MASTERCLASS: Factor Based Investing - November 2017

For several decades, factor-based investing has been the preferred method of using attributes to choose securities and to build a more efficient portfolio. Factor-based investing has recently taken the industry by storm, and investors are still hungry to learn more strategies. How have factors performed this year, why is it difficult to time factors and is smart beta synonymous with factor investing? In this edition of MASTERCLASS, four financial experts discuss new developments within factor investing, and the best strategies to perform due diligence on factor-based models.

  • Gregg Fisher — Founder & Head of Quantitative Research & Portfolio Strategy at Gerstein Fisher
  • Darby Nielson — Managing Director of Quantitative Research at Fidelity
  • Arne Noack — Director of ETF Products at Deutsche Asset Management
  • Ryan Shelby — Head of Factor Solutions at Analytic Investors

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  • 56 mins 31 secs

MASTERCLASS: Factor Based Investing - November 2017 Gillian: Welcome to Asset TV, I’m Gillian Kemmerer. Factor Based investing has attracted a lot of attention lately. But how exactly do these strategies operate? As cash flows to smart beta products and new factors are developed, keeping up with the changes in this unique space can be challenging. Today Asset TV has assembled a panel of experts to answer your questions and discuss the latest innovations. Welcome to the Factor Based Masterclass. Thank you all so much for joining us. So, Ryan, I know this is going to sound like a basic introduction, but for anyone at home that’s considering these strategies, and perhaps hasn’t allocated before, can you just give us a quick overview of what a factor is? Ryan Shelby: Yeah, actually that’s a great question. And, you know, factors I think have been getting a lot of attention recently. You know, you hear this term factor based investing, smart beta, strategic beta. Ultimately it’s taking advantage of some characteristics in the market that we’ve found over decades of academic research to actually impact risk and return of securities. It’s much like, if you’re familiar with a Zillow or an online real estate appraisal company, as you look at Zillow, they have a value of every single house in New York or Los Angeles or wherever you are. They don’t actually visit those houses, right, they actually use a common set of characteristics, how many bedrooms, how many bathrooms, the square footage of the lot, to actually value those houses. We can do the same thing with a security. What’s the price to earnings? What’s the price to book? What’s the ROI? And those characteristics can actually help us determine the risk and return characteristics of stocks. Gillian: Arne, talk to us a little bit about, you know, this is a great overview, thank you, correlation and how that plays into factors. When we look at a crisis scenario for example, a lot of different asset classes become correlated that aren’t normally. Arne Noack: So correlations are actually quite important when it comes to factor based investing because the different factors that exist often are negatively correlated. So for example, a very commonly sort of used example in this case is the factor of size. So smaller size investing, and low volatility investing, those two factors, one size is a more pro cyclical factor, low volatility is a more defensive kind of factor. And typically the correlation in terms of the excess return or outperformance generation of each tends to offset each other somewhat. That means as soon as you sort of combine multiple of those factors you actually are able to harness certain de-correlation or diversification benefits in your equity portfolio and gain a potential for outperformance in different economic cycles. Gillian: Excellent. Now, Darby, when you think about factors, what are sort of … is there a basic set of them that have been operating for a long time? Would you say that there’s been an influx of many new ones or are we all still operating on those same basic few? Darby Nielson: I think many investors still operate with the same basic few. A lot of quantitative investors do. I mean, but I also think it depends on what you’re trying to achieve with your factor investing objective. But yeah, there’s some bread and butter factors that, you know, I’ve been a quant for 15 years now, there’s some that I know and love like value, momentum and quality. Those are some very basic ones that over time have added excess return. Another factor could be dividend yield, right. But I think there the outcome that investors would like is income in their portfolios. And then others like low volatility, I think are a little different, may not be generating alpha or excess return over time, although we could debate that probably. But low vol is a different one that I think is a little better in a portfolio construction framework, to lower the volatility of a portfolio. So those are some of the basics. But I do think that, you know, over time I mean we’ve seen the original beta which is just the market, evolve into those that I talked about. And you know, for the last several decades academics as Ryan said, but plus quantitative practitioners have been discovering a lot of different factors over time. So there are a lot of others that we know about. But those are some of the basics that we as quants know and love that are very useful in an investment process. Gillian: Perfect. And, Gregg, we’ve covered a lot of ground, but I’m curious to know if you find that investors have become more educated on this space? Or do you find that you’re still making the basic definitions and case to them? Gregg Fisher: Yeah, it’s an interesting question. I think, you know, Gerstein Fisher, we’ve been, you know, using factor based investing for 25 years now. And I can’t believe that we’re actually doing a panel on multifactor investing. I remember back in the 90s talking to marketing people about multifactor and it was like what is that. And now here we are. So it’s interesting. But I do think as an industry we are still educating people about this concept of factor investing, these characteristics that seem to do a good job describing risk and return across securities. And I think we’re talking about factors, I think there’s something of about 400 of them that have now been researched. And I would agree that there’s probably 5 or 6 that many of us are all using that are like the Holy Grail of these things. But I think when it comes to factor investing it’ll be a journey that’s never ended. There is still research that can be done and much of it is getting done as we speak. And new factors are seemingly coming out. I think the job for portfolio managers, practitioners, and researchers is to figure out which of these things make sense. And to the point mentioned earlier, how do you combine these things into a smart portfolio in the presence of trading costs? Gillian: Now, you make an interesting point, you’ve been doing factor investing for 25 years. And if there’s something that I heard across the board in every phone conversation I had with each one of you in the lead up it was that why are we talking about it, always it seems the news, is like it’s this new thing that’s suddenly on the scene when in fact it’s been around for a while. So, Arne, maybe you can kick us off and just give us a little bit of an overview on the evolution of factor investing. Arne Noack: Sure. And we could fill the full hour with just that one question and I’ll keep it relatively short. Ultimately the way personally I or we at Deutsche Asset Management like to look at factors is that it’s not really anything mystical. It’s relatively simple and it just requires a little bit of thought around sort of what are we actually trying to accomplish. A lot of factor based investing is actually something that has been done in the active management space for decades. And ultimately why those types of strategies are now gaining popularity is that what I would refer to as the rise of indexing. And the ability with increased data amounts and increased processing ability of that data to actually incorporate factor based investing, factor based stock picking, factor based stock selection in the form