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 security selection. I'm David Cohne,
Speaker 1: I lead mutual fund and active research at Bloomberg Intelligence.
Speaker 1: Today my co host is Christopher kine, Us, quantitative strategist
Speaker 1: at Bloomberg Intelligence. Chris, thank you for joining me today.
Speaker 2: Thank you so much for having me. David.
Speaker 1: So, you wrote a recent note about adding profitability to
Speaker 1: value stocks or the profitability factor. Since our conversation today
Speaker 1: will be focused on quality, I wonder if you could
Speaker 1: give us a sense of how adding that profitability factor
Speaker 1: to a standalone value strategy performs.
Speaker 2: Yeah. I'm a big fan of adding profitability to value.
Speaker 2: I mean just in empirically, you know, it seems to
Speaker 2: work better and it's very logical. So you know, just
Speaker 2: as a as a review, you know, value was the
Speaker 2: only factor that underperformed in twenty twenty four by our measurement.
Speaker 2: If you look at the long short factor, it was
Speaker 2: the only one that's down on the year, And if
Speaker 2: you only look at the long only legs, it was
Speaker 2: the only one that underperform the market. So it so
Speaker 2: just Q one value. Just cheap stocks returned about ten
Speaker 2: percent last year in the Russell one thousand as compared
Speaker 2: to about thirteen or so percent return for the equal
Speaker 2: weighted a Russell one thousand. If you added some profitability
Speaker 2: to that, that increased the returns to about fifteen to
Speaker 2: sixteen percent. So you know it, I'll perform a market
Speaker 2: if you just had that profitability component. To me, you know,
Speaker 2: it's very logical because you know, sometimes value stocks are
Speaker 2: valued for a reason. You know they have, you know,
Speaker 2: not good prospects and little chance for a turnaround. If
Speaker 2: you add a profitability filter to your value factor, you
Speaker 2: kind of filter out those value traps or you know,
Speaker 2: cheap companies that are cheap for a good reason. And
Speaker 2: that seems to work good both in the short term
Speaker 2: and the long term.
Speaker 1: That makes sense. So I think we'd like to introduce
Speaker 1: someone who's actually no stranger to quality, John Davey. John
Speaker 1: is founder, CEO, and CIO of Astoria Portfolio Advisors. John,
Speaker 1: thank you so much for joining us today.
Speaker 3: Great great to be here, guys, thank you for having
Speaker 3: me on.
Speaker 1: So before we get into talking about your investment process,
Speaker 1: Can you tell us more about your start in the
Speaker 1: investment industry and what led you to start Astoria.
Speaker 3: Sure. So I began as a quantitative derivative analyst and
Speaker 3: Merrill Lynch's derivative research group in the late nineties. So
Speaker 3: it was an intern you know, basically spent my first
Speaker 3: ten years kind of doing index level research. Quant research,
Speaker 3: always at the index level, so that included like index
Speaker 3: futures and next options ETFs. You know, got popular in
Speaker 3: the late nineties and so ets were underneath our research group.
Speaker 3: So then did that for ten years, and then I
Speaker 3: became head of Morgan Stanley's ETF content for institutional clients.
Speaker 3: And you know, I had always liked macro research, asset allocation,
Speaker 3: and you know, always wanted to join the buy side
Speaker 3: and be an entrepreneur. So I felt, you know, here
Speaker 3: is a way to kind of do both kill two
Speaker 3: birds one stone, kind of joined the buyside and also
Speaker 3: to you know, be an entrepreneur.
Speaker 1: So let's talk a little more about Astoria. How would
Speaker 1: you describe the Astoria investment philosophy.
Speaker 3: Yeah, so we I would say it's it's a combination
Speaker 3: of there's kind of two verticals, like two business lines.
Speaker 3: One is like quantitative research, and the expression could be
Speaker 3: like an SMA, a quant SMA could be an ETF.
Speaker 3: And then the other business line is kind of multi
Speaker 3: asset ETF investing kind of asset allocation. So really I
Speaker 3: would say it's it's combining active and passive. That's kind
Speaker 3: of what we do, you know, at our firm. I
Speaker 3: would say our ETFs are systematically active. It's very rules based.
Speaker 3: Implementation is active like when we actually rebalance and how
Speaker 3: we trade, and I can spend a lot of time
Speaker 3: talking about that, but it's very kind of rules based,
Speaker 3: quantitative in nature. Our asset allocation is you know, I
Speaker 3: would say the idea there is that we want to
Speaker 3: use the business cycle, use earning valuations, use sentiment in
Speaker 3: order to kind of dictate whether or not we want
Speaker 3: to be ovoid on the way in NASA class, and
Speaker 3: then we use a tiny bit of liquid olts in
Speaker 3: order to kind of hedge our left tail risk. Once
Speaker 3: you hedge your left tail risk, which I know we're
Speaker 3: in a bull market, but we've had many crisises the
Speaker 3: last you know, seven eight years, so that ability to
Speaker 3: kind of of hedge left tail risk, I think is
Speaker 3: quite important and you know, just use like a little
Speaker 3: bit of liquid alts in order to kind of hedge that.
