What is factor-based investing?

Bryan: At the end of the day, as investors, what we're trying to do is appreciate our clients' money. So as active investors, what we're trying to do is create excess return above what a benchmark provides.

We like to describe everything we do as systematic and data driven. I think at the end of the day, using a quantitative factor framework really does allow us to be very systematic in what we do.

Thomas: This is Thomas O'Keefe, and I am joined in the studio today with my esteemed partner in podcasting, Phil Neuhart. And today, we've got the pleasure of having Bryan Light join us.

Phil: Yeah, Bryan is a humble fellow. He won't toot his own horn, so I will. Bryan runs our internal equity strategy. So diving deeper into the stock market is what we want to do today. And one of the great things with Bryan—really homegrown at First Citizens. You've been here a long time and done a couple different roles, but most of this time has been, of course, focused on the stock market. Why don't you tell us a little bit about your background?

Bryan: Yeah. Thanks guys for having me in. Yeah, I've been with First Citizens now for 15 years. It'll be 15 years in February, and I've worn a few hats. I started out on the strategy side, and about a decade ago, in 2015, I moved over to the equity side—first started as a research analyst, then a Junior PM, and I've been a Senior PM now for 4 years. I've been the leader of the equity group for that time.

We're a small group, but what we do is manage four quantitative equity strategies—a large-cap core, a large-cap value, a mid-cap core and a small-cap core.

Thomas: You mentioned quantitative. I know there's different types of investing out there. Can you go into a little more detail on what that means?

Bryan: Yeah, absolutely. At the end of the day, as investors, what we're trying to do is appreciate our clients' money. So as active investors, what we're trying to do is create excess return above what a benchmark provides.

There's a few ways you can do that. A lot of people are familiar with fundamental investing, where you're essentially evaluating a company's intrinsic value using discount cash flow calculators, diving deep into the balance sheets. What you're trying to do is find a company that's undervalued, or in other words, a price lower than what you think it's worth.

On the quantitative side, we're trying to accomplish the same goal, but we're coming at it a little bit differently. As factor-based investors and quantitative managers—

Thomas: Okay, wait, Bryan, stop. Factor-based—I hear that all the time. I hear managers talking about using factors. What is a factor? Can you break it down for me? What does that mean?

Bryan: So factors at their basic level are simply characteristics that help describe something. And I'm a huge baseball fan. So to draw a comparison, you can think of as a factor that anything that describes a specific player, position or team.

In the baseball world, you can get as broad as a position—shortstop—or as granular as advanced statistics, batting average, ERA, wins above replacement level if you're really diving deep. And those are really similar to style factors, such as value or growth.

At the end of the day, each level is describing a player or a team in a different way, just like an investment factor describes a security or portfolio in a different way.

Thomas: So you're collecting data. What do you do with it?

Bryan: Yeah, and I want to be clear—there are thousands of factors out there. You can describe a security or anything in an almost infinite number of ways, but really only certain ones matter in the grand scheme of things and what drive investment returns.

A tech company, for instance, is going to have, like I said, thousands of descriptors that you can use to describe the company and analyze the company, but only a certain handful of them are going to matter. In a tech company, growth, 5-year sales or revenue growth, dividend growth. These are kind of some of the examples of some of the factors that we can use for a company.

Phil: So you mentioned tech. How would you value or assign expected return to a company in a very different sector? So you've got tech. What about another company that's in utilities? How do you think about that when you're doing factor-based investing?

Bryan: Yeah, absolutely. The way we do it is we have almost 11 distinctly different models, one for each sector. There's 11 sectors that comprise the S&P 500, and each one of them is going to be driven a little bit differently to drive to provide excess return. So we look at these sector models and then kind of use a sector-scoring model on top of that to be able to differentiate between the sectors and rank them appropriately.

Phil: Okay, so you're ranking the companies within a sector based on factors, right? If we just go high level, you're saying, "Who has—what companies have the best expected return based on our factors, but by sector?" How do you end up building a portfolio with all this information?

Bryan: Yeah, that's a great question. I think there's really two sides to it. First is what we're talking about, a scoring model. This is how we differentiate Company X from Company Y and decide who we think is going to have a higher expected return over the given period.

The second way is to use a risk optimizer. So we allocate budget risk within the portfolio. Managing and allocating risk, to my mind, is equally or more important than the actual scoring model because you're really determining where you feel comfortable taking risk in the portfolio.

Thomas: So you talked about factors that matter. I interpret that as—this is a factor or a piece of data that informs my decision-making. How does that actually work?

Bryan: Yeah, so historically, there have been five rewarded factors. A lot of people have heard of these so-called rewarded factors. There's size, momentum, quality, low volatility and value. So those are the five that typically and historically have driven performance.