of indices. And ultimately what we’ve seen is sort of in the early 2000s and then in particular from 2010 onwards in the international institutional space a drive to analyze the fundamental return drivers of actively managed portfolios. And the outcome of a lot of that analysis was that a lot of managers are not only index huggers as is commonly known but also factor huggers, meaning let’s say a small cap value investor didn’t necessarily add value above and beyond the two factors of size and value. And therefore as soon as that type of analysis was known in the institutional space there was a push towards possibility and potential for cost reduction. And that cost reduction happens typically in the form of indexing. So as soon as you see that your manager is only systematically harnessing a certain risk premium or a certain factor you then immediately think, well, hang on a minute, if we can quantify that investment process and wrap it in the form of an index that index becomes and can be followed passively. And as we all know, passive investment management tends to be cheaper than active management, hence, sort of have a whole new potential of cost saving for my portfolio. And ultimately that sort of then came from the more institutional side. We saw some sovereign wealth funds in particular in the Nordics in Europe and moving into that space very, very early and since then we’ve seen what we think is sort of inevitable, that kind of tendency spreading throughout the more retail world as well. Gillian: That’s an interesting point. You kind of marked that watershed moment as the rise of the indices. That was still about 16, 15 years ago. So even though that’s relatively new, it’s not even. So it’s not something that’s very well saturated in the marketplace. Gregg Fisher: You know, something I would perhaps add to that, just expand on that point. I think what’s new about factor investing is transparency. It’s this idea that we’re now all talking about things in a transparent way that, you know, before was probably some black box. And in fact, you know, we’re sharing this in a different way and it’s also benefitting the end consumers, the investors out there through lower costs for them. And I think that’s a good thing. One of our academic partners, a guy named Professor Sheridan Titman, who’s a professor at University of Texas, he’s probably best known for his pioneering research in the late 80s on one of the sort of the big factors, momentum. Which is one of those ones that seems persistent across almost all countries, big premium for doing it. And he found it for the following reason as he described, what he was doing back in the 80s was he was researching great performing money managers. And he was trying to identify what were some of the things that these great performing money managers were doing to cause the great performance. And him and one of his research colleagues found that one of the things they were doing is they were buying past winners. And you know, having a little less exposure to past losers. And that simple naïve strategy of just doing that was what became the momentum premium. But it came as a result of trying to find out how active managers were in fact earning great returns. And can we create a quantitative process to duplicate that and sort of share the instruction manual with everyone. And there, that came to the now current momentum factor. Gillian: And this is an interesting point because Darby, traditionally, Fidelity has been an active manager shop. So how have you seen the use of factors evolve? Darby Nielson: Yeah. We are traditionally thought of as a fundamental active shop. We have a long history in that area. We’ve actually had some extraordinarily successful investors. And I’d say we’re still quite good at that. But Fidelity has actually been doing quantitative analysis for decades. We actually hired our first quant analyst in 1965, which I discovered from looking in the Fidelity archives a couple of years ago. I was excited. His job was actually to determine applications for the computer in the investment process. And computer singular because we just had one computer back then. And we’ve also been integrating factors in the investment process for years. You know, as the Head of Quantitative Research at Fidelity in the Equity Division, our mission is to provide factor based insights to our portfolio managers. And we do that using factor models to either generate investment ideas or monitor risk. We do both of those things with our factor models. But we do that with a team of 20 quants. And they’re integrated into the investment process. So the team of quants that work for me, they actually are part of the small cap team or the value team or the emerging markets team, working with the fundamental investors to provide factor based insights. And over time, working with all of them we’ve built a factor library of over 3,000 factors, dozens of different models. You’ve talked about hundreds of factors. We have thousands of factors. And all of those models we’ve built in conjunction with our fundamental colleagues. So I do think that that’s something that makes our factor products a little different, because all the decisions we made in designing those was based on our fundamental colleagues and our interactions with them. And so yeah, factors are definitely part of the active investment process at Fidelity. We’ve been doing it for many, many years. It’s an integrated process. And I think it’s what informed a lot of the decisions we made in the factor products that we’ve designed. Gillian: And then, Ryan, I want to pull you into this conversation. How have you seen the factor investing sphere evolve since you’ve been in it? Ryan Shelby: Yeah. I mean I think if you look back 80/90 years ago, you know, throughout the academic research you see, you know, very simple measures of factors, right. The tendency for cheaper stocks to outperform, right, we noticed that in 1930s. Momentum is one of those things. I was laughing at your story because Analytic found a similar way into factor based investing in the 90s as well. We were looking at active managers and the drivers of those returns and actually built a quantitative process to actually build it ourselves. So the exact same way we got in this space. But, you know, I think what we’ve seen over the years is a move away from, you know, when I hear 3,000 factors, let’s be clear what we’re talking about. Those are characteristics, right, because the difference between a factor and a characteristic to me, a factor needs to have some sort of risk premia associated with it, some sort of behavioral bias, some sort of structural impediment associated with it. So when we talk about value or quality or something like that, you know, your definition of quality might be cash flow to price, mine might be book to price, right. So as we actually look at that we’re trying to play the behavioral bias behind value. People ignore old boring value companies. There’s a risk premia associated with value companies. So when we look at it from that framework there might be 10, 20, 30, 100 characteristics that define value, but the thing you’re actually capturing is that value anomaly, not the cash flow to price anomaly, not the price to book anomaly. Gregg Fisher: That’s so important. I think what’s important about that, as you described it is we may all define these factors a little different. But price being in either the numerator or denominator is a critical factor. Darby Nielson: That makes it value. Gregg Fisher: Yeah, right, because there’s so much information in the price, you know, maybe picking up a little bit on the market efficiency story, but you know, I think many of us use price in a lot of the equations. It saves a lot of time when you don’t question the price. The whole idea or a big part of the idea, factor investing is this idea that on average markets do a good job, not a perfect job, but a good job pricing risk. So if you start with the market price and you assume the market’s done a good job on average pricing risk then you just as an investor or portfolio manager have to decide what risks do you want to own? But using price in the equation I think is a critical component. Darby Nielson: Yeah, I think threading the needle