Speaker 3: So that's kind of like our two business lines. One
Speaker 3: is quant sma's ETFs, the other is multi ASCID ETF
Speaker 3: model portfolios.
Speaker 1: Great. So if we want to, you know, focus in
Speaker 1: on the ETF specifically OROE the astoria US equal Weight
Speaker 1: Quality Kings ETF, is there a process you follow to
Speaker 1: narrow down a universe and then select the stocks for
Speaker 1: the portfolio.
Speaker 3: Absolutely, so you know the idea there is that, you know,
Speaker 3: and for background, you know, we all worried about the
Speaker 3: concentration risk and the ND the CES. You know, ten
Speaker 3: stocks make up forty percent of the S and P
Speaker 3: five hundred and we launched are we back in August
Speaker 3: first of twenty twenty three, So and you know it
Speaker 3: takes like, you know, three six months to let's say,
Speaker 3: launch an ETF. So we were worried about concentration risk
Speaker 3: for a while, you know, and we looked at the
Speaker 3: available options out there and we just weren't quite comfortable.
Speaker 3: And I can spend some time talking about what makes
Speaker 3: our equo weight approach different, but essentially it's like a funnel, right,
Speaker 3: we start with like ten thousand stocks, we filter out,
Speaker 3: set out, we picked you know, large liquid you know,
Speaker 3: minimum free float, minimum market cap weights. Then we come
Speaker 3: up with like eight hundred investible stocks. And the idea
Speaker 3: with those eight hundred stocks is if we want to
Speaker 3: pick the hundred of you know, let's say the best
Speaker 3: in kind of that eight hundred, And what we do is,
Speaker 3: you know, we look at five different factors, so things
Speaker 3: like quality, valuation, growth, momentum, and dividend. And we want
Speaker 3: to so we'll weight our etf So fifty percent of
Speaker 3: the quant code is allocated to the quality factor, twenty
Speaker 3: percent to the dividend factor, twenty percent to the valuation factor,
Speaker 3: five percent to growth factor, and five percent to the
Speaker 3: momentum factor. And essentially these winds up being like high
Speaker 3: quality companies that are reasonably priced. You know, within each
Speaker 3: one of those five factors, there's like three, four or
Speaker 3: five fundamental ratios that express the factor of view. So
Speaker 3: in the case of like quality, like we're looking at
Speaker 3: companies with ro OE r O A, r O I C,
Speaker 3: dividing could be you know, the sustainability the dividend, the
Speaker 3: dispersion of the dividend. Valuations could be like, you know,
Speaker 3: things like PE price, the sales. The growth factor could
Speaker 3: be things like PEG ratios. The momentum factor could be
Speaker 3: like relative strength indicators and our premise. And you asked
Speaker 3: me before, David, like, what do we fundamentally believe in?
Speaker 3: You know, we definitely think that the more factors you
Speaker 3: can harvest in a portfolio, as long as you harvest
Speaker 3: in a low cost manner and as long as you
Speaker 3: stick with the factors like that historically has been able
Speaker 3: to give you higher risk adjuster returns and kind of
Speaker 3: put you higher up on the fishing frontier. So to summarize,
Speaker 3: you know, start with like ten thousand investable stocks, filter
Speaker 3: down to eight hundred of the ones that are the largest,
Speaker 3: most liquid, you know, good free float, and then pick
Speaker 3: a hundred of that eight hundred that have you know,
Speaker 3: strong roe, strong row, you know, strong quality metrics, that
Speaker 3: paid dividends, that are reasonably priced, that have a little
Speaker 3: bit of growth and momentum characteristics. It's great.
Speaker 1: So let's focus in on quality for a second. What
Speaker 1: is your research shown about the long term value of
Speaker 1: quality stocks.
Speaker 3: Well, I liked what Chris said before. I mean, you know,
Speaker 3: valuing in beta or valuant quality you know definitely have
Speaker 3: very very low negative you know, very low correlations, if
Speaker 3: not negative. Right. So if again, if you believe in
Speaker 3: this concept of like how do I get higher? But
Speaker 3: on the fish frontier, how do I mix factors? You know,
Speaker 3: you're picking a factor quality that you know has pretty
Speaker 3: robust long term characteristics, and especially if you pair that
Speaker 3: with like value or you know, you know small cap
Speaker 3: stocks that that looks very very attractive to us for
Speaker 3: us at the end of the day, Like you know,
Speaker 3: quality are companies that you know are robust, they pay dividends,
Speaker 3: they have good earnings, good ROI. You know ro O,
Speaker 3: I c roa Roe. And you know it's it's this
Speaker 3: concept of like it's persistent, pervasive, robust. It works across sectors,
Speaker 3: across countries, across economic cycles, and you know there is
Speaker 3: historical out performance.