I'm here to say that there's actually a lot more going on that can determine performance than just those five factors. So what we're looking at—especially on a sector-by-sector basis—is ranking stocks based on what we expect the factors to drive performance over the next 12 months are.

Thomas: Got it. So you're observing data that get grouped into these five or more factors. That data then suggests—over time in all of your observations—that we can then find some predictive value of that data to what the expected return should be. Is that fair?

Bryan: Absolutely, absolutely. What we're essentially doing, and on the fundamental side, bringing that back, they're actually determining expected return. What we're trying to do is do a relative breaking of expected returns. So not saying we expect Company Y to return 35% over the next 12 or 18 months. We're simply saying we expect Company Y to outperform Company X over the next 12 years.

Thomas: Got it.

Phil: So would you say that's the big difference between quantitative?

Bryan: It's one of the big differences, and the way that we overlay an actual optimization process is another key difference.

Phil: Yeah, so let's talk about the optimization process because I'm listening to you talk and you're ranking stocks against each other. And I say, "Okay, let's just take the 10 best stocks. No matter what sector they're in, we're going have a 10-stock portfolio." How do you think about—I know you don't do that—so how do you think about risk in your optimization, and dig in a little bit on what optimization is and why we don't just buy the 10 highest ranked stocks.

Bryan: Yeah, absolutely, so there's a few things to consider here. One, obviously, if you just bought the 10 best-performing or best-ranked stocks, they might be highly concentrated in one sector or one industry. And in that case, if we are wrong about that industry or sector outperforming, you're really behind the eight ball before you even get started.

Think about it going back to baseball. If you have a team comprised only of pitchers, then quite obviously, you might luck to winning a game or two. A pitcher can hit a home run. It's happened quite a bit.

But that's one game. Over a 162-game season, you are going to underperform your teams simply because you have a highly concentrated team in one position. In the investment world, it's really no different.

Phil: And you manage to a benchmark, right? So you are not just absolute return. You're not trying to just pick the best stocks. You manage to a benchmark. How does the optimization fit into that in terms of drift versus a benchmark and risk constraints?

Bryan: Yeah, absolutely. Everything that we do is going to be kind of geared towards that benchmark. Obviously, our job is to provide excess return over that benchmark. The secondary job is to create a risk-return profile for a client that is kind of in line with that.

So we have certain constraints, we call them, on the portfolio at the security level, at the sector level, that kind of bring us in line with that benchmark more or less. Just for an example, at the sector level, if let's say technology is 30% in the S&P 500, we're going to be somewhere in a range between like 27% and 33% percent—so plus or minus 3% at the sector level.

Phil: Right, so you wouldn't just say we're avoiding a sector completely because we're cognizant of that benchmark and not moving too far outside of it from a risk framework.

Bryan: Absolutely. And the old saying is, know what you don't know. We think we have a pretty darn good scoring model and system, but there are absolutely periods of time where our best thinking about what's going to happen in the market is not going to happen. If you do not have exposure to those sectors, then you are going to be behind the eight ball quite a bit.

Thomas: Yeah, this great, Bryan. So I think if we want to take that 10,000-foot view here, it sounds like we are running—you are running—a quantitative strategy, right, not a fundamental strategy. And within a quantitative strategy, you're using factors in order to inform a ranking of securities that you then use in a portfolio construction and risk management process to build a portfolio to hopefully beat a benchmark. Did I do a good job of summarizing that?

Bryan: That's absolutely perfect. We use factors from beginning to end here, not only in the portfolio construction, the scoring model and the risk optimizer, but also how we talk about our portfolios.

When we look back on performance, we are easily able to see where we won and where we lost, why we won and where we lost, where the risk concentrations were that caused performance from one company or sector. So it's a really intuitive way to not only manage portfolios but to actually talk about them to people.

Thomas: Now are you changing in your process the weight that you have for particular factors, or is it more that the data is changing the sensitivity of those factors to your returns?

Bryan: It's going to be more on the data side now. Over the long term, we have made adjustments to our factor loads, factor weightings, but those are going to be more long term in nature. Think about an equity screen for a typical fundamental manager. If that screen is changing every 2 weeks, then that's probably not a very consistent fundamental equity measure.

Phil: Not a good sign, right?

Bryan: Exactly. So we look at it really the same way. As time passes, obviously the benchmark S&P 500 today looks nothing like it did in 2000 when energy was a top sector. Now energy is one of the smaller sectors and information technology is over 30%. So things do change over time, but we're not looking at changing those models on a weekly or even monthly or quarterly basis.