here, between what we’re all…we’re all kind of saying the same thing, whether it’s hundreds or thousands of factors, I agree, they all kind of fit in these themes of factors, which is I think what you mentioned a moment ago, whether it’s value or quality, momentum, there’s a lot of different characteristics you can use to define those. But I think we’re all kind of saying the same thing. And I completely agree, I learned that years ago, any time you divide anything by P, it’s value. Gregg Fisher: Right. Gillian: Arne, I’m curious, we’ve alluded to it a few times, I think Ryan kind of kicked us off. But what really drives a factor premium? And are you worried about the influx of cash maybe driving them down or taking them away? Arne Noack: Well, the point of sort of your second question is very, very hard to estimate. And in particular sort of if we look at what we said for an earlier question that this type of investing has been around for decades, it’s hard to estimate sort of how much money is really allocated to each individual factor via active managers that may allocate cash in a non-transparent way. And overall what we would say is it’s important to have a view on the persistency and the sustainability of a certain factor. And I think, hence, conversations and panels such as this one are very important to highlight in the consciousness of investors that not everything that might be marketed these days as a factor is really associated with a risk premium. And really associated with a potential for either risk reduction for a portfolio or an excess return and positive excess return, so to your first question, what really makes up a factor is, yes, the characteristics. But alongside those characteristics has to be an improved risk return profile when you implement a certain investment strategy in accordance with that characteristic, that’s how I would put it. Gillian: And it sounds like something that has to be consistently evaluated to make sure that it’s continuing to generate that in order for it to be worthwhile. Arne Noack: Exactly. And as part of this evaluation what is obviously critical is the resonance and the backing by the academic community who scrutinize practitioners and also of course the investment community on an ongoing basis that there is a sound rationale and a statistical significance that supports factor investing. Ryan Shelby: Yeah, there’s something really important there as well. When you’re actually looking at a factor you need to define it properly. But you also need to purify the ancillary factor exposures, right. So if you buy a stock that’s a great value but it’s got really poor momentum and it underperforms, was it the value component or the momentum component? Right, if you’re buying a high quality stock but it’s really expensive, what are you actually buying? And so you know, I think, you know, kind of getting back to the older way versus maybe a newer way are the enhancements that have been made, you know, with the advent of computing power, with more research being put into this space,. I think that factor purity thing, at least for analytic investors has really been a differentiator, looking at how do we purify a portfolio of ancillary exposures, things like interest rate sensitivity, you know, when you buy a momentum stock it’s quite volatile. How do you actually scale the position based on that volatility? You know, these are all things that I think are very good for the industry as we push forward in this space. Darby Nielson: Yeah, we’re a big believer in that as well. Just with our products providing targeted exposure to the factor that you want, trying to reduce, whether it’s sector risks or small cap effect, ‘cause that’s very common actually when you buy a factor product and you see excess return, it could just be a small cap effect. We try to control for that kind of thing to again, provide targeted factor exposure reducing unintended risks. Ryan Shelby: And you see it in these multifactor approaches as well, you buy a value portfolio, you buy a quality portfolio, you buy a small cap portfolio. And then a portfolio manager bolts those things together, so they’ve got four exposures. But when your value portfolio actually has poor quality and your quality portfolio has kind of, you know, expensive valuation, they cancel each other out. And what you’re left with is you’re not sure. And if you actually look at a lot of the back tests which are coming onto the market right now, you know, we see this thing pretty prevalent in a lot of those back tests. Those managers, who, you know, really didn’t control those unintended exposures, either got a tailwind or they got a headwind. But either way it was luck, luck is not one of the factors that we like to play. Gillian: Unfortunately not. Well actually… Darby Nielson: But that’s right, I mean it highlights the importance of factor investors doing due diligence on factor products, just as if it was an active product. Ryan Shelby: Absolutely. Gillian: Sure. So it’s important for you to be doing the due diligence on your factors and investors doing due diligence on you. Darby Nielson: That’s right, yeah. Gillian: So, Gregg, I want to talk a little bit about the buzzword of the moment, which of course is smart beta or strategic beta. I think there’s a whole host that we could come up with. Let’s unpack this term a little bit. Is it synonymous with factor investing? Gregg Fisher: You know, I think back to all the different terms that have been thrown around at parties in the last 20 years, you know, fundamental indexing, smart beta, factor investing. Gillian: What parties do you go to? Gregg Fisher: Yeah, you know, not the ones you’d want to be at. Ryan Shelby: The same one as the four of us probably, yeah. Darby Nielson: I was there. Gregg Fisher: The reality is we’re all really talking about the same thing. I think some of us prefer to talk about it in slightly different ways. At our firm we prefer to talk about the factors than the betas. The beta is really the sort of the sensitivity that your portfolio has to the factor. That would be the way I’d describe it, whereas it’s really the factor that we’re talking about. But in the end we’re all really speaking the same language. I think these are predominantly marketing terms. And I don’t know which of them stick. But I do think we’re all really talking about the same thing. It’s what we’ve been talking about. It’s identifying the characteristics or sources of risk and return that drive the cross sectional differences of security returns across markets. Darby Nielson: To be precise, right. Gregg Fisher: To be precise. And but the other thing is we also have to recognize is that these things work differently in different parts of the world and in different sectors and in different asset classes, you know. For example, momentum works quite well in growth stocks but it doesn’t really work very well in value stocks. You know, and I can give another 20 examples like that. So different factors work differently in different places. But, you know, whether we’re talking about fundamental indexing, smart beta, dividend tilts, small cap, these are all various forms of factor or smart beta investing in my opinion. Gillian: And then, Arne, what about strategic beta? Arne Noack: It’s ultimately the same thing as smart beta, as a lot of the buzzwords that we’ve just heard. On our side the way we like to think about it is smart beta or strategic beta is a very broad umbrella that includes arguably strategies that might not necessarily appear as very smart. So let’s, for example, have a look at equal weighting. If you have an equal weighted S&P 500 strategy, you might seem to have been quite smart in your allocation because in the past that actually outperformed the standard S&P 500, the market cap weighted version of it. However, when you really have a look under the bonnet and have a look at what drives the return of an equal weighted strategy, that’s typically the size factor. And that doesn’t come as a surprise because obviously what you do in an equal weighting is you overweight the smaller cap names compared to your market cap weighted benchmark, you underweight the larger names compared to your market cap weighted benchmark, hence the size premium. And so when you look at really