Speaker 1: Welcome to Inside Active, a podcast about active managers that
Speaker 1: goes beyond sound bites and headlines and looks deeper into
Speaker 1: their processes, challenges and philosophies and securitance selection. I'm David Cohne.
Speaker 1: I'd be Mutual fund and Active Research at Bloomberg Intelligence Today.
Speaker 1: My co host is Mike Casper, sector and small cap
Speaker 1: strategist at Bloomberg Intelligence. Mike, thank you for joining me today.
Speaker 2: Thank you, David.
Speaker 1: Well, you and Chris Kane put out a note last
Speaker 1: week talking about applying bi's proprietary b MVP multi factor
Speaker 1: methodology for the small cap Bloomberg two thousand. Can you
Speaker 1: give a brief overview of the methodology and how it's performed.
Speaker 3: Sure, So what we do is we start with the
Speaker 3: Bloomberg two thousand index. That's kind of roughly equivalent to
Speaker 3: the Russell two thousand. It's just mark a cap weighted though,
Speaker 3: so there are some slight differences on the edges. But
Speaker 3: what we do is we take that universe and we
Speaker 3: apply a profitability screen to it. It's awfully difficult to
Speaker 3: kind of make conclusions on fundamentals without having such a screen,
Speaker 3: given that about a third of stocks in the Russell
Speaker 3: two thousand or in small caps in general aren't profitable
Speaker 3: at the moment, So we take that profitability screen and
Speaker 3: that whittles down the universe a little bit further. I
Speaker 3: think as of September we were at about eleven hundred
Speaker 3: constituents left over from the two thousand. When we do that,
Speaker 3: and then we apply our momentum scores on a sector
Speaker 3: neutralized basis. All these factors are on a sector neutralized basis,
Speaker 3: but momentum the average of trailing six and twelve month
Speaker 3: total returns excluding the last two weeks. We apply our
Speaker 3: low volatility factor, our value factor, which four small caps,
Speaker 3: we just look at the trailing twelfth month sales to
Speaker 3: price ratio, and our profitability factor, which is the average
Speaker 3: of trailing twelve month ROE and ROIC, and then the
Speaker 3: top descal of those percentile ranks once we average those out,
Speaker 3: is the final b MVP small cap portfolio. Now a
Speaker 3: little bit of stats before I go into the back
Speaker 3: test result. That results in a little bit higher market
Speaker 3: cap weighting than the B two thousand. For example, so
Speaker 3: the Bloomberg MVP, the media market caps about two point
Speaker 3: eight billion. In that universe with the largest stock about
Speaker 3: eight and a half billion, small stock about two hundred
Speaker 3: and eighty seven million, So the market cap range of
Speaker 3: the B two thousand as a whole as much wider
Speaker 3: the same thing with the Russell two thousand. The media
Speaker 3: market caps about a billion. But onto results, the cumulat
Speaker 3: return for this thing is pretty solid. So back to
Speaker 3: nineteen ninety nine through September twenty twenty four, you're looking
Speaker 3: at percent significantly lower volatility than the Russell two.
Speaker 2: Thousand equal WEIGHTD.
Speaker 3: But what I really like to compa against is the
Speaker 3: only profitable bin in the B two thousand. That annualized
Speaker 3: return is about eleven point eight five percent, so we
Speaker 3: are generating some alpha over that bin using.
Speaker 1: This nice I think this is a great time to
Speaker 1: introduce our guest, Mitch Zach's. He's CEO and principal portfolio
Speaker 1: manager of Zach's Investment Management. Mitch, thank you for joining
Speaker 1: us today.
Speaker 4: David and Michael, it's a pleasure to be here.
Speaker 1: I'd like to start off, you know, just hearing more
Speaker 1: about your career background.
Speaker 4: Sure, I you know, went to school at Yale and
Speaker 4: I joined Lazard Freyer and Mergers and Acquisitions as an
Speaker 4: analyst I left the analyst program to join Zach's Investment Research.
Speaker 4: At the time, Zach's and we founded a division of
Speaker 4: Zach's Investment Research, which was a money management subsidiary, a
Speaker 4: wholly owned money management subsidiary. At the time I joined,
Speaker 4: we had roughly fifty million dollars in assets under management,
Speaker 4: and over the past twenty some odd years, you know,
Speaker 4: twenty odd plus years actually at this point in time,
Speaker 4: we've been able to grow the firm from around fifty
Speaker 4: million dollars in asset to a little bit over nineteen
Speaker 4: billion dollars in assets under management and model delivery and advisement.
