Speaker 1: Hello, and welcome to the Credit Edge, a weekly markets podcast.
Speaker 1: My name is James Crombie. I'm a senior editor at Bloomberg.
Speaker 2: And I'm Jeannief Cooper, senior analyst at Bloomberg Intelligence. This week,
Speaker 2: we are very pleased to welcome Savina Risova, co Chief
Speaker 2: Investment Officer and Global head of Research at Dimensional Fund Advisors,
Speaker 2: at seven hundred and ninety billion investment firm. How are you, Savina, good?
Speaker 3: Thank you for inviting me.
Speaker 2: Savina joined Dimensional Fund Advisors as a research associate in
Speaker 2: two thousand and four, and just of our year ago
Speaker 2: she added the title of co Chief Investment Officer. You
Speaker 2: also obtained a PhD in finance from the University of Chicago. Last,
Speaker 2: but not least, Sabina was recognized as one of Barn's
Speaker 2: one hundred most Influential Women in US Finance for two
Speaker 2: years in.
Speaker 1: So we're going to get into all that, but just
Speaker 1: to set the scene before we do. Markets have rallied
Speaker 1: on high hopes of a broad ceasefire in the trade war,
Speaker 1: but there's still a lot of uncertainty out there, plus
Speaker 1: more volatility to come as the US moves on from
Speaker 1: tariffs to tax and immigration. Reform, headline risk is very high,
Speaker 1: yet credit markets project an air of complacency, with debt
Speaker 1: spreads back below where they were before the so called
Speaker 1: Liberation Day at the start of April. Keeping corporate debt
Speaker 1: risk premium very tight is the fact that there's way
Speaker 1: too much demand for a very limited net new supply
Speaker 1: of corporate bonds, and unless the M and A machine
Speaker 1: cranks back up, that supplied demand imbalance will probably continue.
Speaker 1: On top of that, the US has lost its Triple
Speaker 1: A credit rating, calling into question the idea of risk
Speaker 1: free rate and investors are now looking more at Europe
Speaker 1: and Asia as alternatives, but there are clear limitations when
Speaker 1: it comes to scale and liquidity there. So, Sabina, what's
Speaker 1: your take. I'm going to ask a really broad question
Speaker 1: because it's one that keeps coming up on this show.
Speaker 1: But is credit fairly valued at these levels?
Speaker 3: Well, the meension we don't pretend to have a crystal bow,
Speaker 3: James and know where prices are relative to fair value.
Speaker 3: We actually take priceses kind of given in public competitive
Speaker 3: capital markets. But what we can say is where the
Speaker 3: current credit spreads are relative to historical averages and medians,
Speaker 3: and these days, what you mentioned is absolutely correct. Credit
Speaker 3: spreads have are about eighty to ninety beps depending on
Speaker 3: whether you look at US or global markets below historical
Speaker 3: mediums of over one hundred, one hundred and ten basis points,
Speaker 3: So definitely narrower credit spreads and based on academic research
Speaker 3: underpinning our approach that suggests lower credit premiums expected in
Speaker 3: the future. As a result, our core strategies tend to
Speaker 3: not go to their maximum allowed credit allocation right now,
Speaker 3: and our credit strategies are not allocated to the maximum
Speaker 3: in what we call low work here single aay tripob
Speaker 3: bombs for example.
Speaker 2: So in terms of allocation, I mean, are you looking
Speaker 2: across the credit spectrum, do you have any views on
Speaker 2: higher quality names versus lower quality names given the environment.
Speaker 3: Absolutely, And it's probably worth kind of taking a step
Speaker 3: back and just telling people a little bit more about
Speaker 3: who they mention is and how we approach investing both
Speaker 3: in equities and fixed income, because I think it's pretty
Speaker 3: unique and different from a lot of guests you've had
Speaker 3: on the podcast. The Dimensional is a firm that was
Speaker 3: founded in nineteen eighty one to implement kind of rigorous
Speaker 3: research into robust investment solutions. One we would like to
Speaker 3: think about. It is sensible ideas, implement it thoughtfully and
Speaker 3: so and it comes to fixed income. You mentioned Gene
Speaker 3: Fama being one of the academics tightly connected to dimensional
Speaker 3: He did a lot of research in the seventies and
Speaker 3: eighties in terms of what drives expect bond returns. And
Speaker 3: if you think of the expected returnal defaulte free bond,
Speaker 3: like what my thing, the US bond still US government
Speaker 3: bands still consider it uh to your earlier point, UH,
Speaker 3: you can actually write it down as like three terms
Speaker 3: yield expected capital appreciation or depreciation depending on the shape
Speaker 3: of the curve, so roll down as some call it.