Speaker 2: Right.
Speaker 3: So if you do some farm of French you know analytics,
Speaker 3: you'll see that high quality stocks have beaten low quality
Speaker 3: stocks and being the market you know, over the last
Speaker 3: you know, half a century, if not longer. I think
Speaker 3: their data set goes back to like nineteen sixty three.
Speaker 3: So that's what we're looking for. I mean, these could
Speaker 3: be you know companies that Microsoft, Google, you know Facebook,
Speaker 3: I mean a lot of them tend to be growth now,
Speaker 3: but you know it's brand hold names essentially. So that's
Speaker 3: that's how we think about it, you.
Speaker 4: Know, John, I I talked to a lot of clients
Speaker 4: in my role, and you know, when it comes to
Speaker 4: factor investing, you know, I feel like the standard factors,
Speaker 4: and you know, most people have a very good definition.
Speaker 2: While it might vary somewhat of these factors, right, things
Speaker 2: like value, things like momentum, things like low risk. Right,
Speaker 2: you might have a different look back for your for
Speaker 2: your momentum factor per se, but we all understand what
Speaker 2: momentum is. Quality seems to be the one where people
Speaker 2: have different differing definitions. It typically is a profitability metric.
Speaker 2: And then I've seen other things and you just mentioned
Speaker 2: some of them. But like when you think about a
Speaker 2: quality company, obviously you use profitability metrics like r O
Speaker 2: E r O. I see other than other factors saying
Speaker 2: within the quality bucket, like what other thing like do
Speaker 2: you look at like things like stability of earnings or
Speaker 2: cruels or anything like that when you're when you're kind
Speaker 2: of defining your quality factor.
Speaker 3: Yeah, we do. I mean there's you know, there's about
Speaker 3: five that go within the quality bucket. But you know,
Speaker 3: as I try to emphasize, like our ro O E Tiff,
Speaker 3: not just high quality stocks, like we're picking high quality
Speaker 3: stocks that have you know, attractive valuations, that have good
Speaker 3: dividend pain ability and that all over and then have
Speaker 3: a little bit of growth the momentum too. But yeah,
Speaker 3: I mean in the end though, within the quality bucket
Speaker 3: it is skew towards ro O E, r O I,
Speaker 3: C ro O A. But I think the point that
Speaker 3: I'm trying to articulate and maybe I am, you know,
Speaker 3: I need to do better job. But you know, if
Speaker 3: you have a good return on equity of a good
Speaker 3: return on asset, you know you are doing other things
Speaker 3: well in the company, Like you're issuing dividends, you have
Speaker 3: good free cash flow, you don't use a lot of
Speaker 3: debt to equity. Your leverage ratios are you know, well
Speaker 3: or well allocated. Let's say. So it does at times,
Speaker 3: Chris like feel a little bit fuzzy because I think,
Speaker 3: like values just okay, you're a stock that has a
Speaker 3: broken story and you need to have something to come corrected.
Speaker 3: The sis factor. You know, small cap stock you're just
Speaker 3: you know, very small. You know, momentum is just you know,
Speaker 3: relative strength, you know, very technical factor. So quality kind
Speaker 3: of encapsulates a few other metrics beyond just you know,
Speaker 3: the return on equity, return on assets. You know, some
Speaker 3: index providers and some metail fishers will say, you know,
Speaker 3: debt to equity is a big component of it. Within
Speaker 3: you know, the quality definition. For us, it's not. We
Speaker 3: tend to use more kind of traditional metrics like r
Speaker 3: O A ro OE and r O C.
Speaker 2: Yeah, I totally agree with that. I mean, just based
Speaker 2: on my research. You know, like you said, it's quality
Speaker 2: is sometimes a fuzzy definition. But it seems very clear
Speaker 2: to me that profitability is the most important part of quality.
Speaker 2: And when you when you look at back tests of
Speaker 2: all these different things or crurals or stability of earnings
Speaker 2: or whatever, you know, the r O E, r O
Speaker 2: I C r O A back tests just perform much better.
Speaker 2: And I and you know, I think profitability is really
Speaker 2: the backbone equality in many respects. So another question I
Speaker 2: give from clients all the time, kind of leading you
Speaker 2: to water here. But you know, some some clients that
Speaker 2: might not be a sophisticated in fact or investing. They'll
Speaker 2: say things to me like, well, isn't quality just growth?
Speaker 2: Why don't you just use growth? Why don't why do
Speaker 2: you use quality in addition to growth or quality, you know,
Speaker 2: instead of growth? You know, what would you say that? Like,
Speaker 2: would you say, and you know, would you say, quality
Speaker 2: is like growth? How would you differentiate it? What would
Speaker 2: you say to that question?
Speaker 3: So they're different. We happen to like combining both of them.