Thomas: Got it. So hopefully everyone is coming away with a factor is a set of data that is helping you and your team understand the expected return of a particular asset.

Bryan: Yeah, it informs our expectations of a given company but also is used to diversify our portfolio and to make sure that we understand where our risk is coming from.

Phil: And I think of this way of investing as important. Look, there's so many ways of investing that work. It's not that one is better than another, but one thing I like about quantitative investing is you're removing that human overlay of, "Well, yeah, I read that headline yesterday. So now I'm not sure I want buy this sector." Right? When, of course sometimes that matters, but often all that is an entry point. Is that fair to say?

Bryan: Absolutely. One of the biggest things that we try to avoid is having our personal views and decisions come into our equity management process. We are letting the data inform us of the decisions. We're letting the data allocate where our risk is coming from. Now, are we keenly aware at all times of where it's coming from? Absolutely. But the data is driving us to those positions.

Thomas: Yeah, so it might actually, Phil, for a future podcast, it would be really fun to have a point-counterpoint with somebody on the fundamental side of this because to your point, I bet the argument on that side of the house would be, "Well, we look at management teams, and we look at supply chains and we look at brand power." These are things that you likely don't look at, is that correct?

Bryan: That's correct.

Phil: And the truth is—as your track record shows—I mean both of these strategies can work, right? That's the truth. And different approaches I like in terms of thinking about broad portfolio construction.

Thomas: Yeah, but as we all know, you can fall into the trap of "I met the management team, I really like them, therefore I'm going to value them higher."

Phil: That's right, whereas Bryan might be seeing underneath-the-hood data characteristics that are good or bad.

Bryan: Yeah, I think I would leave with this. You know, we like to describe everything we do as systematic and data-driven. I think at the end of the day, using a quantitative factor framework really does allow us to be very systematic in what we do.

Thomas: And we're trying to take that emotion out. I mean, this is for professional investors and for amateur investors. You and your team are trying to take that out of it.

Bryan: Yeah, absolutely, absolutely.

Thomas: Bryan, this is a pleasure to have you here. Like Phil said, your track record is incredible. Your process is thorough. Couldn't be more pleased to have you on here today and talk through all of the complexities of quantitative investing and factors. And hopefully our audience came away with this with a deeper understanding of what your team does but also just what quantitative and factor investing is. Hopefully we'll have you back soon.

Bryan: Yeah, thank you guys. It's been a pleasure.

Disclosures

The views expressed are solely those of the authors and do not necessarily reflect the views of First Citizens Bank & Trust Company or any of its affiliates. This material is for informational purposes only and is not intended to be an offer, recommendation or solicitation to purchase or sell a specific investment strategy, any security or insurance product and should not be construed as legal, tax or accounting advice. Please consult with your legal or tax advisor regarding the particular facts and circumstances of your situation prior to making any financial decision. While we believe that the information presented is from reliable sources, we do not represent, warrant or guarantee that it is accurate or complete.

Many companies referenced in this content are independent third parties and are not affiliated with First Citizens Bank & Trust Company. All third-party trademarks, including logos, trade names, service marks and icons referenced remain the property of their respective owners.

Your investments in securities and insurance products and services are not insured by the FDIC or any other federal government agency and may lose value.  They are not deposits or other obligations of, or guaranteed by any bank or bank affiliate and are subject to investment risks, including possible loss of the principal amounts invested. Past performance is no guarantee of future results. Estimates of future performance are based on assumptions that may not be realized. This material is not a solicitation of any offer to buy or sell any security or other financial instrument or to participate in any trading strategy. Diversification does not guarantee a profit or protect against loss in a declining financial market.

First Citizens Wealth™ (FCW) is a marketing brand of First Citizens BancShares, Inc., a bank holding company. The following affiliates of First Citizens BancShares are the entities through which FCW products are offered. Brokerage products and services are offered through First Citizens Investor Services, Inc. ("FCIS"), a registered broker-dealer, Member FINRA and SIPC. Advisory services are offered through FCIS, First Citizens Asset Management, Inc. and SVB Wealth LLC, all SEC-registered investment advisors. Certain brokerage and advisory products and services may not be available from all investment professionals, in all jurisdictions or to all investors. Insurance products and insurance are offered through FCIS, a licensed insurance agency. Banking, lending, trust products and services, and certain insurance products and services are offered by First-Citizens Bank & Trust Company, Member FDIC, and an Equal Housing Lender, and SVB, a division of First-Citizens Bank & Trust Company. icon: sys-ehl

For more information about FCIS, FCAM, or SVBW and its investment professionals, visit www.FirstCitizens.com/Wealth/Disclosures.