Speaker 3: And the third term is expected changes in the shape
Speaker 3: of the youth curve. And between now and when you
Speaker 3: expect to sell the bond. So the first two components
Speaker 3: of that decomposition, yield and roll down together our called
Speaker 3: forward rates. And there is a lot of empirical academic
Speaker 3: reaserch showing that forward rates do contain information about subsequent
Speaker 3: bond returns. So differences in forward rates across bonds contain
Speaker 3: information about differences in future bond returns. And you can
Speaker 3: apply the frame and tested and we have not only
Speaker 3: across duration spectrum, but also across credit quality spectrum and
Speaker 3: across currency of issue spectrum. So, for example, the differences
Speaker 3: in fields or forward rates between longer and shorter bonds
Speaker 3: tell you the term spread essentially contain information about the
Speaker 3: future term premium. The wider the term spread is generally
Speaker 3: the wider the subsequent future term premium is. Similarly for
Speaker 3: credit premium and credit spread. That's why I said like
Speaker 3: currently credit spreads are relatively narrower, which means we expect
Speaker 3: relatively narrower credit premiums less reward for holding credit. And
Speaker 3: then similarly you can apply it across different currencies around
Speaker 3: the world. For example, HATCH to USD looking at what's
Speaker 3: steep versus flatter, the steeper curves HASH to USD imply
Speaker 3: higher expected reward for going into those bonds and hedging
Speaker 3: back to USD right now. For example, the Japanese government
Speaker 3: bond curve is relatively steeper haah to USD compared to
Speaker 3: many other develop market currencies, so some of our strategies
Speaker 3: that are allowed to go global are allocating more to
Speaker 3: Japanese intermediate bonds. So in essence that the dimensional we
Speaker 3: look at forward rates the combination of field and roll
Speaker 3: down as the indication of where highest expected returns are
Speaker 3: and allocate on a daily basis based on differences in
Speaker 3: expected returns and those expected returns those forward rates can
Speaker 3: change any day across the credit, the duration and the
Speaker 3: currency of vision spectrum. So it is important to have
Speaker 3: a daily process where we consume information, compute those expect returns,
Speaker 3: and decide how to allocate new cash community or from
Speaker 3: coupons or from cash flows, and what to buy what
Speaker 3: to sell based on those expected return differences.
Speaker 1: Say, Savi, you have a sort of scientific approach to this,
Speaker 1: and you know, you talk about decades of rigorous theoretical
Speaker 1: empirical research. But as we've discussed, you know, the so
Speaker 1: called developed markets are becoming highly unpredictable as politics becomes
Speaker 1: such a big factor. You know, I would say that
Speaker 1: they're behaving a lot more like emerging markets than they
Speaker 1: used to. Who knows what social media posts will wake
Speaker 1: up to on any given day that will royal global markets.
Speaker 1: But how does that affect your approach? Do you need
Speaker 1: new models for that? Do you rip up the script
Speaker 1: and have to you know, really just improvise a lot
Speaker 1: more than you used.
Speaker 3: To not really exactly, because we are kind of grounded
Speaker 3: in evercreen principles of what drives expect the returns. All
Speaker 3: we need is latest market prices essentially to identify bonds
Speaker 3: with higher versus lower expect the returns. And that's why
Speaker 3: we are big advocates for price transparency and we're very
Speaker 3: happy to see trace that trade reporting and compliance engine
Speaker 3: arrived in the early two thousands bringing a lot of
Speaker 3: transparency to the corporate bond market in USD and now
Speaker 3: there's tracks for a non USD. So we have that
Speaker 3: and we use it on a daily basis in real
Speaker 3: time during the day to essential monitor prices as well
Speaker 3: as bidden as quotes across many different bonds to identify
Speaker 3: differences in expected returns. But what we also do with
Speaker 3: current market information as it changes all the time to
Speaker 3: your point right now very volatile markets, is also used
Speaker 3: current market information for the other two very important dimensions
Speaker 3: of investing. So one day mention is expected returns. The
Speaker 3: other two day mensions of investing in general are risks
Speaker 3: and costs, and we use current market information all the
Speaker 3: time to manage risks and control costs in our portfolio.
Speaker 3: Is because we believe that you can add value by
Speaker 3: systematically designing strategies to pursue higher expected returns, but you
Speaker 3: can also add value through talk for portfolio management and trading,
Speaker 3: how do you use current market information? In portfolio management, we,
Speaker 3: for example, track to your point within the day through
Speaker 3: and daily. The deer inventory trace gives us kind of
Speaker 3: information on net deer buys and sales throughout the day.
Speaker 3: We also get that information daily from similar information daily
Speaker 3: from Blueberg and inter the day from trade web and
Speaker 3: market access platforms that many of your listeners probably are
Speaker 3: familiar with, and this helps us identify bones where dealers
Speaker 3: might in augria have an inventory, accumulated inventory might be
Speaker 3: willing to sell to us at a favorable price, and
Speaker 3: similarly for sales, so der inventory is very important to
Speaker 3: monitor to get great execution. Also, we use market prices
Speaker 3: to monitor credit quality. To your point, in the last
Speaker 3: five years, most of the credit rating changes internal credit
Speaker 3: rating changes we've performed most have been driven by prices
Speaker 3: information in current market prices, not by credit rating agencies
Speaker 3: changing their ratings. So what we use there is not
Speaker 3: just prices of bonds, trading or quotes, but also CDs
Speaker 3: market prices. Even the equity prices of the issues of
Speaker 3: those bonds, so you can use current real time market
Speaker 3: information along with kind of the academic framework for what
Speaker 3: drives expected returns to continue to deliver robust investment solutions
Speaker 3: even in highly volatile times as we are experiencing this year.