Speaker 3: We have an ETF G Triple Q that's kind of
Speaker 3: quality growth stocks. It's like fifty percent, you know, it's
Speaker 3: like half quality half growth. Let's say I would say,
Speaker 3: right now, we're in this kind of unusual period, Chris,
Speaker 3: where a lot of growth companies tend to also be
Speaker 3: in the quality bucket. It wasn't O is the case,
Speaker 3: you know, but because tech stocks have produced such strong
Speaker 3: returns and they have good you know, earnings revisions, they
Speaker 3: have good growth estimates, good PEG ratios, they also happen
Speaker 3: to have like strong ROE strong ro I C strong
Speaker 3: ro A, So they're in both buckets. But like you know,
Speaker 3: we use like these zis. We have like a white
Speaker 3: paper we wrote for our ro O E TF and
Speaker 3: we show them in the paper, like, Okay, what's historically
Speaker 3: the sharp ratio the standard deviation for quality momentum involve
Speaker 3: those size growth market divine il VALU and you see
Speaker 3: quality as the highest sharp ratio and it's got a
Speaker 3: pretty low standing deviation. So the standardiation and this has
Speaker 3: gone back you know, thirty years in MSA and the
Speaker 3: SEAS is about fourteen and a half. The growth factor
Speaker 3: has about seventeen and a half stand deviation, so much
Speaker 3: like almost like three standard deviation points higher. And they
Speaker 3: both have similar kegers. So growth stocks just happen to
Speaker 3: have a lower sharp ratio. But this is like thirty
Speaker 3: years worth of data, right, But I would say technically
Speaker 3: the answer is like they are different. You know, one
Speaker 3: has traditionally like strong roa ROI. You know that's equality,
Speaker 3: and the growth have you know, more like higher peg
Speaker 3: ratios earnings momentum. It's just the only recently in the
Speaker 3: last cycle where I would say there's a lot of
Speaker 3: like mix. You know, stocks are in both quality ETFs
Speaker 3: and the growth ETFs.
Speaker 2: Yeah, I found that same thing, and you know I've
Speaker 2: also found that you know, quality is much better, sharp
Speaker 2: ratio is much better risk adjuster returns, and like you know,
Speaker 2: I've seen that quality slaze profitability. It's definitely not the
Speaker 2: same as something like low risk, but it does overlap
Speaker 2: with like low risk, low beta lovall, you know, you
Speaker 2: typically get similar stocks in there, and that also has
Speaker 2: very strong risk adjuster returns. So the next question I
Speaker 2: wanted to ask you was something that's very interesting and
Speaker 2: something that I again talk to clients all the time about,
Speaker 2: and that is weighting your stocks right like right now.
Speaker 2: Just because of recency bias, it seems like any non
Speaker 2: market cap weight you know, it's it's lagging. You know,
Speaker 2: customers come to me and say, why would you eagually
Speaker 2: wait the stocks? Why would you have any other waiting
Speaker 2: scheme other than market cap waiting, because market cap waiting
Speaker 2: has worked so well very recently, and you know, I
Speaker 2: know that when you go back far in time, that's
Speaker 2: not the case. So I would love to know your
Speaker 2: thought process behind why you weight your stocks how you do,
Speaker 2: and maybe you know, you could dub to into maybe
Speaker 2: some you know, concerns you could potentially have with the
Speaker 2: market cap weighted indices how they're currently constructed.
Speaker 3: I saw my career in two thousand and it was
Speaker 3: basically the Internet bubble erupted, and that was kind of
Speaker 3: like the the you know, the impetus for like Wisden
Speaker 3: Try got popular, Rob Barnett got popular, you know, AQR launch,
Speaker 3: And it was because Marke cap weight indities were flawed
Speaker 3: because you know, they had a lot of these tech companies.
Speaker 3: Some of them were profitable, some of them were not profitable,
Speaker 3: and really smart bait investment, I think became popular because
Speaker 3: the tech bubble and you know, unwinding in two thousand
Speaker 3: and one, two thousand and two, I feel like it's
Speaker 3: the same movie again, although the difference is now is
Speaker 3: that a lot of these companies are actually pretty profitable.
Speaker 3: It's just that they're just gargantuan size. I would say
Speaker 3: we whenever I've done quantitative like stock selection, you know
Speaker 3: here at Astoria or my prior companies, like we always
Speaker 3: generally equally weighted, and it's like a risk mitigation tool.
Speaker 3: You know, the more way you give one stock, the
Speaker 3: more you know risk you take in that one stock.
Speaker 3: You know, obviously now that there's a big passive bubble,
Speaker 3: a ETF bubble, and money keeps pouring into like spy,
Speaker 3: vu IVV and it's like this massive self fulfilling prophecy
Speaker 3: because you know, the cost sore low. It's you know,
Speaker 3: two basis points, three basis points. Whatever it is, it works,
Speaker 3: people buy it, more money comes in, they buy the
Speaker 3: same stocks. So I would say now more than ever.