Speaker 4: So you know, that's kind of my background. I've been
Speaker 4: working with quantitative equity portfolio strategies my entire career, and
Speaker 4: I've designed most of the asset management strategies that we
Speaker 4: implement at Zach's. Zach's Investment Management's a wholly owned subsidiary
Speaker 4: of Zach's Investment Research. Zach's Investment Research is the second
Speaker 4: largest provider of independent investment research in the country, and
Speaker 4: our contribution to finance was that we created the concept
Speaker 4: of the quarterly consensus earnings estimate before Za's came around.
Speaker 4: What people were doing was pretty much looking at how
Speaker 4: earnings evolved on a year over year basis, looking at
Speaker 4: how that earnings growth compared to sort of a trend
Speaker 4: line analysis based on historical earnings growth, and saying, well,
Speaker 4: earnings have been growing at you know, ten percent, in
Speaker 4: at twelve percent year over year earnings growth, it was
Speaker 4: a good quarter. What we started doing is we created
Speaker 4: this concept of the quarterly consensus earnings estimate, where we
Speaker 4: took to the cell side earnings estimates by all the
Speaker 4: analysts following these companies, and we created a consensus and
Speaker 4: then when a company would report earnings, it would be
Speaker 4: compared to what Wall Street expectations were. If the earnings
Speaker 4: were greater than Wall Street expectations, it would be deemed
Speaker 4: a earning surprise, and if they were less than Wall
Speaker 4: Street expectations, it would be a negative earning surprise. And
Speaker 4: we started to look at this data we created and
Speaker 4: started to say, well, how can we use this data
Speaker 4: to effectively manage money? And what we found to be
Speaker 4: the most important use of the data is not to
Speaker 4: look at the year over year earnings growth and instead
Speaker 4: to focus on how the earnings estimates are changing over
Speaker 4: time and what we found to be the case is
Speaker 4: that there's some degree, it's a reasonably strong degree given finance,
Speaker 4: you know, time series metrics of earning of serial correlation
Speaker 4: with earnings estimate revisions, and that became the basis of
Speaker 4: some of our proprietary models that we then started the
Speaker 4: asset management firm with.
Speaker 1: So you mentioned, you know, earnings revision. Can you, I
Speaker 1: guess speak to you know how that affects your investment philosophy?
Speaker 1: And you know, I'm thinking, actually, you know your investment
Speaker 1: process specifically for the ZACH small cap or fund.
Speaker 4: Sure, what we're What we found to be the case
Speaker 4: is that companies that have received upward earnings estimate revisions
Speaker 4: in the past are more likely to receive upward earnings
Speaker 4: estimate revisions in the future. And if you own a
Speaker 4: group of companies that have received upward earnings ESTEMA revisions
Speaker 4: in the past, you're roughly about sixty percent more likely
Speaker 4: to receive upward earning cestemer revisions in the immediate future.
Speaker 4: So the first thing I started to do is to
Speaker 4: try and say, well, what if we create a portfolio
Speaker 4: where we simply own all the companies that are receiving
Speaker 4: upward earning customer revisions, we hold them for a certain
Speaker 4: period of time, and then we rebalance the portfolio. And
Speaker 4: what happens is if you kind of apply that sort
Speaker 4: of very very structured approach, you tend to have a
Speaker 4: very high degree of turnover in the portfolio. Roughly sixty
Speaker 4: seventy percent of the companies that are receiving upward earning
Speaker 4: cestemer revisions at the beginning of the month are not
Speaker 4: receiving upward earning customary visions over the end of the month,
Speaker 4: So there tends to be a high degree of turnover.
Speaker 4: You also tend to get a very very high degree
Speaker 4: of sector concentration, so you not only see a high
Speaker 4: degree of turnover, you see a level of sector concentration
Speaker 4: that increases sort of the volatility and tracking error of
Speaker 4: the portfolio relative to the benchmark. So what we started
Speaker 4: to do is saying, well, how can we control the
Speaker 4: turnover and how can we control the sector exposure to
Speaker 4: generate a return that's more in keeping with the benchmark.
Speaker 4: And that's what I've been doing for many years, and
Speaker 4: in the ZAC small cap core process as a mutual
Speaker 4: fund CIX, which is a very small mutual fund which
Speaker 4: actually kind of helps us in terms of being able
Speaker 4: to move in and out of these positions. We're trying
Speaker 4: to control the turnover so that the turnover is around
Speaker 4: one hundred percent per year, and we're trying to control
Speaker 4: the tracking error as much as we can through optimization
Speaker 4: to try and keep the risk in line with our
Speaker 4: benchmark of the Russell two thousand.
Speaker 3: Basically, now I give my whole feel at the beginning
Speaker 3: of this about how profitable companies tend to outperform the
Speaker 3: egaloid to benchmark. It sounds like we're kind of arriving
Speaker 3: at similar things you with earning s revision mean with
Speaker 3: profitable stocks. When you look at earning servision, do you
Speaker 3: only select profitable companies or do you care if it's
Speaker 3: going from unprofitable to less unprofitable.