Speaker 2: So in terms of your investment approach, I mean, I
Speaker 2: mean the two main investment approach being top down or
Speaker 2: bottoms up, and especially you know, looking at all these
Speaker 2: data that is available in terms of as you said,
Speaker 2: trade and ventory prices, how do you reconcile the two
Speaker 2: and how your investment process I'm sure incorporates you know,
Speaker 2: both of the top down view from rates to you know,
Speaker 2: sectors and then the bottom up this this bond is
Speaker 2: actually treading wide or cheap against another one, and that's the.
Speaker 3: Time to buy. Yeah, thank you for the question. It's
Speaker 3: a common question we get because people are in fixed
Speaker 3: income are generally used to two types of investing traditional
Speaker 3: passive and by the way, these are the biggest kind
Speaker 3: of ETFs and mutual funds out there. Indexed approach in
Speaker 3: fixed income with some sampling under the hood, or traditional
Speaker 3: active where you're typically either top down for making macroeconomic
Speaker 3: forecasts and then driving your investment or bottom up picking
Speaker 3: individual bonds based on research on specific sectors or currencies,
Speaker 3: et cetera. We are kind of combining the best of
Speaker 3: both worlds, traditional passive and traditional active in the sense
Speaker 3: that we have broad diversification in our strategies and relatively
Speaker 3: low turnover just like traditional passive, but we are taking
Speaker 3: from traditional active the daily flexible implementation in the pursuit
Speaker 3: of higher expected returns. How do we do it, though
Speaker 3: different from traditional active? Are we top down or bottom up?
Speaker 3: I would say we're both. Why because we start every
Speaker 3: day by looking at the overall spreads out there, turn spreads,
Speaker 3: credit spreads, and spreads across different field cares, heads to
Speaker 3: a local currency, and that kind of guys the overall
Speaker 3: positioning of a portfolio in terms of how much we
Speaker 3: want to okay to credit corporates versus governments or different
Speaker 3: types of currencies. Once we get do this kind of
Speaker 3: top down analysis based on current market information, then we
Speaker 3: try to kind of bottom up looking at what we hold,
Speaker 3: what we want to hold, which bonds within kind of
Speaker 3: the para. Now those parameters how much we want to
Speaker 3: okay to corporate today versus governments within corporates, Let's say,
Speaker 3: which are the bonds with highest expected returns, most attractive
Speaker 3: forward rates, And we start kind of identifying bonds that
Speaker 3: we would like to buy today based on that approach,
Speaker 3: very systematic, and then what we do is we go
Speaker 3: filter those bonds to a bunch of criteria including kind
Speaker 3: of how liquid those bonds are in the marketplace today,
Speaker 3: are we likely to get good prices for those bonds?
Speaker 3: And then once we kind of set on a group
Speaker 3: of bonds we'd like to buy, we pass this to
Speaker 3: the trading that so for from portfolio management to trading,
Speaker 3: where traders whould go to the marketplace and very flexibly
Speaker 3: seek to purchase some of those bonds without being particularly
Speaker 3: attached to an individual bond. And I think this is
Speaker 3: also a huge differentiator for the dimensional is that we
Speaker 3: are not chasing individual bonds picks of a portfolio manager,
Speaker 3: not at all, and that gives us the ability to
Speaker 3: have great execution. What do I mean by great execution?
Speaker 3: When we compare our corporate and agency trades versus the
Speaker 3: prior trade in the same issue or the next trait,
Speaker 3: on average, our trades are twenty basis points better on
Speaker 3: the buy side and five to ten basis points better
Speaker 3: on the sales side because we trede flexibly with patients
Speaker 3: with optionality out there, we have multiple bonds with similar
Speaker 3: expactor returns that we're interested in buying or selling today.
Speaker 1: Your approach seems take a lot of trust in what
Speaker 1: the market price is selling us in terms of transparency
Speaker 1: in terms of the liquidity. But as you know, you know,
Speaker 1: the further you get down the rating spectrum and the
Speaker 1: more you get into sort of exotic credit you know
Speaker 1: e merging markets, those markets get stuff wrong all the time.
Speaker 1: You know, the signals are just plain wrong. How do
Speaker 1: you protect yourself against that as an investor?
Speaker 3: Great question, James, Another great question. We have historically stuck
Speaker 3: to the parts of the market that benefit from a
Speaker 3: lot of price transparency. So, in terms of kind of history,
Speaker 3: Dimensional started in high quality corporate and government back in
Speaker 3: nineteen eighty three with its first fixed income strategy, and
Speaker 3: then later on expanded to develop market currencies, so applying
Speaker 3: our kind of variable maturity and variable currency approaches there.
Speaker 3: And then we started investing in full investment rate only
Speaker 3: in two thousand and nine, actually a few years after
Speaker 3: trades arrived and brought transparency to the corporate bond market,
Speaker 3: and then we started also kind of dipping our tools
Speaker 3: in double bees, but not going below that. To your point,
Speaker 3: once you go the low double bees into single bees
Speaker 3: and three POC's and below, one major concern is the
Speaker 3: default rates. The default rates increase meaningfully on average historically
Speaker 3: for single bees they are like three percent for trip
Speaker 3: o C and below twenty five plus percent. Those are
Speaker 3: we viewed those as not necessarily suitable investments for ETFs
Speaker 3: and mutual funds, which need to provide liquidity on a
Speaker 3: daily basis. Similarly, we've stuck through history to develop market currencies.