a, for example, size factor index and compare that to an equal weighted index, you see amazing correlations and similarities. So a smart beta strategy would be something that is very broad, ultimately the factor is the engine that would then drive a smart beta premium, that’s how we like to look at it. Gillian: And, Ryan, would you agree? I see you nodding your head. Ryan Shelby: I would, I’d probably add one more caveat to that, so, yes, and, the and I think is they tend to be more passive in nature, more transparent rules based. For me, smart beta tries to bridge the gap between active and passive management. You know, it’s passive in they’re liquid and transparent, you know they’re pretty low fees, they’re pretty inexpensive to trade typically. But they also preserve the ability to outperform the market, so better than a cap weighted benchmark. So for me the hallmark of a smart beta strategy is that it gets exposure to factors but it’s a very transparent sort of rules based approach. Darby Nielson: Sorry, I was just going to add to that, that I think that that’s been part of the evolution of factor investing in the last 10 or so years where it’s gone from active, quantitative strategies that were opaque to very transparent passive based strategies where you can get it in an ETF structure. And I think that that’s been a major evolution that’s made factors available to investors all over the world. And I think it’s good. And I agree with all this. I mean it only went from beta, the original beta, which was sensitivity to the market from the capital asset pricing model to smart beta because you could presumably get excess returns. But to me, I think we’re all in agreement that whether it’s smart beta, factor investing, strategic beta, whatever you call it, to me it reminds me of what I heard a portfolio manager say a couple of years ago, He said, “What I like about quant is that it’s the automation of the quantifiable aspects of investing.” And I think that’s kind of another way to talk about or to describe what factor based investing is all about. Gregg Fisher: Yeah, and I’ll and, and to that, which is that I agree with everything we’ve all said. And I’ll bring transaction costs back into the discussion. I think when you look at these factors that have been researched and we think about which ones to pick, whether it’s dividend tilts or the size premium or price to book. There are a lot of ways of getting to the same place. But often what we find is that some of the ways of getting to that same place could be more cost effective than others. An example I would give, coming back to the equal weighting concept or fundamental indexing which is just a cute way of doing value investing. You’re sort of tilting your portfolio to either size or value. But what happens with those strategies is they tend to have higher turnover than more a simple price to book strategy or a dividend tilted strategy tends to have higher turnover than a price to book strategy. And it’s another form of value investing. So if one wanted to create a low cost, low turnover, stable value strategy, might it be the most effective to create a price to book strategy versus price to dividends. Now, that’s a question we don’t have to answer here. But I think as portfolio managers, strategists and researchers, that’s something we’re always thinking about, how do we get the investor to the place we want to get them to in the most cost effective way. Gillian: Yeah, I think that’s a great point. And there’s no more timely discussion than the discussion of fees. I mean, it’s the one thing that’s dominating the headlines now. I want to move over to a little bit about how factors work in the particular environment that we’re in. But before we go there and I think, Darby, I’ll start with you, is it possible to time factors? Darby Nielson: Well, I’m not going to say it’s impossible. But I would say it’s extremely difficult. You know, we’ve done a lot of research on that. We do have some models where we try to adjust the weights of some of the factors in some of our models. But it’s extremely difficult. However, it is the case that, you know, even the factors that work over time and add excess return to a portfolio like value and momentum, they don’t work all the time. Typically factor returns are cyclical. Therefore there should be an opportunity to time factors. However, building those models, I’ve tried it myself, my team does it. We’re making an enhancement to those models. It is extremely difficult which is why often a multifactor approach of combining factors tends to be a better way to do it, I think. However, if you have a view on factors or where you are on the business cycle which may impact the returns to factors or a view on interest rates, which I think you mentioned a moment ago, all of those things affect the performance of factors. And because they’re cyclical in nature, it’s possible to do it, but it’s very hard. Gillian: Hard to get it exactly right, Arne, I’d imagine. And you’re obviously running a multifactor portfolio so is it just an opportunity for some to be up while others are down and it doesn’t necessarily matter when that happens? Arne Noack: Yes. On our side the way we’d like to talk about this with our clients is sort of as a two step process. One is, are you a believer in factors? Do you believe in the sustainability and persistence of certain risk premium that they actually generate over time that which everybody believes they do. And if the answer to this is yes, great, we go to the next step of the conversation, how to best deploy them in a portfolio. And of course then you can come from either sort of a risk management approach or sort of an investment sort of investment side of approach, which is risk management, you dissect your existing portfolio and find out whether you have any unwanted biases either, you know, you might be overweight or highly exposed to value when you don’t actually want that. Or you have not enough exposure to momentum and you sort of want to balance that out. In sort of the absence of that risk management approach, from an investment approach, the way we like to look at things is we actually like to blend the factors in a way that we actually have high factor exposures to all of the premia at the same time. And I think what comes into play here is that it’s very important to understand that factors are unlike sectors. One particular stock has exposure inadvertently to all of the factors all at the same time. The question is how much. And the implication of it is that you can actually, if you don’t do it properly, you’re at the risk of diluting factor exposures when you, let’s say, mix the wrong stocks. If you mix a high value stock, but that’s also very volatile and you have a low vol stock but that’s not very cheap, you combine the two, you don’t really have exposure to either value or low volatility in your portfolio. So ultimately the way we like to look at things in our multifactor approach is we like to identify stocks that have high exposure to all of the different factors that we seek exposure to at the same time. So let’s say if it was value and low volatility, the high conviction stock for us would be the cheap stock that also has a low volatility instead of combining two stocks that have one characteristic each. Gillian: Yeah. I think that’s a good point. Everyone knows when they look at sectors that you can’t necessarily be a healthcare and a telecom at the same time. But with factors it’s much more nuanced than that. So, Ryan, you’re also operating on a multifactor model. So if we can’t time them, how do we weight them properly? Ryan Shelby: Well, I may take issue with you can’t time them. I’d say it’s difficult, you know, we have a business that focuses on actively timing factors. So that’s one thing. But, you know, what you get with that is you get the potential for outperformance. You know, we’ve been managing those strategies for over 20 years very successfully I might add. But you get a reduced capacity into those strategies, you get a lot more turnover, you get a lot less tax efficiency, if that’s something you’re interested in. Obviously you get higher transaction costs and management fees. And so, you know, if you want to actively time factors you can, but there is a give