Speaker 3: You know, it's important to tilt away. And we have
Speaker 3: like these decision trees, like when we run our multi
Speaker 3: asset ETF strategies, like what do you want to tilt
Speaker 3: the way towards? So I'll go that real quick. So basically, okay,
Speaker 3: like you tilted away from our cap. You can choose
Speaker 3: eco weight. That's one you know decision tree. But you
Speaker 3: have to be careful with equal weight because how are
Speaker 3: you equally waiting it? And we could spend like five
Speaker 3: minutes talking about that. Do you want to tell towards value? Okay?
Speaker 3: Value is a factor. That's very tough. It's very fickle.
Speaker 3: It works you know every ten years, maybe two three
Speaker 3: of the ten years work. So that's tough. Small caps,
Speaker 3: that's tough. You need a certain credit cycle, interest rate
Speaker 3: cycle for small caps to work. Then you have international.
Speaker 3: So the point is like, if you have concerns about
Speaker 3: market weighted ind ses, people tend to lean on equal weight.
Speaker 3: You have to be careful with equal weight. I think
Speaker 3: eqal weight you know now has been tough, but like
Speaker 3: over like twenty thirty years, Like you see the equal
Speaker 3: weight tensaple form mark cap it works better out of
Speaker 3: like a recession, so when you cut it up, you'll
Speaker 3: see that. Like when when you're like in this like
Speaker 3: economic slowdown, people buy more market cap weight, which I
Speaker 3: think is kind of this current period that we're in now.
Speaker 3: I sometimes hear people say, wow, small cap EQO weight's
Speaker 3: no longer going to work because companies stay in private.
Speaker 3: But I just think we're in this like really unusual
Speaker 3: bubble of passive indexation ETF flows and mark cap is
Speaker 3: just bid because just money keeps plowing into those products.
Speaker 2: Yep, yep. I found the exact same thing. So what
Speaker 2: about like you know, and I typically stick to equal
Speaker 2: weight as well. I feel like it gets you like
Speaker 2: ninety five percent of the way there. But like sometimes
Speaker 2: customers ask me, well, what about a more complicated scheme,
Speaker 2: Like what about some kind of inverse polatility waiting like
Speaker 2: Ray Dalio style, or like risk parity or maybe even
Speaker 2: more like me invariance optimization type waiting scheme, Like do
Speaker 2: you find any value in those overly complicated ones or
Speaker 2: do you think that's kind of adding more degrees of
Speaker 2: freedom to a model which is you know, generally bad.
Speaker 3: I mean to be honest, Like it gets such a
Speaker 3: bad name, you know, smart beta. But this idea of
Speaker 3: like weighting based on like quant metrics, like the higher
Speaker 3: the quant rank in, the more way you give, Like
Speaker 3: we have some strategies where we do that. That to
Speaker 3: me makes sense and as like easier to explain if
Speaker 3: you deal with institutional investors, totally get it, you know,
Speaker 3: mean variance optimization inverse volatility, Like I think you can
Speaker 3: do that and get away with it. But in the
Speaker 3: financial advisor world that I live in, our world, like
Speaker 3: equal weight is enough tracking error versus the benchmark that
Speaker 3: and it's easy to explain. I think you just have
Speaker 3: to be careful with equally weight and like when you
Speaker 3: equally wait, you know, let's say the Russell one thousand
Speaker 3: index now you're talking about each stock is like thirteen
Speaker 3: bip weight. Let's say twelve bip weight. That's tough. If
Speaker 3: you equal wait s and P five hundred each stock
Speaker 3: is twenty BIPs. Wait, we just like the reason why
Speaker 3: we launched o OEI was because we weren't comfortable with
Speaker 3: SMP equal way to DTF because a, you know, there
Speaker 3: was only fifteen percent technology exposure, so we wanted to
Speaker 3: kind of optimize our ro oe E TF to match
Speaker 3: the S and P sector weight. So and then we
Speaker 3: pick only one hundred stocks. So now your marginal contribution
Speaker 3: and to risk and return is a lot higher when
Speaker 3: you once you equally weight one hundred stocks compared to
Speaker 3: like five hundred or thousand. And the other real extreme
Speaker 3: example is I put out a report called ten ETFs
Speaker 3: for twenty twenty five, and I put in there this
Speaker 3: xn tk ETF. It's an equal weighted tech ETF from
Speaker 3: Spiders and it's actually been the cues over the last
Speaker 3: three years. When we launched a report, and some people
Speaker 3: were surprised, but you know, it's got thirty five stocks.