Speaker 3: We do not invest directly in emerging market currencies to
Speaker 3: a large degree because of price tre experiency, but also
Speaker 3: because of operational law and order consideration as well.
Speaker 2: I think there is an interesting point of you know,
Speaker 2: create risk transparency and maybe to switch gears a little
Speaker 2: bit and move into private credit. I mean, we've seen
Speaker 2: a huge expansion of private credit, but also a lot
Speaker 2: of comments and risks maybe out there, and some people
Speaker 2: have been saying there is maybe a risk of you know,
Speaker 2: ratings inflation, or risk of lack of transparency or very
Speaker 2: credit trade. I mean, how do you approach private credit
Speaker 2: as a nassage class within fix income.
Speaker 3: So as a manager, they mentioned it is in the
Speaker 3: public space public stocks and public bonds and a systematic approach.
Speaker 3: But we strive to be a very objective thought leader
Speaker 3: in the industry put a lot of papers out are
Speaker 3: the SIK to provide kind of a framework for how
Speaker 3: to think about different investment topics. And so a couple
Speaker 3: of years ago, with the growing interest in private and
Speaker 3: the growing i'd say push of private out there, we
Speaker 3: decided to actually buy data historical data from Burgess now
Speaker 3: MSCI on private fund performance and study private performance across
Speaker 3: four major asset classes, one of them being private credit.
Speaker 3: So we looked at historical performance of private credit from
Speaker 3: nineteen eighty to twenty twenty two, and what we found
Speaker 3: there for private credit was that depending on the average
Speaker 3: kind of historical ten year IRR is about ten percentage points,
Speaker 3: which sounds appealing, But when you compare to hyat public
Speaker 3: benchmarks like the Bloomberg Hi index, then what you see
Speaker 3: is that public market equivalent or direct out of measures
Speaker 3: comparing private to public performance are all kind of in
Speaker 3: favor of the high index. There is no outperformance relative
Speaker 3: to yield public bonds, which comes to tell you that
Speaker 3: private credit is, at least historically has been a way
Speaker 3: to get exposure to yield below investment grade credit. Does
Speaker 3: private credit provide additional diversification beyond what's available in the
Speaker 3: public market? Yes, absolutely. There are different bonds out there,
Speaker 3: generally different issuers going for the private route versus public,
Speaker 3: So there are some diversification benefits if you want to
Speaker 3: add private credit to your public exposure. But of course
Speaker 3: private comes with a lot of caveats and challenges, one
Speaker 3: of which you mentioned very important ones for US prices,
Speaker 3: frequent updates of prices, reliability of prices there it's not
Speaker 3: by accident, it's called private. Also, lack of adequate diversification
Speaker 3: because ultimately we cannot all own parts of all private companies,
Speaker 3: you cannot get the full diversification you get in public
Speaker 3: markets if you want to. And as a result, I think, well,
Speaker 3: it will be interesting to see how private interesting private
Speaker 3: credit develops, because there is kind of a an evergreen
Speaker 3: value proposition for private It is has its own economic
Speaker 3: function out there, but not everyone probably suited for an
Speaker 3: investment in private people who might have short term immediate
Speaker 3: liquidity needs, etc. Who cannot have a long horizon and
Speaker 3: a for not to touch that part of money for
Speaker 3: a long term might not be prepared for private investments
Speaker 3: or well suited for private investments. In terms of information available,
Speaker 3: definitely much less information available easily, and I think that's
Speaker 3: why even in the when you look at buyouts, another
Speaker 3: segment of the private market trades in the secondary market,
Speaker 3: which attempts to mimic a public market right in terms
Speaker 3: of getting some valuations for buyout stakes, et cetera, you
Speaker 3: typically see haircuts of like ten fifteen percent, which speaks
Speaker 3: to prices might not be as reliable they are as
Speaker 3: they are in public markets.
Speaker 1: We've had some guests recently talk about a two hundred
Speaker 1: basis points premium in private markets against public I'm assuming
Speaker 1: that mostly talking about loans there, but sounds like what
Speaker 1: you're saying is that there is no relative value in
Speaker 1: private and actually there's better risk just to return in
Speaker 1: hial bonds versus private debt. Is that is that correct?
Speaker 3: So it's very important what you compare private.
Speaker 2: Too.
Speaker 3: Many people might compare private to the Global or us
Speaker 3: ag I Investment Grade Index. There you would see our
Speaker 3: performance if you compare to Hyatt, you don't see our performance. Yes,
Speaker 3: and it's kind of similar. On the private equity side,
Speaker 3: many managers like to compare themselves to the S and
Speaker 3: P five hundred. In our opinion, that's not an adequate
Speaker 3: benchmark public benchmark. For private equity, you want to probably
Speaker 3: take a look at well designed small happiness is small growth,
Speaker 3: small value. And then the conclusion is very similar to
Speaker 3: what we discuss for private credit. So it really matters
Speaker 3: what you compare yourself to.