Speaker 4: What we're looking for are changes in the earnings estimate
Speaker 4: revision so that they're positive. So we're looking for sort
Speaker 4: of four factors, agreement to the extent to which multiple
Speaker 4: analysts are revising their earning estaments in the same direction, magnitude,
Speaker 4: the size of those estimate revisions upside, where the most
Speaker 4: accurate or recent earnings estaments are coming in relative to
Speaker 4: the consensus, and the earning surprise, the frequency and magnitude
Speaker 4: of earning surprises that have occurred in the process that
Speaker 4: we're implementing. We're using the Russell two thousand universe as
Speaker 4: the initial universe of selection, and we're adding to at
Speaker 4: any company that's in our current portfolio that may have
Speaker 4: been removed from the index at some point in time.
Speaker 4: So the union of those two sets is really our basis.
Speaker 4: What I will say is that companies that are getting
Speaker 4: negative earnings are a little bit less likely to get
Speaker 4: positive earnings estimate revisions because they're sometimes in some sort
Speaker 4: of growth phase where the management is spending money for
Speaker 4: some sort of potential you know, jackpot in the future,
Speaker 4: so to speak. So they might be a biotech company
Speaker 4: where the management has decided, hey, we're going to continue
Speaker 4: to spend money to engage in the drug development and
Speaker 4: our hope is that it gets approved at the end
Speaker 4: of the entire process. So generally, those companies that are
Speaker 4: kind of in the development phase that are based on
Speaker 4: massive capital expenditures to sort of capture a market will
Speaker 4: likely not get upward earning cestmer visions, And in some
Speaker 4: of those instances, it's possible they get downward esimate revisions,
Speaker 4: but they're getting closer to their sort of goals in
Speaker 4: terms of growth that the stock price will respond positively.
Speaker 4: So they are two separate ideas. One idea is, hey,
Speaker 4: can you look at companies that have positive earnings to
Speaker 4: do companies with positive earnings or positive expected earnings outperformed
Speaker 4: companies with negative earnings. And that has historically been the case,
Speaker 4: but that's been widely disseminated amongst managers. So I'm not
Speaker 4: positive that's going to be completely the case over time.
Speaker 4: I think it might be a little bit better instead
Speaker 4: of sort of throwing out you know, I guess you know,
Speaker 4: roughly thirty percent of the Russell two thousand to instead say, okay,
Speaker 4: are these companies? These companies are expected to lose money,
Speaker 4: but they expected to lose less money this quarter? Are
Speaker 4: they expected to lose less money over the last month
Speaker 4: because analysts are revising their earnings estimates upward. And what
Speaker 4: I've actually anecdotally found to be the case is companies
Speaker 4: that move from a nonprofitable sort of scenario where they're
Speaker 4: losing money to companies that are going to generate positive
Speaker 4: earnings tend to maybe not all the time, but have
Speaker 4: a potential for very very strong returns, and you don't
Speaker 4: want to necessarily remove those from the portfolio.
Speaker 1: That makes sense. You know, I'm familiar with Zach's investment research,
Speaker 1: and you know kind of you know Zach's rank and
Speaker 1: you know strong buy stocks. Does it kind of follow
Speaker 1: the portfolio kind of follow something similar where it only
Speaker 1: includes like strong buy or buy stocks according to those formulas.
Speaker 4: Yeah, in zsci X, which has been performing relatively well
Speaker 4: over the last you know, a couple of years. Here,
Speaker 4: what we're doing is we're combining an estimate revision model
Speaker 4: with a model that focuses on quality. We're using that
Speaker 4: sort of alpha model as an input to an optimization
Speaker 4: routine to generate a buy, a hold, and sell list
Speaker 4: that we then evaluate and pretty much implement. But there
Speaker 4: is a basis in the alpha model looking at companies
Speaker 4: that are likely to receive upward earnings estimate revisions in
Speaker 4: the future. But you have to remember that we again,
Speaker 4: the pure estimate revision universe has a high degree of turnover,
Speaker 4: and what we're trying to do is use earning sest
Speaker 4: revisions as an alpha source and then control the turnover
Speaker 4: and control the sector exposure. So the overall risk of
Speaker 4: the portfolio is in line with the Russell two thousand benchmark.
Speaker 4: So to answer the question, what we're doing is we're
Speaker 4: using earnings estimate revisions along with another model in a
Speaker 4: multi factor model, but we're using that as an input
Speaker 4: to optimization that then can identify companies. So it's a
Speaker 4: subset of that group that might be potential by candidates,
Speaker 4: and we might even go outside of that group if
Speaker 4: the optimization indicates that adding that position could conceivably reduce
Speaker 4: tracking error.