Speaker 3: Each stock is three percent weight. And then it's not
Speaker 3: just like they pick stocks that have like strong sales
Speaker 3: and revenues, so it's a combination of like you know,
Speaker 3: smart beta, and then the mechanism to weight is like
Speaker 3: just a small concentrated portfolio thirty five stocks three percent weight,
Speaker 3: so just have to be careful with equal weight. Even
Speaker 3: though it's simplistic, it's easier to like talk to advisors
Speaker 3: about that. It's like, how are you doing it and
Speaker 3: how are you optimizing the sectors?
Speaker 1: So, actually you mentioned sectors, so I kind of want
Speaker 1: to touch on that a little bit. You know, we've
Speaker 1: talked about waiting stocks, but how do you determine overweighting
Speaker 1: or underweighting different sectors? Are you looking at more macro
Speaker 1: I guess component issues or so.
Speaker 3: In our quantitative stock selection SMAs and our ETFs, like
Speaker 3: we do track the benchmark sector weight, so we optimize
Speaker 3: against that. We want to have our stock selection provide
Speaker 3: the alpha and this concept that when we're designing it,
Speaker 3: you know, we're doing a multi factor you know, when
Speaker 3: we when we're just doing like multi asset investment in
Speaker 3: our ETF model portfolio business, you know, we will overweight
Speaker 3: on the weight and that's more based on macro top
Speaker 3: down research kind of like depending on you know, where
Speaker 3: we are in the earning cycle, the credit cycle, the
Speaker 3: inflation cycle. That's a much different game sort of say.
Speaker 3: But when we're talking about like just quantitative investing, we'd
Speaker 3: rather have our stock selection in our quont code, which
Speaker 3: you know, for background, we have five CFAs on staff.
Speaker 3: My colleague nixer Bone kind of oversees the quant side
Speaker 3: of it, and Ponkach Patel is kind of head of
Speaker 3: quant data science. I mean collectively these you know, the
Speaker 3: five CFAs, and we've got a lot of years experience
Speaker 3: building quant fulfillis like, we know that code is very powerful,
Speaker 3: but we just stay diligent. We stick to our process.
Speaker 3: We do have risk management risk management capabilities within that
Speaker 3: which I can talk about, but I think when it
Speaker 3: comes to like quantitative systematic investment, it's better to be
Speaker 3: like rules based, diligent and stick with the process.
Speaker 2: You know, one of the things we do at BI
Speaker 2: that gets a lot of traction is monitoring the valuations
Speaker 2: of the factors. So we typically do is we'll look
Speaker 2: at meeting valuations of a long and short side of
Speaker 2: the factors, compare them to each other, right, and that
Speaker 2: would say like is a long and short factor cheap
Speaker 2: or expensive? Now I know that you said that your
Speaker 2: value is part of your overall process, but just thinking
Speaker 2: about quality in and of itself or really any other factor.
Speaker 2: To be honest, is there every scenario where like a
Speaker 2: certain factor gets too expensive historically, where you might decrease
Speaker 2: the weight to it. Like one of the things we've
Speaker 2: noticed recently is that profitability slash quality is very expensive.
Speaker 2: You can compare it to the market, you can compare
Speaker 2: it to low quality stocks. The ratio is very high
Speaker 2: historically when this stuff is very bit up. Would that
Speaker 2: have any influence on your the weighting of your factors?
Speaker 3: It would, And that's where the power of being active
Speaker 3: and passive together and being kind of rules based, I think,
Speaker 3: is the benefit. So what I would say to you
Speaker 3: is like, Okay, right now, we've thought about this. In
Speaker 3: our quality to Froe, quality fact is only fifty percent, right,
Speaker 3: so again we've got twenty percent in like dividends, twenty
Speaker 3: percent in valuation. We would say if we got even
Speaker 3: more expensive, we would say, okay, take down the quality
Speaker 3: factor attribution in the ranking process down until it's say
Speaker 3: forty percent, because that you know, at the end of
Speaker 3: the day, like we do want to buy below intrinsic value.
Speaker 3: Way for it to achieve intrinsic value. Our ETF has
Speaker 3: like a seventeen p ratio versus like twenty two for SPY,
Speaker 3: So I feel like, you know, it's like quality at
Speaker 3: a reasonable price. But yeah, I think that's the flexibility
Speaker 3: that you can provide once you buy an active ETF
Speaker 3: or use an active manager. You know, if you just
Speaker 3: going out there buying like the quality TF qual, you
Speaker 3: know you're going to be stuck with high quality stocks,
Speaker 3: let's say, especially if it's MARKAP weighted, which that is
Speaker 3: you know for us, the minute you tilt away from
Speaker 3: mar Cap, you're going to get something that looks at
Speaker 3: a discount to the market. So you know, I would
Speaker 3: say the other main point to make here, Chris, is
Speaker 3: like each stock fights with one another in the quant
Speaker 3: ranking code, right, so if a stock got too expensive,
Speaker 3: you know eventually it's ranking would fall down. When we
Speaker 3: pick one hundred stocks in row, each stock fights one another,
Speaker 3: but we are picking top DEA SALSASL one, DEASTL two
Speaker 3: amongst you know, ten descals amongst twenty different valuation metrics.