Speaker 1: And also you mentioned it, you know, it really depends
Speaker 1: on the kind of investors. Not suitable for everyone, but
Speaker 1: you know you're an ETF shop. There are ETFs now
Speaker 1: for private credit. What do you make of that?
Speaker 3: We shall see, let's put it that way. In terms
Speaker 3: of public bond ets, we see a lot of demand
Speaker 3: for those. Obviously the largest ones are index focused, but
Speaker 3: we now see growing demand for a kind of what
Speaker 3: the types of ETFs with delivery dimensional systematic active, both
Speaker 3: on the bond and on the equity side. We are
Speaker 3: actually the largest systematic active ETF manager out there with
Speaker 3: one hundred and seventeen plus a billion dollars in active ETFs.
Speaker 3: We have forty one ETFs right now, thirty one on
Speaker 3: the equity side, ten on the fixed income side, and
Speaker 3: of the ten I was looking, which are kind of
Speaker 3: all of them have positive flow netflows this year and
Speaker 3: last year broadly used and the most used ones are
Speaker 3: our US core fixed in committef along with global corporals
Speaker 3: ultra short. So kind of a variety of segments where
Speaker 3: people like to use a thoughtful, systematic yet active approach.
Speaker 3: And I think for for focusing on public corporate bond
Speaker 3: of public market bond markets, not just corporate government, corporate munis,
Speaker 3: even mortgage backed securities. I think the ETF rapper is
Speaker 3: a good wrapper, but of course even the ETF rapper
Speaker 3: has to be well implemented. I think this is something
Speaker 3: that I'm not sure your listeners have been aware of,
Speaker 3: but there are some papers in the academic literature that
Speaker 3: have looked at the baskets for fixed income ETFs in
Speaker 3: the last years and suggests that looking primarily at index
Speaker 3: of fixed income baskets that authorized participants, those that come
Speaker 3: to the ETF you sure to create and redeem baskets,
Speaker 3: create more shares of an EF essentially have been getting
Speaker 3: an advantage in terms of pricing of these or picking bonds,
Speaker 3: delivery which bonds to deliver some advantage over the issuer.
Speaker 3: So when we set off our active ETFs, we are
Speaker 3: very cautious to make sure that there's no all want
Speaker 3: taking advantage of us in in that space of activitfs
Speaker 3: where you have to kind of create baskets every day
Speaker 3: throughout the day, negotiate baskets with APS, and we developed
Speaker 3: a lot of infrastructure and criteria how to create our
Speaker 3: baskets and in a typical dimensional men are also a
Speaker 3: lot of infrastructure to track our execution of baskets over time.
Speaker 3: So when we compare the bonds that we eventually bought
Speaker 3: through a creation process from APS versus the bonds we
Speaker 3: discarded and the bonds that kind of we started with
Speaker 3: in the initial basket, we we don't find any underperformance,
Speaker 3: no evidence of underperformance of what we bought versus what
Speaker 3: we started with or what we discarded. Uh to the
Speaker 3: point that we don't see APS pushing prices up to
Speaker 3: deliver to acquire the securities we got, or to demonstrate
Speaker 3: any informational advantage. And I think going forward, people shure
Speaker 3: and hopefully will pay more attention to basket creation, because
Speaker 3: this is where you might be leaving money on the
Speaker 3: table if you're not careful enough.
Speaker 1: You're right. The ETFs in credit have just become so
Speaker 1: huge and so influential, not just for retail investors, also
Speaker 1: for institutional investors using them to trade. But I'm interested
Speaker 1: in in, you know, the active elements of that, because
Speaker 1: the passive guys just tracking the index sing to be
Speaker 1: doing just fine and they're probably very low cost. So
Speaker 1: what's the edge you get from being active in this?
Speaker 3: Yeah, And I love how you mentioned the first thing
Speaker 3: people think about when when indexing comes to mind is cost,
Speaker 3: low cost. And I was looking at kind of the
Speaker 3: two largest ETFs out there are index ETFs. We all
Speaker 3: know probably they are tickers and they're about three based
Speaker 3: sports in expense ratio. And when people see that, they're like,
Speaker 3: they're they're cheap, Like, why why should I go with
Speaker 3: anything else? Well, because you can, again based on rigorous
Speaker 3: academic research and top FOO implementation actually outperforms systematically benchmarks
Speaker 3: net A fees and expenses over the long term. And
Speaker 3: one of our the most popular flagship strategy of dimensional
Speaker 3: in mutual fund format code investment grade portfolio in each
Speaker 3: format code DFCF core fixed income. Both of those, the
Speaker 3: longer one, the mutual font format since inception has outperformed
Speaker 3: the same benchmark that the two biggest index city have struck,
Speaker 3: the Bloomberg Us Act by thirty five to forty basis
Speaker 3: sports per year NETA, FeAs and expenses over the last
Speaker 3: ten years and since inception back in twenty eleven. And
Speaker 3: I think this speaks to the point that there is
Speaker 3: something you can do better. You can than indexing by
Speaker 3: focusing on current information in for rates, to think about
Speaker 3: where to position new flaws, where to kind of pursue
Speaker 3: higher expector returns, how to control costs, how to manage
Speaker 3: risks in the portfolio. And these are areas where the
Speaker 3: indexing just falls behind and leaves money on the table
Speaker 3: because it's index. Our index approaches are simply thinking about
Speaker 3: sampling from the huge index universe, but then not taking
Speaker 3: into account real time market information as we discussed, to
Speaker 3: identify where the best opportunities highest expected returns are in
Speaker 3: a systematic manner, or how to monitor credit quality on
Speaker 3: a real time basis, or how to seek for being
Speaker 3: flexible in what bonds to buy and sell to get
Speaker 3: the best trading costs possible for the index approach, the
Speaker 3: tradeoff is always tracking error versus costs or taxes depending
Speaker 3: on the wrapper. For us, that's not the right trade off.