Speaker 1: Okay, so you know, if you're starting at this universe,
Speaker 1: you know, you know, I know the four factors of
Speaker 1: zach Ring. So that is, you know, something that's just
Speaker 1: kind of at the very beginning, is what you're looking at.
Speaker 3: Now, are there any sectors that you find particularly compelling
Speaker 3: at the moment or that are being flagged for overweights
Speaker 3: right now?
Speaker 4: What I've found to be the case over time is
Speaker 4: that sector risk control is less effective than looking at
Speaker 4: projected tracking error relative to a benchmark. So what happens
Speaker 4: is if you focus on sort of sector exposure, what
Speaker 4: tends to happen is there'll be companies that are classified correctly.
Speaker 4: They are companies that are misclassified based upon their sector.
Speaker 4: But there are companies that will be classified correctly based
Speaker 4: on their sector, but they will move like a company
Speaker 4: that is outside of that sector. So, for instance, right now,
Speaker 4: there are companies that are construction companies that are helping
Speaker 4: construct sort of cloud computing centers, helping with construct infrastructure
Speaker 4: on semiconductor equipment, manufacturing plants, and things of that sort,
Speaker 4: and these companies will be correctly classified as construction companies.
Speaker 4: They build things, they issue debt, they use the debt
Speaker 4: to buy to buy land to build things, and they
Speaker 4: sell the they sell their what their access or they
Speaker 4: sell their effective use to a company that needs to
Speaker 4: use that type of building or that type of source.
Speaker 4: But in terms of their contribution to risk, they behave
Speaker 4: much more like semiconductor companies than construction companies. So I
Speaker 4: tend not to try and think from a top down perspective.
Speaker 4: I tend to want to think from a bottom up perspective.
Speaker 4: And what we're looking for when we do do some
Speaker 4: qualitative oversight in some of our other strategies is we're
Speaker 4: looking for lack of crowding in the market. So we
Speaker 4: don't want to look for a individual company where there's
Speaker 4: a tremendous amount of information or focus from either the
Speaker 4: media or from investors on what the outcome of or
Speaker 4: how that company is evolving over time. But in terms
Speaker 4: of like if you had to pin me down in
Speaker 4: terms of sectors, I think industrials are looking relatively interesting
Speaker 4: at this point in time.
Speaker 1: Kind of want to move to a slightly different topic, actually,
Speaker 1: market caps something that I've kind of been looking at recently,
Speaker 1: where if you think of the traditional dollar value of
Speaker 1: what one considers a small cap, you know, up to
Speaker 1: about two billion. I've been noticing a lot of mutual
Speaker 1: funds holding much larger stocks. I know, for this particular one,
Speaker 1: I think about half the portfolios in midcaps, you know,
Speaker 1: which is, you know, much less than what I've seen.
Speaker 1: Some small cap funds are even holding large caps. So
Speaker 1: I'm just asking you know, for you is it Do
Speaker 1: you think this is due to small companies growing into
Speaker 1: midcaps or just they're being less available small cap companies.
Speaker 4: I think that if you look at the companies right
Speaker 4: now that are getting upward earning cestemer visions, they tend
Speaker 4: to be more mid cap companies. If you look at
Speaker 4: various quality metrics that we're combining with the estimate revisions,
Speaker 4: it also tends to bias more towards MidCap companies. And
Speaker 4: going back to I think Michael said, if you look
Speaker 4: at those companies that are having a negative earnings, I
Speaker 4: believe that they also correlate with small with much smaller
Speaker 4: cap companies. So we're agnostic in terms of capitalization as
Speaker 4: long as it is within the Russell two thousand universe
Speaker 4: or within our portfolio. But we are looking for companies
Speaker 4: are receiving upward earning cestemer revisions. We are looking for
Speaker 4: companies that have a reasonable score on our quality metric,
Speaker 4: and we are looking for companies that, when added to
Speaker 4: the portfolio, will conceivably provide us with the alpha score
Speaker 4: while reducing the tracking error relative to the benchmark. So
Speaker 4: you know, part of this is that you know, midcaps
Speaker 4: have been performing a little bit better than small caps.
Speaker 4: As you go down capitalization ranges, the number of companies
Speaker 4: that are not quote high quality or good companies tends
Speaker 4: to increase. So as you go down to sub five
Speaker 4: hundred million dollar market cap, as you go down to
Speaker 4: sub two hundred million dollar market cap, the number of
Speaker 4: companies that really shouldn't be public tends to increase. The
Speaker 4: number of companies that are kind of basically completely ignored
Speaker 4: by the market for usually a good reason also tend
Speaker 4: to increase. So if you start using quantitative factors that
Speaker 4: statistically have just gener returns, profitability, momentum, earnings, estimate revisions quality,
Speaker 4: that will always try and sort of push you away
Speaker 4: from smaller cap companies. You also have the case that
Speaker 4: with estimate revision based strategies there tends to be a
Speaker 4: correlation between higher market cap and the amount of analyst coverage.
