Introduction to MFS Blended Research®: Combining Fundamental and Quantitative Insights

Josh Barton:

Jeff, to start us off, can you introduce the Blended Research capability for us?

Jeff Morrison:

Yeah, sure. The Blended Research capability at MFS started around 2000. And what it does essentially is it systematically combines our proprietary fundamental research with our proprietary quantitative research, and then builds portfolios from those two signals in a very quantitative manner.

Josh Barton:

So that combination of quant-fundamental in a single strategy is relatively unique, I would argue, and particularly so the way that we do it. What's the benefit of having those two disciplines combined in a single strategy?

[CARD]: "What are the benefits of combining fundamental and quantitative research in a single strategy?"

Jeff Morrison:

Yeah, so the key benefits are you getting the complementary attributes of each type of research. And so if you think about quantitative, quantitative is very disciplined, very structured, unbiased. And most importantly, it gives you an opinion on every stock in the investable universe you're looking at.

You contrast that with the fundamental side. Fundamental analysts do a great job of going deep on companies, they are typically meeting with management teams, doing site visits, and modeling out their companies on a three to five year basis. The one thing with that is they're not able to cover every company in the universe, so that's where you get a little bit of it from the quant.

Another benefit of the fundamental side is that they're very forward-looking. So if you think about what's happening in the macroeconomy or you think what's happening with maybe an M&A situation with a company, the analysts are very quickly able to adapt to that and think forward as to how this is going to impact my company. And they will adjust their models and adjust their opinion on the stock based on that forward-looking assessment. And so you get that forward-looking assessment from the fundamental team, a more consistent, disciplined, backward-looking approach from the quantitative side, and then you get that complementary benefit by combining them together.

Josh Barton:

In what sort of environment would you expect the Blended Research strategies to perform? And conversely, when might they struggle?

[CARD]: "In what environments do the MFS Blended Research® strategies perform well, and when might they struggle?"

Jeff Morrison:

Yeah, so we've really designed the process to be multidimensional in the sense that we want to have something in the process working at every phase of, say, a business cycle. If we think about how we've designed the models, on the quant side, we have valuation, momentum, quality, and sentiment. And then we couple that with our longer term focus quality component from our fundamental team.

And when you think about a business cycle, you think about the early part of the business cycle, that's where you're coming at a recession or out of a bear market, and you typically get that description as being a junk rally. But what we find is our quantitative models capture that very well with the value and momentum component that we have in the models. As you move into the mid-part of the business cycle, that's where the recovery becomes more entrenched and the emphasis shifts to earnings and momentum. And that, again, is captured very well in our quantitative models.

Then you get into the late part of the business cycle. That's typically where central banks are raising rates. The economy is growing well, but it's starting to slow. And what the investors tend to focus on then is durability and sustainability of earnings, margin protection, quality of the balance sheet, et cetera. And those are things that are captured best by the quality components of our quantitative models, as well as our fundamental team. And so we think that as we go through a full business cycle, that the process should allow us to produce consistent performance through that period with different drivers from the process.

Josh Barton:

MFS is probably more well known for its fundamental research. Can you talk a little bit about the quant research process as it relates to Blended Research and talk about some of the differentiating factors of that quant approach?

[CARD]: "Can you explain the quantitative research process in the context of MFS Blended Research®?"

Jeff Morrison:

Yeah, sure. The quantitative, if you think about it, we're using at the end of the day street research. We're not utilizing our proprietary research for the inputs to the data, so it's all data inputs. And the models are, well, not as long-term as our fundamental signal. They still are pretty long-term, so they tend to have a duration of 12 to 18 months, which is typically a little longer than your usual quant model.

And so we've designed it to have factors that really are focused on valuation factors, so trying to understand what that company's worth. So we're looking at multiples like PE, price to cash flow, price to sales, et cetera. And we couple that with some other more momentum factors like earnings momentum that measures earnings revisions from analysts. They look at companies and they're either revising up their numbers or down their numbers. We're capturing those types of insights.

And then price momentum, which is a little bit more of a technical factor, but it's really looking at the historical relationship between stocks that have done well historically in the past year or past six months, that performance historically has tended to carry on and perform better for the next year. And so higher price momentum stocks, we try to look for those as well.

And then finally in the quality emphasis, we built our quality model around three different components. We're looking at balance sheet quality, we're looking at business profitabilities with factors such as margins. And then we're also looking at earnings quality. We look at that through accruals and what is the quality of those earnings that those companies are reporting.

Josh Barton:

So I guess if you think about dedicated quant strategies as a differentiator, they're more focused on or incentivized to really find those shorter term signals because they don't have that fundamental component to their process.

[CARD]: "How does the combination of fundamental and quantitative signals differentiate MFS Blended Research® from dedicated quant strategies?"

Jeff Morrison:

That's exactly right. And so this is the thing with our models, is that we're trying to match those quantitative signals up with a longer term focused fundamental signal. And so we've identified many factors that work with a one-week duration or a one-month duration, but those really don't fit into our modeling structure because we want something that's going to really match up well with the fundamental signal. And so that really has lifted the bar pretty high for getting factors into our model that have that longer duration signal.

Josh Barton:

Yeah. And obviously that reduces turnover as well.

Jeff Morrison:

Exactly, exactly. The turnover of our portfolios are typically higher than a fundamental portfolio, but much lower than your typical quantitative portfolio.

Josh Barton:

Sure. How long have the Blended Research strategies been running for and what's the AUM across the suite of capabilities?

[CARD]: "How long has the MFS Blended Research® strategy been running, and what is the AUM across its capabilities?"

Jeff Morrison:

Sure. We started the Blended Research portfolios back around 2000, and we started with a US core strategy, which still exists today. And over the years we've built out our capabilities to incorporate style-based portfolios in the US, size-based portfolios, so we have a mid-cap and a small-cap strategy in the US. And then as we got into the late part of '09, into 2010, we started to develop global models. And as a result of that, we've built an international suite of portfolios, such as our international model, our global portfolio, as well as our emerging market strategy.

All told, we have close to 18 distinct strategies that encompasses about $20 billion in assets under management, and that's split between what we call our targeted tracking error portfolios, which is about 60% of that 20 billion. And we have some more outcome-oriented portfolios that utilize the same investment process with different portfolio construction dynamics that focus on volatility, so low volatility suite of portfolios, as well as incomes. We have an equity income suite of portfolios as well.

Josh Barton:

You talked about the fact that there's a systematic portfolio construction process. Obviously one outcome of that is that we're able to tailor these products for specific client demands. Can you talk a little bit about that, and what are some of the recent examples that you could give us around some of the tailoring we've done to meet client requirements?

[CARD]: "How does the systematic portfolio construction process allow for client-specific customization?"

Jeff Morrison:

Sure. Yeah. We have a lot of requests from clients to come in with unique situations, unique needs that they may have. And so we're able to customize based on tracking errors. We have clients that want lower tracking errors. Then we have other clients who want some type of customization around ESG factors for instance, or ESG indexes. We can customize to that. We look at exclusion lists. We'll take stocks out of our universe and manage the portfolio based on that universe. We also look at different benchmarks, and so whether it be a regional benchmark or a more specialized benchmark, we have that capability as well. So it's a very flexible portfolio construction approach that allows us to customize to pretty much any need a client has.

 

 

The views expressed here are those of the speakers. These views do not necessarily reflect the views of MFS or others in the MFS organisation. No forecasts can be guaranteed.

 

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