Speaker 3: As we talk, tradeoffs are very important, but the right
Speaker 3: tradeoff should be expected returns versus costs and risks.
Speaker 2: And then on the return side, I mean could investor
Speaker 2: expect from those Well, what.
Speaker 3: I mentioned is for our investment great portfolio here in
Speaker 3: the US has outperformed the Bloomberg Us Act by thirty
Speaker 3: five to forty basis points. Again native fees and expenses,
Speaker 3: So forget about industry, the feed differential, expense oration differential
Speaker 3: versus the bloomberg Us Act over the last ten years
Speaker 3: since inception almost fifteen years now. So I think it's
Speaker 3: a it's a good trade off for many advisors and
Speaker 3: many advisors in their end clients, many institutional clients. And
Speaker 3: as a result, we've seen kind of growing interest in
Speaker 3: systematic active fixed income. I think in fixed income, more
Speaker 3: people are aware of the rigidities and flaws of indexing.
Speaker 3: As a result, more more people know about kind of
Speaker 3: the maturity cutoff where everybody has to sell one year
Speaker 3: or once a bond is down organded, everybody has to
Speaker 3: kind of sell it out of their portfolio because it's
Speaker 3: leaving the index for investment BRAN and we still see
Speaker 3: meaningful costs around those transitions. So people are open to
Speaker 3: something better than indexing. But at the same time, people
Speaker 3: often get disappointed with the inability of traditional active to
Speaker 3: consistently systematically outgas the market, and as a result are
Speaker 3: looking for an approach. It doesn't claim to have a
Speaker 3: crystal ball, but see systematically based on science to deliver
Speaker 3: with the understanding that it won't necessarily outperform the market
Speaker 3: day in and day out, but over the long term,
Speaker 3: based on academic principles and research, it should deliver higher
Speaker 3: expected returns.
Speaker 1: The strategy kind of outline quality, you know, transparency, liquidity,
Speaker 1: all this stuff. That's basically what everybody wants right now,
Speaker 1: and there's just so many people chasing it. How do
Speaker 1: you get your edge in that? I mean, how do
Speaker 1: you get your allocation? How do you kind of muscle
Speaker 1: in when there's so much you know, pressure to buy,
Speaker 1: there's so much capital to allocate. You know, you have
Speaker 1: to be selective obviously, but what's what's the strategy in
Speaker 1: terms of just like getting enough assets to buy.
Speaker 3: Yeah, how do you execute efficiently right now? If other
Speaker 3: people are also focusing let's say, only government bonds or
Speaker 3: higher quality in a very short term, I say, go
Speaker 3: back to kind of the key principles of our value
Speaker 3: ads in portfolio management and training, being flexible. We believe
Speaker 3: that they measure that optionality. Flexibility adds value as a result.
Speaker 3: If you are starting the day with one hundred or
Speaker 3: two hundred eligible bonds to buy in a given portfolio,
Speaker 3: or a thousand for that matter, being able to walk
Speaker 3: away from a potential trade because you know that there
Speaker 3: are similar bonds with similar characteristics that you might be
Speaker 3: equally happy to buy today. That is what helps us
Speaker 3: in today's environment where others might be kind of looking
Speaker 3: for similar type bonds at the same time. Uh, The
Speaker 3: ability to be flexible, be patient, and not chase an
Speaker 3: individual specific bond. As we discussed earlier, many bonds don't
Speaker 3: trade on a given day, so if you are chasing
Speaker 3: as particular, body are likely to push prices for that bond.
Speaker 3: Whereas if you are flexible, you if you view multiple
Speaker 3: bonds is substitutes for each other when you go to
Speaker 3: buy or sell. That gives you more flexibility, and as
Speaker 3: I said, this flexibility ultimately gets reflected in better execution.
Speaker 3: We've been monitoring that for years and we see kind
Speaker 3: of year in and year out as paying off, and
Speaker 3: especially kind of in April, as I mentioned, our relative
Speaker 3: trade price adventage was higher than in the in the
Speaker 3: previous three months of the year. Again, when periods are
Speaker 3: highly votile, this is what we see both inequities and
Speaker 3: fixed income. A lot of people tend to panic, the
Speaker 3: many immediacy try to kind of rush to market, and
Speaker 3: people who are flexible, who are long term focused and discipline,
Speaker 3: tend to benefit in those environments.