Speaker 3: So if something gets very very expensive within the code,
Speaker 3: it'll de rank by itself.
Speaker 1: Sort of saying I wanted to ask about selling positions.
Speaker 1: So I understand it's a quantitative portfolio, and you know,
Speaker 1: I know you're ranking the stocks. Is this done on
Speaker 1: a periodic basis or is there anything that would kind
Speaker 1: of trigger a cell, you know, in terms of rankings outside.
Speaker 3: Of that, So good question, I would say in anytime
Speaker 3: you equally wait, I think it's really important that you
Speaker 3: quarterly share change rebellance. Like we had this one stock
Speaker 3: sm CI that you know went up you know, eight
Speaker 3: hundred percent, So it's you know, each stock in our
Speaker 3: basket starts at one percent weight and then does drift
Speaker 3: up or down. So this then got up to like
Speaker 3: a three percent weight, and then you know, and then
Speaker 3: quarterly share a balance it you know, got trimmed down
Speaker 3: to like one percent. Our code is longer term in nature,
Speaker 3: so it's not going to pick up like accounting fraud.
Speaker 3: Let's say, so in the case of like app love
Speaker 3: and let's say when we launched our g triple QTF,
Speaker 3: it was like October first last year. Like in the
Speaker 3: case of like a Nazak one hundred, where like an
Speaker 3: annual rebellance, like you know, Nazek added app lovin in
Speaker 3: the December rebalance. I mean it was up like a
Speaker 3: thousand percent when they added it. You know, these are
Speaker 3: things that you can look for and be you know
Speaker 3: a little bit more strategic when you're active, let's say,
Speaker 3: but again, like it's not going to pick up like
Speaker 3: an accountant fraud story. So like if we had an
Speaker 3: instance where you know, a stock fell twenty percent, you know, overnight,
Speaker 3: you know, we would then do like the human bottoms
Speaker 3: up research and do like stock selection on that one
Speaker 3: stock to say, okay, you know, does this stock need
Speaker 3: to be kicked out? And I think that's a benefit
Speaker 3: of active. The extreme example I'll give you is like
Speaker 3: ten fifteen years ago, there was a stock in the
Speaker 3: FXI ETIF that like just stopped trading because of like
Speaker 3: a fraudulent thing, and it stayed in the FXIEYTF for
Speaker 3: like six months right before it's kicked out. So, like,
Speaker 3: you know, there's benefits of doing both right, being rules based,
Speaker 3: which is more passive, and then being you know, using
Speaker 3: like an human oversight and kind of be inactive. But
Speaker 3: outside of these very episodic periods, we generally don't have
Speaker 3: a lot of like intra quarter cell signals. Let's say,
Speaker 3: for ro O ETF. It is like an annual reconstitution process,
Speaker 3: but you know, every quarter we bring the shared change
Speaker 3: you know, to share way back to one percent and
Speaker 3: then we look at the quon code to see if
Speaker 3: anything materially deranked, and if it did materially de rank,
Speaker 3: like you know, a one to two decile became like
Speaker 3: an eight, you know, then we would like investigate further.
Speaker 3: So that is kind of like a risk management oversight.
Speaker 2: Yeah, I'm just going to piggyback off that with the
Speaker 2: risk management. Like I know, I think about risk management
Speaker 2: is a couple of layers, right, It's like diversification is
Speaker 2: one layer and moving to equally wait does a lot
Speaker 2: for risk management in and of itself. And then you
Speaker 2: have individual position management like do you stop yourself out
Speaker 2: of positions which you kind of just spoke about. And
Speaker 2: then there's like I would call it like overall tactical
Speaker 2: risk management, Like, so, is there anything like that, like
Speaker 2: whether everybody a scenario where you think the whole market's
Speaker 2: going down or went below is two day moving average
Speaker 2: or something like that where you would like de risk
Speaker 2: the whole portfolio. Is there any kind of tactical overall
Speaker 2: signals like that or No?
Speaker 3: Not in our SMAs and our ETF. So I mean
Speaker 3: in our other business multi asset you know, ETF investment,
Speaker 3: Like we do have the ability to kind of be
Speaker 3: much more flexible, which I can speak to. I would say,
Speaker 3: I just don't believe you can kind of time the market.
Speaker 3: So even if we were to de risk the portfolio,
Speaker 3: it would be like US trimming like expensive US docs
Speaker 3: to buy more value and or international and they're using
Speaker 3: like more liquid olds. But like we wouldn't go more
Speaker 3: than you know, let's say five ten percent versus like
Speaker 3: its benchmark, so we kind of have like guardrails in place.