or take depending on how you look at it. You know, on the more passive side to managing factors or more strategic or long term exposure to these factors, you know, I think you’re right. I think as you build a portfolio from factors, you want to be cognizant of the factor loads of the individual stock level. You want to do it in a very integrated approach to kind of balance out those things. I would…our process is slightly different. And so when you actually look for a low vol cheap stock, that’s a unicorn, right. That’s a great stock to buy. The problem is there aren’t very many. So then you’re kind of back to the active management side of things. And then when that stock moves around then you’re actively trading around that. And so for us we take a slightly different approach. And so we look at the stock exposure at the individual stock level. But we balance that stock’s exposure to marginal contribution to risk and marginal contribution to return. So we try to understand, hey, is this stock actually helping our portfolio or hurting it? Right, I don’t care if it’s expensive if it’s really giving me a nice risk reduction in the portfolio, you actually might be willing to pay for that. You know, 2008 is a great example of that. If you look at low vol stocks in 2008, good luck finding a cheap low vol stock. If it was cheap it probably wasn’t really low vol, right. There was probably something going on at that stock, because people were willing to pay for that insurance as the market, you know, caught on fire essentially, right. Darby Nielson: it became high vol. Ryan Shelby: It became high vol, everything moved into that high vol, VIX, a common measure of investor fear, went from, you know, 20 long on average to 80, a very, very scary time in the market, people wanted safety. And so, you know we, our process is slightly more nuanced in that we do the tradeoff at the individual security level, balancing, maybe it’s an expensive stock but it has these other characteristics that we like. Gillian: Ok, I think those are all good points. And I want to move over a little bit to this theme that we keep coming across. A lot factor investing seems to have a sort of value tilt, Gregg, would you agree? And can you apply it to growth stocks? Gregg Fisher: Yeah, it’s a good question I think. So when I took a look at the industry back in the late 90s, you know, I had tremendous respect for all the researchers that pioneered a lot of this work, Merton and Ross and Fama and French and Titman and Carhart and Sharpe. You know, these are, you know, for us like the Babe Ruths of finance. But what I found was that almost all of these ideas and strategies that were out there in the 90s and early 2000s were all some form of value investing. As a matter of fact, almost everything we just talked about for the last half hour or so were various forms of value investing. And there were very few, if any, quantitative managers applying these ideas amongst growth stocks. So actually at our firm we actually launched growth products which were somewhat unique, you know, using a multifactor approach in growth stocks. And then later we actually did the same thing in REITs, a global REIT portfolio, we were the first multifactor really quant global REIT strategy. There are a few others now. These are asset classes that were traditionally filled with fundamental managers, that weren’t really talking about multifactor investing. And again, as a point I made earlier, I think what we found was that there are certain factors that work better in things like growth stocks or REITs than they do in value stocks. I could give examples, the momentum one we talked about earlier which works quite well in growth stocks. We also found that in REITs for example, another area where it wasn’t popular to be doing this. There was something we came across which was leverage. Leverage is a factor that affects the price and returns and risk of REITs. And we found that by just underweighting leverage, we produced better sharp ratios, better risk adjusted returns. And combine that in this multifactor setting where you’re also thinking about other things like size and value and how you put these things together. So I think there’s still a lot of work to be done applying these ideas in growth stocks. It’s definitely not as common. I think that one of the reasons for that is that there’s a lot more ambiguity of what the sort of fundamentals and prices are in growth stocks than there are in value stocks, the dispersion of analyst opinions, the behavioral biases, overconfidence. There’s just so many reasons for why it’s just not as popular to do this there and why there might be plenty of room to expand on the products and factor research in that area. Gillian: Do you also find that there’s a value bias in a lot of factor based strategies? Darby Nielson: I think that there is. I mean but I would slightly disagree with some of what we’re saying here. I mean I do think, I mean like I said before, there’s factors that I know and love, value’s one of them. I actually kind of consider myself a value investor. And I love including value in any sort of multifactor product. But I think that there are some factors that aren’t value, right. I think if you combine it with value you get a better outcome. But momentum is very much not value, right. You’re buying expensive stocks that have gone up probably, and not cheap stocks. And I think that there are other factors that don’t work at the same time as valuation, which means it’s not quite value. So I’m not sure I would say that they’re all kind of based on value. However, to your second question, I think it very much can work in growth stocks. You know, stocks follow earnings; it’s actually part of our investment philosophy at Fidelity. And we’ve actually done a lot of work on figuring out how much do stocks follow earnings? Which is a growth approach to investing I would say. If you can get the earnings growth right, you can make a lot of money. But if you combine it with valuation you can make even more money. So within growth, value works quite well. And I think some might even argue that value works better in a set of growth stocks than it does in value, so absolutely. Gregg Fisher: Yeah. I think that’s a good point actually, the research that Novy-Marx did a few years ago on profitability. Because I think growth managers were struggling on you know how do we find value characteristics in growth stocks when earnings are a little more debatable, book value is a little more debatable. You know, a lot of growth companies don’t have book value. They’re all like R&D and things like this. So I think that profitability research was a good example of the point you’re making where it was a way to search for value characteristics in growth stocks, and sort of go higher up on the income statements since earnings are so polluted for growth stocks. And I think it’s exactly the point you’re making and it’s a good one. Gillian: Now, whenever I speak with equity managers who are not necessarily in name, factor investors, we are always talking about growth and value. But, Ryan, I’m curious to know how have some other factors performed this year? And can we look back maybe over the last calendar year and think about what did well and what didn’t and anything that we can deduce now that really drove that? Ryan Shelby: Yeah, absolutely. If you go back, let me take it a step farther back and I think that’ll kind of set a scene. So you know, I mentioned 2008 and the performance of low volatility, or low beta assets in that market. You know, when the market is very fearful it moves into safe haven assets typically. Low volatility is typically the beneficiary of that. Those stocks tend to lose less in a down market. And on the back end of that in 2009 when the market rallies, volatility or VIX or, you know, market fears falling very quickly, you know, investors don’t really care about safety assets. They want gasoline to put on their portfolio. They want beta in their portfolio. And so that’s when those stocks actually underperform. That’s that cyclical nature of a low volatility factor. Now, if you hold it over that time period you’re compounding out at a better rate. You’re losing less on the downturn and it’s the eighth wonder of the