help provide buy and sell ideas for our portfolio managers.
‘These are exciting times in factor investing’, says Fidelity Investments quantitative analyst Bobby Barnes.
I also give the managers guidance to help them identify how to best structure their portfolio so they’re capturing as much of the upside as possible, but also minimizing any inherent risk.
For example, some of the managers I work with ask me to help them identify stocks that will satisfy certain selection criteria they have and that will also give their portfolio downside protection to mitigate against the possibility of negative returns.
Starting with that objective, I’m able to then seek out the characteristics to help identify those stocks that will protect downside. My team and I also build solutions for the end shareholder. Depending on what that shareholder is looking for, that will dictate the source of the characteristics or factors that go into their solution.
How can investors benefit from such a strategy?
Every client has a different investment outcome that they’re trying to solve. Take an investor nearing retirement: I would use quantitative investing to prioritize having a portfolio with some downside protection. I would create a portfolio with a lot of exposure to high dividend stocks that ideally would be from quality companies that are very profitable with high margins – because those stocks tend to be more stable, and do well even when the economic environment is receding.
As a retiree, they will get the benefit of receiving that dividend income. They will also have a portfolio that won’t necessarily go down as much as the broader market when the market goes through difficult times during the various economic cycles.
What attracted you to this area of investing?
I began my career as an electrical engineer, where my first job was at a large telecommunications company developing cell phones. When I started working, I had savings to invest, so I began to dabble in the stock market. It became a hobby of mine and along the way, that hobby grew. I learned that a lot of the skills I had as an engineer were applicable to the financial markets in the quantitative analyst capacity. So I went back to school and got my MBA as a way of providing an entrance into this space.
What I really love about the stock market is that every day there’s a different problem to solve. I find it really invigorating waking up and looking at the stock market, and trying to figure out “what’s driving the market today? What’s the best way for me to create models that will identify those stocks that will perform the best over time?” That’s a very exciting process for me.
From your experience, how much of the quantitative analysis decision is based on computer-based models versus human intuition?
When I first got into this business 10 years ago, my boss at the time told me all quantitative models should begin by asking the question, “What is the economic rationale for why this should work?”
One hundred per cent of this process will start from intuition. The reason that is important as a starting point is because it helps you avoid creating models that simply fit a hypothesis based on the past. It also helps you to avoid investing in relationships that are spurious and, moving forward, are not necessarily likely to hold true.
The computer-based model is the second step to validate that intuition. There are circumstances where we as investors think that something should work, but then we look at the historical data and see that perhaps it doesn’t. And so it cuts both ways.
Give an example of how you would use a combination of human intuition and a computer-based model to serve a client using quantitative analysis.
Let’s take a hypothetical investor with a preference for a portfolio of stocks that have stability. I would start with my intuition that companies that are highly profitable tend to have stock prices that are more stable, and would look for companies with high profit. Then I would build a computer model to identify the past performance of those companies’ stocks, and study how those stocks performed moving forward through various economic cycles. I would examine questions such as, “Did these high corporate profits allow their stock prices to be less volatile during recessions or economic downturns?”
What current trends are shaping the quantitative industry?
These are exciting times in factor investing. Fidelity recently launched six new exchange traded funds (ETF) covering Canada, the U.S., and international markets. Through these new funds, quantitative investing allows everyday investors to get access to some of the same insights that our portfolio managers have been using for years. I think of it as a way of democratizing access to these building blocks that do a great job of helping investors achieve whatever their investment outcomes are.
Take the U.S. as an example. We launched two dividend ETFs for Canada that invest in U.S. stocks. The underlying indices that those products are tracking are the customized indices we built internally. The calculation that went into those indices leverages on the investment insights that we have been using for many years to select a sub-set of stocks within the U.S. market that are most attractive for our own funds. Another trend in factor investing that I’m most excited about is looking at how we can use computers to come up with better insights into stock picking, [using tools such as] artificial intelligence or big data. There’s a lot of growth in those areas, and it’s very exciting to explore those.
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