Speaker 3: I think that the thing I would tell listener here
Speaker 3: is like, if you have a high conviction view, like
Speaker 3: you want to really de risk your portfolio, you know,
Speaker 3: you really have to have that kind of second line
Speaker 3: of thinking that like Howard Marx talks about, like what
Speaker 3: do you know that's not already in the price. And
Speaker 3: you know, the one instance where we really had this
Speaker 3: huge high conviction idea was like during the inflation scare
Speaker 3: in twenty twenty two, and that was just us you know,
Speaker 3: thinking about economics one O one, the M two velocity money,
Speaker 3: and we really did nail the inflation call, and we
Speaker 3: had some pretty significant performance versus benchmark, you know, past
Speaker 3: performance on it take a future result. But I think
Speaker 3: the last two years since that inflation scare, we've been
Speaker 3: mined in this like market cap you know, weighted bubble
Speaker 3: passive seven stocks driving most of the SMP. Not really
Speaker 3: sure what's going on with you know, the market from
Speaker 3: a policy standpoint, so you know, we don't make any
Speaker 3: of those bets now, we just haven't had that view.
Speaker 3: And then the only other point to really drive home
Speaker 3: is like, Okay, why we're active is like, and I
Speaker 3: do have high commction in this is that my first
Speaker 3: job was like derivative research like forecasts and ads and
Speaker 3: deletes to like the S and P and next to
Speaker 3: Russell and next And I mean I personally have a
Speaker 3: lot of friends that work with these hedgrophones at arbitrage
Speaker 3: in next flow. So I mean, let's say, you know,
Speaker 3: the cash Cow's ETF has thirty billion dollars. It's index space.
Speaker 3: You can basically know what stock's going to be added
Speaker 3: or deleted, and you know, you can like pre position yourself.
Speaker 3: I felt strongly that ANYTF that I was gonna put
Speaker 3: my name next to would not be passive, just because
Speaker 3: I wouldn't want the street to front run my order
Speaker 3: flow to like you know, arbitrage net asset value points
Speaker 3: off DTF, So what are what are I tf's like,
Speaker 3: we just don't rebalance on the day of you know,
Speaker 3: triple Witch, and let's say it's kind of like done
Speaker 3: you know, before or afterwards, and certainly could be intro
Speaker 3: day too.
Speaker 1: So we have one more question. And actually it's funny
Speaker 1: you mentioned Howard Marks because my question was on books.
Speaker 1: I know his most important thing. Book is one of
Speaker 1: your favorites, might be your all time favorite. But it's
Speaker 1: curious what other, you know, favorite financial books.
Speaker 3: You have, So I I definitely think, you know, Larry
Speaker 3: Sueddrow has written a lot of great books and and
Speaker 3: there's a very important concept that we definitely subscribe to,
Speaker 3: which is this idea that, like you know, when you
Speaker 3: combine in fact in a portfolio, you can get higher
Speaker 3: by in the first fal frontier. So and he's got
Speaker 3: research that goes back, you know, seventy years, fifty years.
Speaker 3: So basically he says, okay, in this one table, if
Speaker 3: you do a twenty five percent allocation towards Debta factor,
Speaker 3: the size factor, the value factor, and the momentum factor,
Speaker 3: the historical sharp ratios like point seventy four, and that's
Speaker 3: basically double any of the individual factor bets on either
Speaker 3: beta value size probably you know, Okay, So then he says, okay,
Speaker 3: instead of doing twenty five percent, do like twenty percent
Speaker 3: to each of those four factors. And then you add
Speaker 3: profitability as a fifth one, and you get a point
Speaker 3: nine to six sharp ratio. And then in the next
Speaker 3: iteration he's substitute quality for profitability, and now you got
Speaker 3: like a one point one sharp ratio. You know, when
Speaker 3: you combine you know, five factors, you had profitability, you
Speaker 3: sub out profitability for quality. You know, you're talking about
Speaker 3: almost triple the sharp ratio of any individual leg beta
Speaker 3: value size. And then you know, like if you he
Speaker 3: runs someone elsis on, like what's the underperformance odds over
Speaker 3: like a one year period, of three year period, five, ten,
Speaker 3: twenty year and the odds of you on the perform
Speaker 3: and are dramatically lower when you combine factors. And so
Speaker 3: his book, you know, like everything you want to know
Speaker 3: about fact investing. I maybe miss a title in the book,
Speaker 3: but that book is kind of seminal to us. You know,
Speaker 3: I'm a big fan of buffet. He just releases you know,
Speaker 3: newsletter this this weekend, and you know, kind of what
Speaker 3: he preaches, like buying quality businesses but just at a
Speaker 3: low price. I think that's really important to how we
Speaker 3: think about investing. So those are some of the top
Speaker 3: two or three that I would say resonate with me.
Speaker 1: Well, this is great, John, thank you again for joining
Speaker 1: us today.
Speaker 3: Next, thanks guys and Chris, thank you for.
Speaker 1: Being my co host today. Thank you until our next episode.
Speaker 1: This is David Cohne with Inside Active.