Speaker 1: Is there a way that you can get an edge
Speaker 1: over the competition when we hear a lot of people
Speaker 1: talking about CMBs, about MBS, about structured, about asset based finance,
Speaker 1: but all these other things that they're trying to get
Speaker 1: and you know, generate alpha from in terms of you know,
Speaker 1: standing out when it comes to doing better than the
Speaker 1: index and best than everyone else for returns. How do
Speaker 1: you get your edge in.
Speaker 3: Mortgage back securities? I should have mentioned that earlier. We
Speaker 3: do invest now in mortgage back securities as well in
Speaker 3: some of our strategies. I think it's a fascinating asset class.
Speaker 3: But we started investing in mortgage back securities only only
Speaker 3: in twenty twenty. Again, if you track our evolution because
Speaker 3: transparency price transparency arrives to the NBS and TBA market
Speaker 3: in twenty eleven twenty twelve, when those transactions became mandatory
Speaker 3: to report to trades, similar to what happened to corporate
Speaker 3: bonds about ten years earlier. And so once we accumulated
Speaker 3: enough price information and study or able to study the
Speaker 3: MBSTBA market historically and essentially see that the same framework
Speaker 3: for what drives expected returns in corporate government immuni bonds
Speaker 3: can be applied. It is well supported in the data
Speaker 3: for mbstbas. We started investing in nbs via TBA is
Speaker 3: actually because they are ninety percent of the trading happens
Speaker 3: through the TBA to be the announced derivatives market. And
Speaker 3: we also engage with one of the top experts of
Speaker 3: MBS in academy, again going back to our strong ties
Speaker 3: with academia, Professor Sung from John Hopkins Carry Business School,
Speaker 3: and we hold together a paper on the drivers of
Speaker 3: Expected Returns of MBS, which essentially says, again kind of
Speaker 3: field and roll down, but customized to the world of
Speaker 3: MBS is with the prepayment kind of potential, there still
Speaker 3: are the main drivers of differences in expected returns within MBS,
Speaker 3: and this is kind of where we seek to have, say,
Speaker 3: seek out performance within that spectrum right now in our
Speaker 3: portfolios that invests in MBS tvas is basically by identifying
Speaker 3: tvas with higher expected returns and allocating more to them
Speaker 3: within our TVA portfolios. So again going back to having
Speaker 3: a robust, academic scientific framework for how to seek systematically
Speaker 3: higher returns and then applying in a very thoughtful manner,
Speaker 3: because even though TBAs are the second most liquid market
Speaker 3: out there after US treasurers, in case your listeners didn't
Speaker 3: know even there, you have to be very thoughtful about execution.
Speaker 3: You cannot be just demanding a particular TBA contract today
Speaker 3: in huge qualities and expect that you're not going to
Speaker 3: have any impact on the market.
Speaker 1: And for those out there, I don't know what TBA is.
Speaker 1: What is it?
Speaker 3: It is an abbreviation for to be announced and it's
Speaker 3: a very interesting mechanism. Maybe we should spend like a
Speaker 3: couple of minutes just explaining it to people to bring
Speaker 3: more liquidity and lower execution costs to this mortgage backed
Speaker 3: securities market. So when I get got a mortgage on
Speaker 3: my house, and I'm sure you guys have probably mortgages
Speaker 3: on your house. Is the band that lends the mortgage
Speaker 3: typically doesn't hold on to death. Mortgage sends sells it
Speaker 3: to one of the three agencies out there in the US.
Speaker 3: This is specific to the US market, and those agencies
Speaker 3: package many mortgages, typically of the same term, so let's
Speaker 3: say thirty or fifteen year with similar coupons, payments, so
Speaker 3: interest rates on a mortgage, and they pass them to
Speaker 3: investors out there and securitize that. And as you can imagine,
Speaker 3: every month there is a new potentially package out there
Speaker 3: from one of the three agencies with different terms, with
Speaker 3: a different coupon. Lots of packages training issued over many,
Speaker 3: many vintages, So the market is quite dispersed for mortgage
Speaker 3: backed securities if you are One way to bring transparency
Speaker 3: to that market is actually to create an instrument that
Speaker 3: aggregates a lot of those characteristics, and that's what the
Speaker 3: TBA delrivative does. It basically says, I promise to deliver
Speaker 3: to you in a month or in two or three months,
Speaker 3: a package of mortgages that is issued by one of
Speaker 3: the three agencies that has this coupon let's say five
Speaker 3: point five percent and has thirty year term, oh you know,
Speaker 3: up until a few days before delivery, is just those
Speaker 3: three characteristics. And by limiting the information exchanged across market
Speaker 3: participants to those three characteristics, it makes the market much
Speaker 3: more liquid. And as a result, tvas are very very
Speaker 3: cost efficient to trade and a highly highly liquid market.
Speaker 3: And one little interesting nugget on that is, when we
Speaker 3: started researching MBS and tvas, I was surprised to see
Speaker 3: that one of my huge mentors in life, can French,
Speaker 3: professor Ken French from Dartmouth College, he actually had a
Speaker 3: paper on tvas or related back in the day where
Speaker 3: they made a comparison basically with diamonds traded in a
Speaker 3: black bags in transparent bags similarly to reduced kind of
Speaker 3: informational advantures or cross market participants in increased liquidity of
Speaker 3: trading diamonds. And I found that comparison very fascinating.