Speaker 4: So the larger the market cap, not all the time,
Speaker 4: it really depends on the sector and how much in
Speaker 4: vogue that company is, but generally the larger the market cap,
Speaker 4: the more analyst coverage you have. So again I don't
Speaker 4: think it's a function of a qualitative decision. It's more
Speaker 4: a function of the result of the quantitative models we're
Speaker 4: using to try and generate returns. And my guess is
Speaker 4: in the process that was described at the top of
Speaker 4: the hour, there would also be a somewhat of a
Speaker 4: MidCap bias if you're using low volatility and price momentum
Speaker 4: and valuation metric to take a look at things based.
Speaker 1: Okay, do you incorporate valuation metrics at all when you're
Speaker 1: looking at, you know, quality companies, and.
Speaker 4: In this process we're somewhat valuation agnostic, so we're really
Speaker 4: focused on, well, if the company's receiving upward earning estament revisions,
Speaker 4: does adding that company to the portfolio potentially reduce the
Speaker 4: tracking error in other strategies that we runs. As I mentioned,
Speaker 4: we're currently managing a little bit over nineteen billion dollars.
Speaker 4: We do look at valuation as a primary factor that
Speaker 4: we're looking at. My experience has been that as you
Speaker 4: move lower in capitalization, the returns from sort of the
Speaker 4: smaller cap universe tend to accrue a little bit more
Speaker 4: towards technology and more towards some biotech companies because they're
Speaker 4: able to effectively compound over time, go from becoming a
Speaker 4: small cap company to a mid cap and maybe even
Speaker 4: potentially a small large cap company, and that compounded return
Speaker 4: compensates you for the losses that you have with all
Speaker 4: these other companies. So that if you look at valuation
Speaker 4: amongst very very small cap companies, you can run into
Speaker 4: a somewhat of evaluation trap where you find companies that
Speaker 4: are attractively valued and there might be an initial push
Speaker 4: upward as the price book ratio you know, reverts to
Speaker 4: historical means amongst historical levels amongst sort of bank stocks.
Speaker 4: But these companies don't have the ability to compound on
Speaker 4: an annualized basis at a high enough rate to compensate
Speaker 4: you for the smaller cap names that might not perform
Speaker 4: well or might be value traps. So what I found
Speaker 4: to be the case is that valuation metrics seem to
Speaker 4: make more sense and the larger cap that you moved towards,
Speaker 4: and as you move towards smaller cap names, you know,
Speaker 4: you have the traditional Fama French research which shows this
Speaker 4: anomaloust return amongst small cap value names, and I'm not
Speaker 4: quite sure if that has been picked over by the
Speaker 4: market with the amount of capital that's that's looking for
Speaker 4: these opportunities. So if you if you think about value stocks,
Speaker 4: and you're saying, well, do small cap value stocks necessarily
Speaker 4: always out reform small cap growth stocks? You're looking at
Speaker 4: this regression analysis that's saying, well, yes, small cap value
Speaker 4: gives you a bias, But it's possible. We've seen sort
Speaker 4: of a such a flood of capital into the small
Speaker 4: cap space that that thirty five dollars small cap company,
Speaker 4: or that twenty dollars small cap company is now worth
Speaker 4: twenty two dollars, or is now worth thirty six or
Speaker 4: thirty seven dollars, and that would eliminate the annualized return
Speaker 4: from owning those small cap value companies, And anecdotally, that's
Speaker 4: what I happening. So I think that as the market
Speaker 4: becomes more efficient, valuation as a metric sometimes loses some
Speaker 4: of its historical outperformance. And I'm much more comfortable owning
Speaker 4: companies that are receiving upward earning vest revisions and controlling
Speaker 4: the risk through tracking you a relative to the benchmark,
Speaker 4: looking at the PE multiple, looking at cash will multiples,
Speaker 4: just eyeing them to make sure they're in line with
Speaker 4: the benchmark in aggregate, than saying let's try and select
Speaker 4: those companies in the Russell two thousand that have the
Speaker 4: lowest p multiple relative to the industry group that they're
Speaker 4: trading in.
Speaker 2: Basically, So, we.
Speaker 3: Talked a little bit about profitability, and you mentioned that
Speaker 3: it's pretty well disseminated across the market that profitability in
Speaker 3: small caps works, right, And when we were breaking down
Speaker 3: our MVP model across the four factors. We notice that
Speaker 3: pretty much any naive factor that you want to look
Speaker 3: at for the long end of a factor was working
Speaker 3: very well over the long term. Do you think that's
Speaker 3: kind of more of a function of factor crowding given
Speaker 3: your commentary on profitability and everybody kind of be in there,
Speaker 3: or do you think it's more, you know, small caps
Speaker 3: are inefficient or something else.