world, compounded returns, right. It grows at a much more attractive rate. If you fast forward back to 2016, particularly the second half, we saw the second part of what I just described. You saw a very low risk environment where investors were very not fearful about their equity allocations. You saw volatility remain at incredibly depressed levels. If a long run average for VIX, a common measure of investor fear, is 20, it was about 10 most of the year, particularly second half of the year. As it moved into that rate, we saw a huge dispersion in performance between high volatility or high risk and low volatility or low risk, low beta names, to the tune of about 30% US markets. If you had an allocation to low beta in your portfolio it hurt, that’s a 30% spread between higher risk and lower risk. And so I think that’s really why we’re all talking about multifactor solutions in this space because you know having a dedicated allocation to low vol is a fantastic idea over the long term. The problem with that is in periods like the second half of 2016 it can really hurt. And so, you know, for Analytic we manage about 15 billion or so in low volatility assets. Our clients were comfortable with that return stream, because it’s more of an asset allocation tool. I mean we’ve been talking about, you know, return side of everything throughout this whole conversation. I think where we need to shift it as well is the risk side of things. Some of these factors don’t necessarily give you an excess return; they give you a lower risk profile, the diversification to the market. That’s what low vol is. And so if you have it in your portfolio for the right reason, investors are typically happy with that. They kind of understand there is volatility around your excess return, or tracking error as we know it, but 2016, our tail end of that was quite painful for anybody that had a low vol allocation. Gregg Fisher: You know, something that, we recently published … well, there’s a paper that we just wrote about what we’re now calling the country size effect. There has been very little research done on this, but it’s another factor that we have sort of done some work on. And it’s about having more exposure to smaller countries than larger countries. Now, on the point about what’s done well in the last year I think for any advisor out there, you know, we’re talking about factors and security level research. But the real reality is, you know, the more money you had outside of the US this year the better you did. You know, that was the real big factor, I guess, currency or, you know, foreign market exposure. And then a lot of these themes we talk about at the security level also work in other countries. But this idea of thinking about your country weighting, a lot of the concepts we’re describing like price to book, price to earnings, you can almost think of countries as stocks and think about price to book or price to GDP. And what you’d find is you’d have, if you followed these ideas at the country level you’d probably have a little more exposure to smaller countries and a little less exposure to bigger countries, of course the US being the biggest country if you rank it by market cap. I think there’s a lot more research to do there. But you know, looking back over the last year, you know, thinking about your global exposure and applying a factor kind of set of ideas to that might be an interesting thing for advisors that are watching this to think about. Ryan Shelby: That’s actually how we construct portfolios as well. We’ll take what country is it in, industry is it in, region is it in. There’s a number of different things we’ll actually look at. And we’ll grass out the beta of that return stream essentially. And so, you know, oftentimes when you see a premia associated with a country, is it because it’s smaller or is it because there’s more geopolitical risk? Is it because their manufacturing base is more concentrated? It’s very difficult to sort of mix those risk premia. So for us again, that whole purifying your factors approach, we really want to strip out all those country effects, all those industry effects, all those residual effects and really get that one thing we’re after. And again we want to understand the risk embedded within that. And so, you know, again, one thing we haven’t talked about is weighting these multifactor approaches, right. How do you actually decide on a weight between value and momentum and quality? Well, you can equal weight it, that’s a fair way of doing it. But what if one of those factors is twice as risky as something else? Right, you can conviction weight it but what if you’re wrong? These things are cyclical and so the way we actually look at doing it is weighting it based on some sort of a risk measure, trying to deliver the highest sharp ratio is really our objective on our portfolios. Gillian: Now, we’ve done a little bit of a look back here on some of the things that have done well. But, Arne, I want to point out that we’re coming into a rising interest rate environment, all be it off of a low base. How do factors generally perform in this type of environment? Arne Noack: Well, that sort of goes to some of what we said earlier in terms of predicting factors. And I won’t go into that too much because it is very difficult. What I would say is some of the sort of low risk factors tends to be overweight, if not controlled, some of the more interest rate sensitive kind of sectors. And so what very often you do, if not controlled for carefully on something like quality maybe, or in particular, low volatility what can happen is you increase certain interest rate sensitivity in your portfolio. So if you look at using single factor products, maybe you want to have a look at that as an investor, that there are controls around sector exposures and ultimately the interest rate sensitivity that you may introduce through that. Gillian: And, Darby, please. Darby Nielson: No, I was just going to say, I mean I don’t know which direction interest rates are going to go. And therefore it’s hard to tell what different factors, how they’re going to perform going forward. But I think the answer to your question of if and when rates go up, how are factors going to perform? The answer is it depends on the factor, right. And I can answer empirically what we’ve seen in the data in the past is typically when interest rates are going up, it’s because the market is becoming a little more … interest rates are going up because bonds are going down, right. So the market is becoming a little more risk on. When that happens things like low vol strategies tend to underperform. Things like dividend strategies tend to underperform because the bonds become more attractive relative to the equity. So there are some certain things that have happened in the past when rates go up, value tends to do a little better, small cap tends to do a little bit better as the market goes into more risk on environment. And I think actually a good test case is what happened in the second half of last year. Interest rates bottomed, I think in July. And I think that was probably the top of low vol when that started to underperform. They bottomed in July and just crept up the rest of the year. And then when the election occurred we saw a big spike in interest rates. When you saw all that happen, low vol underperformed, value and small cap did very well, which is what has typically happened, or at least if you look at the data empirically. And so I think there are some relationships over time between interest rates and factors but it depends on the factor. And that’s what we’ve seen in some of our research. Gillian: So I’d like to move our discussion. We’ve kind of built a really robust picture of the factor investing universe. But I want to dive into each of your areas of expertise. And so, Ryan and Arne, you’re sat next to each other and I want to start with the two of you. You’re both employing a multifactor approach. So, Ryan, you started to touch on it a little bit. But give me a little bit of a deeper dive into how you build your multifactor portfolios. Ryan Shelby: Yeah, no, we actually look at the factor exposure at the individual stock level. You know, our underlying philosophy of our strategy is, look, if factors matter, and we think they do, and