Speaker 2: Maybe to talk a little bit about about risk, I
Speaker 2: mean we're you know, fixing of investors and or analysts
Speaker 2: and always worry about what could go wrong? But what
Speaker 2: are the key risks that you see right now in
Speaker 2: the market.
Speaker 3: I'd say they mentioned when we think about key risks
Speaker 3: in portfolio, we always think the number one risk in
Speaker 3: any portfolio is probably concentration and the risk that your
Speaker 3: portfolio will be driven down by the underperformance or default
Speaker 3: of particular UH issuer. And so from that perspective, the
Speaker 3: best and the best way to address that risk of
Speaker 3: concentration is diversification. Diversification across issuers, issues, garanteurs, UH sectors, industries,
Speaker 3: countries of visions if if allowed, and currency of visions
Speaker 3: if allowed. I think that's kind of always number one.
Speaker 2: Uh.
Speaker 3: Think about concentration, then liquidity obviously, how liquid are the
Speaker 3: bones you're holding? Can you relatively quickly trade them around?
Speaker 3: And of course when you're running an ITA for a
Speaker 3: mutual fund, that's top of mind to have. Also kind
Speaker 3: of a good pocket of liquidity in a portfolio, even
Speaker 3: if it's long term, that can be turned around and
Speaker 3: satisfy redemptions for example a quick notice. And after that,
Speaker 3: I would say it's just generally the understanding that for us,
Speaker 3: the other risk is obviously that the academic kind of
Speaker 3: driven relationships in the data that we are pursuing turnspread
Speaker 3: predicting turn premium credit spread predicting credit premiums might not
Speaker 3: manifest themselves in the predicted by consistent with theory manner
Speaker 3: every day, every month, every year, you might have a
Speaker 3: period of one, two, three years underperformance because terms spread,
Speaker 3: why don't but premium dinner wide after that? Instead it
Speaker 3: narrowed and so building a roll bust well diversified portfolios
Speaker 3: that even if those relations we are pursuing, based again
Speaker 3: on academic theory and research, do not show up in
Speaker 3: the data over a given period of time, you're still
Speaker 3: left with a very good portfolio to hold, and applies
Speaker 3: to both our equities and our fixing of so broadly
Speaker 3: diversified systematic approach that will deliver kind of minimum costs
Speaker 3: the good portfolio to hold regardless of what the future brings.
Speaker 1: Do you worry it's all about the risks that might
Speaker 1: be brewing in private credit in terms of you know,
Speaker 1: the risks that you cannot see that building your potential defaults.
Speaker 1: There's a lot of payment and kind a lot of
Speaker 1: amendments and things you can't see. But also essentially it's
Speaker 1: taking away supply that maybe further distorts pricing in the
Speaker 1: public markets.
Speaker 3: Whether I worry or not, I think that all of
Speaker 3: those potential developments are there. The word is that actual
Speaker 3: investors in the marketplace have are reflected in kind of
Speaker 3: their trading decisions, bias and cells of different types of
Speaker 3: bonds out there. If edything, some people might get disappointed with,
Speaker 3: again some of the attributes of private credit or private
Speaker 3: in general, if they are not going with enough kind
Speaker 3: of research on what that type of investment can representing
Speaker 3: their portfolio and in their investment experience. And I think
Speaker 3: we all need to also kind of appreciate even more
Speaker 3: the benefits of public markets, the transparency that we talked
Speaker 3: about a lot today that gives us any immediacy in
Speaker 3: liquidity that are instrumental to most people's needs when it
Speaker 3: comes to investing.
Speaker 1: And as you say, your sort of more scientific approach
Speaker 1: is quite different to a lot of guests we have
Speaker 1: on this show. If you had to kind of say
Speaker 1: how you most contrarian on credit, I mean, how would
Speaker 1: you describe that? Are you contrarian at all? And if so,
Speaker 1: how would you characterize that?
Speaker 3: I would say that our focus, our location to credit
Speaker 3: depends on the current curves of their spreads and curves.
Speaker 3: So in periods like now, where credit spreads are not
Speaker 3: as wide as they have been historically, we are a
Speaker 3: little bit less focused on credit and more on governments,
Speaker 3: so you could say a little bit more focused on government.
Speaker 3: And then in you know, in periods or in areas
Speaker 3: of the market where we see steeper credit curves, so
Speaker 3: intermediate segment us for example, generally steeper than short term
Speaker 3: within a credit strategy would be kind of going longer
Speaker 3: corporate bonds and less shorter corporate bonds, So depends on
Speaker 3: market conditions. How have your corporate bonds?
Speaker 1: Great stuff, Savina Resova, co, Chief investment Officer and global
Speaker 1: head of Research at Dimensional Fund Advisors. Has been a
Speaker 1: pleasure having you on the credit edge. Many thanks, thank you,
Speaker 1: and of course we're very grateful to Jehan ef Coupin
Speaker 1: from Bloomberg Intelligence. Thank you so much for joining us today.
Speaker 1: Welcome for even more credit market analysis and insight. Read
Speaker 1: all of Jean Eve Coupin's great work on the Bloomberg terminal.
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