Speaker 4: What I think is happening is that the nature of
Speaker 4: the small cap market is changing over time. So if
Speaker 4: you take a step back and you say, well, what
Speaker 4: type of company would be going public in the small
Speaker 4: cap space, it would be a company looking for capital
Speaker 4: where the capital is not available through bank financing, so
Speaker 4: they don't have any physical, tangible assets, they can't engage
Speaker 4: in any bank financing. They have an idea, they're going
Speaker 4: to create an online service, they're going to create a
Speaker 4: new generative AI, whatever it is, and they need a
Speaker 4: massive amount of capital to grow. Historically, in the seventies,
Speaker 4: in the eighties, in the nineties, even in the early
Speaker 4: two thousands, these companies would go public at reasonably small capitalizations.
Speaker 4: They would use the capital and grow. Now what is
Speaker 4: happening is that the companies that are capable of growing
Speaker 4: with capital expenditure and growing very largely with capital expenditure,
Speaker 4: are staying private. And the companies that are non profitable
Speaker 4: are not growth companies that have gone public. They're remnant
Speaker 4: public companies that really shouldn't be public and are losing
Speaker 4: money for some purpose, for some reason, because they're under
Speaker 4: competitive pressure. So what I think is happening is there's
Speaker 4: adverse selection within the smaller cap names, within the Russell
Speaker 4: two thousand that the companies that are going public are
Speaker 4: going public because they can't remain private and they can't
Speaker 4: attract financing to grow. So what's happening is that as
Speaker 4: those companies that show up as nonprofitable in the smaller
Speaker 4: cap name, they're more likely to be less likely to
Speaker 4: be able to compound on a very very high basis.
Speaker 4: So it's you have this sort of two tiered market system.
Speaker 4: You have all these remnant companies that are public. They
Speaker 4: shouldn't be public, they are not generating any money, they
Speaker 4: have a low return on equity, they should not continue
Speaker 4: to trade. But there's there and there's no methodology to
Speaker 4: remove it. Meanwhile, the good private companies are staying private
Speaker 4: and coming public at much much higher capitalization levels. So
Speaker 4: a lot of the research showing that hey, small caps
Speaker 4: dramatically outperform over time may be skewed until we kind
Speaker 4: of receive these companies that are going public and can
Speaker 4: grow in the small cap space. But in terms of
Speaker 4: you know, what happens is it's it's very interesting in
Speaker 4: the mark is that as an idea becomes readily disseminated
Speaker 4: and acted upon it, the market changes and it ceases
Speaker 4: to reflect that idea. The biggest example I can come
Speaker 4: up with this sort of the accrural phenomenon, where there
Speaker 4: was this indication that there's an anomaly and maybe the
Speaker 4: anomaly was due to data mining, but everyone was talking
Speaker 4: about accurals. There was all this research done on purls
Speaker 4: and then if you go back and you look, you know,
Speaker 4: five ten years after the crural phenomenon was publicized, companies
Speaker 4: that with attractive accurals are no longer outperforming. And I
Speaker 4: am I would be a little bit wary of going
Speaker 4: into the small cap space. And because this phenomenon where
Speaker 4: unprofitable companies have dramatically underperformed for such a period of time,
Speaker 4: and it's just accepted wisdom that if the company is
Speaker 4: not profitable, it has to underperform the profitable company that
Speaker 4: the market may have adjusted valuations in such a way
Speaker 4: that that no longer holds to be the case going forward.
Speaker 4: And that's why I think it's important to focus on
Speaker 4: the earnings estimate revisions as opposed to necessarily the profitability
Speaker 4: or the valuations.
Speaker 3: Basically, Yeah, and what you're saying about privatization and all
Speaker 3: that is definitely something we've seen in our research.
Speaker 2: I mean, twenty twenty three is the weakest.
Speaker 3: Year for small cap IPOs by our tracking, and it's
Speaker 3: something I'm definitely worried about for the long term. But
Speaker 3: moving on, there's a lot of managers out there, a
Speaker 3: lot of your peers out there that are kind of
Speaker 3: and defend their box type territory. Because the Russell two
Speaker 3: thousand has been underperformed the S and P for so long.
Speaker 3: What do you think since store maybe for twenty twenty five,
Speaker 3: for the Russell two thousand as a whole.