I think that’s what this panel would agree, factors do matter to the risk and return of your portfolio, you have them in your portfolio whether you like it or not, right. They’re already in there. If you have an index fund, you have good stocks, high quality stocks, you have low quality stocks, you have high momentum, low momentum, expensive, cheap stocks. You kind of buy the good and the bad and the ugly, right. Our philosophy in our more passive or factor enhanced strategies is really look; there’s a few things that you like about a passive index, which is that liquidity and transparency, that low fees. And there’s a few things you don’t like which are exposures to factors which we know are actually going to hurt the risks or hurt the return of your portfolio. So the way we actually do it is from the bottom up, we look at those securities that are dragging down that marginal contribution or that individual impact on risk or individual impact on return. Which stocks are making your portfolio worse? We take everything that’s left, build that into a portfolio and that’s ultimately what we do. When we actually look to weight the factors we’re going to use the volatility of those factors to help inform how we weight them in our model, because again, you know, coming back to how do you actually combine those things. You want to make sure that one factor really isn’t driving the ship. You want to have that multifactor smooth sailing ride. You want that diversification to help really, you know, give you that nice smooth ride or low volatility strategy you’re looking for. Gillian: I like the way you started that, it’s like you have factors whether you like it or not so you might as well make them work for you. Ryan Shelby: Right. And I think one last thing. We are not looking for an all around athlete. I think that’s probably a big differentiator. And I think those are harder to find. I mean we all kind of know who’s, you know, if you go to athletics or you go to sports teams or something like that. If you have one basketball player, you may have a very good jump shot. You may be very good at driving. You may be able to shoot threes. But there’s only one or two of those players. I think you’re much more likely to put together a very good team, a good shooter, right, a good dribbler, a good rebounder. And that team is going to be better than that one player. And so that kind of summarizes our philosophy. We look for those characteristics which are really helping the whole team, and that’s how we try to build our portfolio. Gillian: So the money ball approach, if you will? Ryan Shelby: I suppose that’s right, yeah. Gillian: Arne, how do you build your portfolios? Arne Noack: I’m actually surprisingly much in agreement with everything that was just said. The approach that we have is also a bottom up approach and whereby we actually try to identify those stocks that do well across the different factors that we seek exposure to. For the purpose of the off-the-shelf products that we have at the moment, the factors that we use are five size, so low size, high quality, high momentum, low volatility and value of course. And so for the purpose of those products, the sort of high conviction stocks are the biggest weights in our portfolios, the biggest active weights compared to market cap weight benchmark, are stocks that do well in all five are multiple of those factors at the same time. And we would underweight the stocks that don’t do well in particular, one or two of those factors. The idea is that you still maintain a market beta of roughly one and ultimately through the combination of those stocks you skew your up and down capture ratios with the idea that you capture the market when it goes up. So ideally a capture ratio of roughly 100, maybe between 95 and 105% and at the same time have a downside capture ratio of maybe 75/80%. So ultimately to your point, make use of compounded return, win by losing less over time and when things are going well still have a decent capture on the upside. And of course that’s sort of our standard approach. What we actually do a lot is we engage in conversations with clients to customize this. Gillian: I was just going to ask that. If it’s a static approach or not. Arne Noack: So for the purpose of what, you can simply find on our website and then click, and invest, buy an ETF, that’s sort of a plain vanilla approach that we offer. And then if you have the desire to actually have something more customized, more fit for you own very specific purpose, we can go down as granular as you like. We can employ certain risk frameworks to control for volatility, to control for let’s say an equal risk contribution of each of the factors. We can overweight specific factors if you want a more conservative portfolio to even reduce the downside capture even more, or we can be a bit more aggressive to reduce the upside capture a bit more. And then sort of deliver that in various formats, either ETFs, funds, mandates, it’s essentially all open and at investors’ disposal. Gillian: So you can fit pretty much any investor mandate? Arne Noack: Pretty much. Ryan Shelby: Yeah. And I think that’s a theme, right, factor investing is the building blocks. And I think all of us kind of apply it in different ways. And I think it’s up to the client to figure out how that fits, right. It’s a conversation we have a lot with our clients. How does this fit? What can we customize for you? I think it makes a lot of sense, that approach. Gillian: Darby, what’s the Fidelity approach? Darby Nielson: Well, I was just going to say, to me, it kind of comes down to how you weight the factors, which we’ve touched on by now. But I think it depends on what is the investor outcome objective that they’re trying to achieve. Or it depends on their philosophy. So I think you customize it, if maybe you want more yield then you put more weight on the dividend factor. Or if you want lower volatility, it’s obvious what you do there. So I think it depends on the objective, that’s how you kind of weight the factors or the investor’s philosophy, where if they’re a value investor you want more exposure to value. Typically in our multifactor models that we use across the quant team, and we have a lot of them. We often err on the side of equal weighting. And part of the reason is because it’s very difficult to factor time. Like I said, we do have some models that can tilt those factor weights based on some factor timing models we have. But we err on the side of equal weighting because we want to avoid over-fitting, right. Us quants have been doing this a long time, we know that quants can be guilty of over-fitting things all the time. But if you equal weight you can kind of avoid that. Although I think another important consideration is turnover because some factors have more turnover than others. And if you’re concerned about turnover you might want to have less weight on momentum than you would have on something like quality. So I think a lot of this comes down to how you weight your factors in your multifactor process. And I think that it depends on your objective. And you’ve got to consider some of these other things like turnover. Gillian: Now, Gregg, you touched on the country size premia, but can you tell us a little bit more about how you apply factor investing to global real estate? Gregg Fisher:Sure. Yeah, I think, so global real estate is a bit interesting. It’s still for many investors and advisors that serve them, it’s a tiny percentage of investors portfolios. Maybe on average you see 2, 3, 4, 5% allocations to this asset class, when meanwhile real estate around the world is still probably the greatest value out there, the trillions of dollars of real estate privately and publicly. REITs are a funny thing in that it’s the strange asset class where we’ve got a public and private market operating for almost identical properties at the same time, which makes it very different than traditional equities. So there are some things that are unique about it. But I would just say that on the high level, everything we’ve all said I would agree with. And we’re applying that in our REIT strategy and in our growth strategies. For REITs in particular I think something to reference, I mentioned earlier, leverage. So the size premium as