Speaker 4: I mean, I think that the relative valuations of the
Speaker 4: Russell are more attractive than they've been relative to large
Speaker 4: cap companies. I think it comes down to a question
Speaker 4: of whether the productivity gains due to sort of generative
Speaker 4: AI accrue to the largest companies or if it helps
Speaker 4: the smallest companies. What has traditionally happened is that technological
Speaker 4: changes benefit the smaller companies because they're easier to be adopted.
Speaker 4: The larger cap companies tend to be passed over by
Speaker 4: the technological change. And you have this, you know what
Speaker 4: the US economy is tremendously good at is this creative destruction.
Speaker 4: But this does may not hold with software for some reason.
Speaker 4: So if you think about a company like JP Morgan,
Speaker 4: and you think about your favorite small cap bank, and
Speaker 4: you think about which company is going to be better
Speaker 4: able to increase productivity as a result of you know,
Speaker 4: if generative AI becomes as strong as you know, sort
Speaker 4: of optimist are anticipating which company is going to be
Speaker 4: better able to increase productivity. What should be happening is
Speaker 4: the it should help the smaller cap company a little
Speaker 4: bit more. They can do more with fewer people. It's
Speaker 4: easier for them to adopt their procedures, it's easier them
Speaker 4: to change. But what we're seeing in the immediate future
Speaker 4: is it's helping the larger cap companies because they have
Speaker 4: more capital to expand, to create these structures necessary to
Speaker 4: integrate the technological change. And I think the future of
Speaker 4: small cap stocks is dependent upon whether the technological changes
Speaker 4: continue to be monopolized or come benefit the larger companies
Speaker 4: more than the smaller cap companies. And that has to
Speaker 4: do with questions of monopolies from these sort of platform
Speaker 4: type large tech companies and the question of well, why
Speaker 4: aren't the productivity gains, why are they flowing from the
Speaker 4: largest companies to the smallest instead of from the smallest
Speaker 4: companies to the largest, which is how the economy always
Speaker 4: functioned prior to basically two thousand and I think that's
Speaker 4: going to be the key question. The key question is
Speaker 4: whether a small cap company and you don't need many
Speaker 4: of them, you need one or two or three of them,
Speaker 4: can become the next Microsoft, can become the next AOL,
Speaker 4: can become the next Google, or whether that growth is
Speaker 4: going to be segmented to private companies and that any
Speaker 4: technological change is going to be gobbled up at the
Speaker 4: top of the food chain, preventing the small cap companies
Speaker 4: from growing. And I think that's the most important fundamental
Speaker 4: factor driving whether small caps can effectively grow. I mean,
Speaker 4: all these companies, all these elements, they obey sort of
Speaker 4: power laws where you have small numbers of companies generating
Speaker 4: excess returns and compensating you for the majority of companies
Speaker 4: that do not perform well. And so the question of
Speaker 4: whether can small caps outperform, I don't think is a
Speaker 4: valuation question, and you might get a year or two
Speaker 4: years where valuations revert to normal levels in terms of
Speaker 4: relative valuations. The key question is a growth question, and
Speaker 4: can within the small cap universe a company arise that
Speaker 4: can grow or are the sort of monopolistic platforms and
Speaker 4: the integration of new technology so great amongst the large
Speaker 4: cap names that it prevents these smaller companies from growing.
Speaker 4: And I think that is more the fundamental question of
Speaker 4: whether small caps can regain their historical annualized return levels.
Speaker 4: That being said, small caps are very attractive from a
Speaker 4: valuation standpoint, just from a common sense standpoint, the trees
Speaker 4: will not grow to the sky, and it's reasonable to
Speaker 4: have some degree of diversification around a large cap cap
Speaker 4: weighted index.
Speaker 3: Basically definitely makes sense and kind of in line with
Speaker 3: what we're seeing with a lot of our macro models
Speaker 3: that suggest, you know, valuations could expand, but growth could
Speaker 3: be pretty anemic given how the economy is kind of
Speaker 3: go in right now, and an apologies for this question
Speaker 3: in advance.
Speaker 2: I kind of hate answering it myself.
Speaker 3: But with the election only a few weeks away, are
Speaker 3: there any policies you're seeing out there that are you're
Speaker 3: pretty excited about or less excited about.
Speaker 4: Let's say I did a lot I did you know,
Speaker 4: for one of the books I wrote, I did a
Speaker 4: whole bunch of stuff on sort of calendar research, which
Speaker 4: is kind of anomalies based on timing and election cycles
Speaker 4: and things of that sort. And you know, there are
Speaker 4: certain segments that do better under one party, there are
Speaker 4: certain segments that do better on the other party. All
Speaker 4: this is very hard to prove statistically because you just
Speaker 4: don't have enough data points. But what what did seem
Speaker 4: to be statistically sort of significant is the more divided
Speaker 4: the government, the better the stock market seems to do.
Speaker 4: So if you're taking a step back and you can
Speaker 4: remove yourself from all the sort of raw rahing on
Speaker 4: one side or the other, if the government can remain
Speaker 4: divided so that the structure the regulatory is nothing changes,
Speaker 4: that is probably the best outcome for an equity investor,
Speaker 4: So a divided government is less likely to produce changes
Speaker 4: that are going to cause you know, massive changes and
Speaker 4: flows of capital are going to provide winners to some
Speaker 4: companies and losers to other companies, and effectively, you know,
Speaker 4: what you have priced in in the equity market is
Speaker 4: then reflecting what the future earnings growth are is currently.
Speaker 4: So I think as an investor, one thing to hope
Speaker 4: for is for a divided government and for the government
Speaker 4: to make the least amount of changes based on what's
Speaker 4: occurred in the past.
Speaker 2: Basically, yeah, totally. Markets love certainty.
Speaker 3: And the other big story obviously kind of over the
Speaker 3: next coming weeks is earning season. Is there anything you're
Speaker 3: watching in particular? Is earning season? Gets going in earnest
Speaker 3: or small caps?
Speaker 4: The key question is whether we can see some sort
Speaker 4: of broadening of the earnings growth that has has been
Speaker 4: extremely strong amongst the large cap companies. And there's some indication,
Speaker 4: you know, just based on price movements and based on
Speaker 4: what we're seeing in terms of year over year projected
Speaker 4: earnings growth, that we are going to see some broadening
Speaker 4: if the economy does not head into a recession, which
Speaker 4: looks less and less likely it would not be unheard
Speaker 4: of for sort of an equal weighted or smaller cap
Speaker 4: weighted benchmark to outperform a larger cap weighted benchmark. As
Speaker 4: sort of the earnings growth tends to sort of broaden
Speaker 4: and move away from these extraordinarily large, extremely profitable, extremely
Speaker 4: high growth, and reasonably valued companies that make up the
Speaker 4: you know, the largest companies in the cap weighted index.
Speaker 1: Basically, before we let you go, I do have one
Speaker 1: more question. You know, since you started, or you know,
Speaker 1: since ZAX has started, have you noticed any changes in
Speaker 1: trends regarding analyst revisions.
Speaker 4: Well, there was rage FD that was passed several years ago,
Speaker 4: and that kind of eliminated sort of special flow of
Speaker 4: information to certain select analysts. So that sort of increased
Speaker 4: the effectiveness of looking at sort of agreement, which is
Speaker 4: the extent to which multiple analysts are revising in the
Speaker 4: same direction. But generally, what I what I've seen is
Speaker 4: just an increase in the efficiency of the market over time.
Speaker 4: And you know, bringing it back to sort of the
Speaker 4: small cap space, you know, I when I look at you,
Speaker 4: I qualitatively look at a couple of companies and I
Speaker 4: find some very small cap company that looks interesting, and
Speaker 4: it looks like it has some earnings growth, and maybe
Speaker 4: it doesn't even have any analysts following it, and I'll
Speaker 4: start to read the ten k's and ten ques, and
Speaker 4: what will come up is that in the process of
Speaker 4: doing this, there'll be two activist investors that will come
Speaker 4: on board and start sort of looking for changes to occur.
Speaker 4: So the level of sort of pouring over the public
Speaker 4: equity markets has increased, and as a result, I think
Speaker 4: the efficiency of the market has increased, and sort of
Speaker 4: the mean reversion due to valuation metrics has decreased, which
Speaker 4: I think actively helps estimate revision processes, because what you're
Speaker 4: doing with estimate revision processes when you're implementing them quantitatively
Speaker 4: is you're looking for not necessarily misvaluation on any one equity.
Speaker 4: You're looking in aggregate that your valuation is basically in
Speaker 4: line with your benchmark. And the more efficient the market is,
Speaker 4: the more likely that's going to occur, and the less
Speaker 4: likely there's going to be mean reversion in terms of
Speaker 4: sort of valuation metrics. So over time, what I've seen
Speaker 4: is an increase in efficiency, an increase of interest amongst
Speaker 4: smaller cap companies, and a less more likely that a
Speaker 4: company's stock price, no matter that it's capitalization, is going
Speaker 4: to reflect current earnings outlooks, So as a result, it's
Speaker 4: more likely conceivably to respond to upward estimate revisions that
Speaker 4: materialize that have not yet been published.
Speaker 1: Basically, it's great well Mitch. I enjoyed this and wanted
Speaker 1: to thank you again for joining us.
Speaker 4: David and Michael, it's been a pleasure. Everyone have a
Speaker 4: good rest of the week.
Speaker 1: And Mike, thank you for joining me today as Mike Coast.
Speaker 1: Thank you both until our next episode. This is David
Speaker 1: Cone with Inside Active