it relates to security size in REITs, we apply that in our REIT strategy. So on average we have smaller names than our peers and benchmark. And the size premium is vibrant in the REIT space. And similarly the momentum premium is also vibrant in the REIT space. As a matter of fact, the momentum premium in REITs is actually even bigger than it is across almost all sectors. So size, momentum and then of course, value. Value is a little bit different with REITs because you can’t really just accept the book value of REITs. There’s this net asset value that has a lot of subjectivity to it and needs to be refreshed and updated more frequently than what we pull off financial statements. So we have a certain unique way of rethinking about the net asset value and then again, of course, that price in the numerator. Then you take all of those things and you think about leverage. So if you think about risk and marginal contributions and correlations. When we dial up the risk by having a greater amount of exposure to things like momentum and size, but we dial down the risk by reducing leverage. When we put those things together the unit has better risk adjusted returns or sharp ratios than if we had not done that. So it’s about taking the right risks and how we combine them. And that’s really what we’re doing in our global REIT strategy amongst other things. Gillian: Perfect. So you’ve given us a good opportunity to get to know each one of your businesses. But I want to since we’re coming close to the end of our discussion, turn it back to our audience. So as they’re evaluating the range of opportunities, and you’ve certainly presented some great ones here today, can you give us a sense of the best way to perform due diligence on factor based models? Because, frankly, Ryan, all products are not the same. Ryan Shelby: Yeah, and that’s a great point. You know, I think first the philosophy of the fund, or the strategy, right. What are they actually trying to get exposure to? And are they doing it successfully? So that’s what you want to start with. Why did I hire this fund? Or why am I taking a good look at this fund? What are the things that should drive the return? From there you can kind of back into, ok was it a value market and that underperformed, what happened? What ancillary exposures did they have? You know, for us the key thing is performing very detailed attributions, or splitting out the contribution from each of the factors. You know, we hear this a lot, that when you build four factor portfolios, kind of bolt them together, it’s very easy to do attribution. In some ways that’s true. The problem is if you don’t purify those individual portfolios, again you see those ancillary or unintended exposures kind of sneaking in. Developing those or catching those early in the process is really important. So as I look at multifactor funds, I want to look at the construction techniques, right. I want to make sure it’s an integrated approach. That they’re considering all that stuff, they’re pulling out all these ancillary exposures. And then I want to say, “Okay, how did the individual factors perform? And then how did that actually translate into my portfolio’s performance?” Gillian: Perfect, Darby, what are your final thoughts of anyone that’s watching this program, how can they do due diligence on factor products? Darby Nielson: Yeah, I would say the first thing you need to consider is who’s the provider, right? I mean is the provider of the factor ETF, or mutual fund or whatever, do they understand factors? Are they investors? Do they understand why factor works? Do they have a robust quantitative research team that knows what they’re doing? So who is the provider? Do they have the expertise? That’s the first thing. And then the next couple of things, I think Ryan touched on, right. One is are you getting the exposure you want? If it’s a value product is it cheaper than the rest of the market? If it’s a quality product, does it have higher profitability, return on equity, whatever it is. So you need to insure you’re getting the targeted exposure that you want. And then the second thing I would say which you kind of hinted at which is what are the other effects in the portfolio? Are you getting big sector effect? Is it just a utilities fund in disguise? Is it a small cap fund in disguise? So ensuring you get the targeted exposure you want and you’re not getting other exposures that you don’t want is what you really have to analyze, which I think is really what Ryan and I are both saying. So I would say those are a handful of things you want to think about in the due diligence process. Gillian: Ok, so keeping an eye on that exposure and making sure that your manager has the expertise to do that for you. Darby Nielson: Yeah, the expertise that you’re getting the targeted exposure and that you’re reducing the unintended exposure. Actually I would add maybe a fourth thing which is that you want to make sure it’s competitive performance, but not shoot out the lights performance, because that means it might have been over-fit, as I talked about before. And if it looks like it was far better than all the other products then you might be looking at an over-fitted back test or something like that. I think that’s something people also need to keep an eye on. Gillian: Perfect. Gregg. Gregg Fisher: You know, I think I would just say how long have they been doing this, the track record, you know, I see a lot of firms in the industry that will sell to investors whatever Wall Street, you know, whatever people want to buy. And I’m seeing a lot of people coming to factor investing because it’s in demand, not because they have a genuine belief in, you know, markets and how they price risk and the research. You know, I have a bias here because we’ve been doing this a long time. You know, we trademarked the term ‘multifactor’ in the use of mutual funds about a decade ago. And I mentioned earlier at a time when no one was talking about it. So I think it’s important to, you know, look at how long have they been doing this, not other things, but this? And that’s how we would analyze any portfolio manager out there, it’s nothing new. And the philosophy, you know, do they really believe in this? Were they doing this at a time where it wasn’t so popular, you know, as opposed to just coming to it because it’s what the market demanded? Gillian: Excellent. And, Arne, last and final thoughts. Are Noack: So what I would add, and all of these points are extremely crucial and important. If I was an advisor how I would approach this subject first is from my point of view, what’s my objective? Why do I care? Why do I want to enter this space? And what’s my objective for the purpose of doing this allocation? And then the second step is, which is the best tool to achieve my objective? So for example, do I want to reduce volatility in my portfolio? I might then pursue the avenue of the low vol or high quality investing. And I look at the different funds and ETFs that are out there compare them in accordance with all the metrics that we’ve just heard. Or alternatively, do I want to replace a core strategic allocation to a market cap weighted benchmark, multifactor investing might be a good approach. And then once you go down the multifactor route there’s various considerations, for example, do I already have fairly substantive and substantial exposure to one of the factors and therefore, you know, I look at the different multifactor combinations that are available, which factors do they combine? If I already have one in my portfolio maybe I choose the one that doesn’t have that one that I already have in order not to re-jiggle my portfolio too significantly. So if I was an advisor I would always bring it back to my existing portfolio and the objective that I have for the purpose of my allocation and then find the best tool. Gillian: It’s a good place to end on, so knowing what you’re getting into, knowing the exposures, the managers, their track record. But also knowing yourself and knowing what you have exposure to and what you want. So thank you all so much for joining us here today, I really appreciated hearing your thoughts. And thank you for tuning in. From our studios in New York, I'm Gillian Kemmerer and this was the Factor Based Masterclass.