In this episode I speak with Guillermo Roditi Dominguez, managing director at New River Investments.

This was one of the more unique and wide-ranging conversations I have had on the podcast to date. We begin by discussing Guillermo’s approach to portfolio construction, which is heavily focused on the idea of under-writing risk. How he goes about achieving this, though, takes us from adjusted valuation measures to the positioning of large, systematic players and even to the importance of higher frequency tax data.

After discussing the macro framework, we dive into how decisions are made within equities and fixed income. Again, Guillermo stays consistent to his philosophy of underwriting risk and I found his example of allocating to mid-caps versus large-caps in 2020 to be particularly insightful.

While we spend a lot of the episode talking about under-writing risk, we end the episode with Guillermo’s view as to why the right tail is actually more difficult to manage. So make sure you stick around for that.

I hope you enjoy my conversation with Guillermo Roditi Dominguez.


Corey Hoffstein  00:00

All right 321 Let’s jam. Hello and welcome everyone. I’m Corey Hoffstein. And this is flirting with models. The podcast that pulls back the curtain to discover the human factor behind the quantitative strategy.

Narrator  00:19

Corey has Hoffstein Is the co founder and chief investment officer of new found research due to industry regulations he will not discuss any of new found researches funds on this podcast all opinions expressed by podcast participants are solely their own opinion and do not reflect the opinion of newfound research. This podcast is for informational purposes only and should not be relied upon as a basis for investment decisions. Clients of newfound research may maintain positions and securities discussed in this podcast for more information is it think

Corey Hoffstein  00:50

This season is sponsored by simplify ETFs simplify seeks to help you modernize your portfolio with its innovative set of options based strategies. Full disclosure prior to simplify sponsoring the season, we had incorporated some of simplifies ETFs into our ETF model mandates here at New Found. If you’re interested in reading a brief case study about why and how visit with models and stick around after the episode for an ongoing conversation about markets and convexity with the convexity Maven himself simplifies own Harley Bassman. In this episode, I speak with Guillermo Rhodey Dominguez Managing Director at New River investments. This was one of the more unique and wide ranging conversations I’ve had on this podcast today. We begin by discussing your most approach to portfolio construction, which is heavily focused on the idea of underwriting risk. how he goes about achieving this, though, takes us from adjusted valuation measures to the positioning of large systematic players, and even to the importance of higher frequency tax data. After discussing the macro framework, we dive into how decisions are made within equities and fixed income. Again, Guillermo stays consistent to his philosophy of underwriting risk. And I found his example of allocating to mid caps versus large caps in 2020 to be particularly insightful. While we spend a lot of the episode talking about underwriting risk, we end the episode with Guillermo his view as to why the right tail is actually more difficult to manage. So make sure you stick around for that. I hope you enjoy my conversation with Guillermo ro DD Dominguez. Guillermo, welcome to the show. Really excited to have you here today.

Guillermo Roditi Dominguez  02:43

Thank you, Cory. I am super happy to be here.

Corey Hoffstein  02:45

So I want to start just dive right in you own and manage New River investments, which is an RIA, that serves individuals trusts retirement plans. And you’ve described to me that sort of the core investment offering that you have for your clients, you would actually describe as sort of a 6040, alternative account sort of structure. And I know, your goal is to outperform, but you actually spend a lot of time and probably what you and I connected on the most was this idea of sort of underwriting risk. Talk to me about what that concept means walk me through this approach. What does it mean to approach that sort of 6040 alternative from an underwriting risk perspective?

Guillermo Roditi Dominguez  03:25

So I think whenever we tackle the the process of asset allocation at any level, we have to really find a process and stick to that process, and at the same time, understand where the weaknesses lie for that process, because that’ll help you understand when and why you’re underperforming or outperforming, so that you don’t miss attribute, something that is inherent to the process to a mistake and implementation, or, you know, you don’t attribute luck to skill. And one of these things that we’ve done is this approach to risk taking and approaching every risk as sort of underwriting a barrier, so to speak. And in practice, what it means is, you know, we’re looking for extremes, you know, both in the left tail and the right tail, we could talk more about the right tail later. I think what most people are concerned about is the left tail and saying, hey, you know, what would a really terrible event look like? And in what size? Am I willing to take that risk? And how much do I need to be compensated for taking that risk?

Corey Hoffstein  04:29

So is this something you normally approach from a top down perspective? Or is this a bottom up process for you? It is

Guillermo Roditi Dominguez  04:38

both. We approach it with regards to aggregate measures of markets from a top down perspective. And in a way, we’re not just doing it from the top down in terms of looking at earnings estimates for a whole index or growth expectations for the market as a whole but actually looking at it at a macro economic level. We’re looking at what we think, you know, potential GDP as we’re looking at what percentage of that forward estimate of GDP, we could attribute to corporate earnings? And what level of penetration publicly traded equities have in that space. And it’s very much very similar to an output gap model that you traditionally see, maybe from the Fed or maybe from academics. But we’re always looking at, hey, you know, how does this measure in terms of valuation versus, you know, future potential would be even if that future is fairly far away from today.

Corey Hoffstein  05:37

So I want to tackle this idea of a 6040 alternative, from really three different pieces, sort of the asset allocation decision you make as to maybe tactical tilts towards equities or towards fixed income. And then we’ll talk about the equity allocation, and then we’ll talk about the fixed income piece. So maybe starting with that equity versus fixed income component, what’s your sort of framework or macro framework for thinking about those tactical tilts, and when it makes sense to lean into equities or lean away?

Guillermo Roditi Dominguez  06:09

I think, basically, our fixed income allocation is, it’s almost the residual, we budget for how much risk we’re willing to take in equities, you know, where we’re going to get, historically, you’re going to generate a return where we know we’re going to accrue value through book value accretion, through dividends, through buybacks through optimization of capital structure. But that’s also where you have big risks. And depending on where you are in the spectrum of valuations, you might be able to safely allocate 80% to equities without incurring the kind of risk that would give you call it a 30% portfolio drawdown. But there’s other times at which you really can’t go much above, you know, 40 or 50% into equities, if you have any hopes of being able to have some spare room to buy if things get cheaper, you know, and, and that’s one of the main tensions, right? Are you are you underwriting so you can take the maximum amount of risk you’re taking now, are you leaving yourself room so that if the expected returns become more attractive, you have the ability to increase your allocations at that point? That’s a hard thing to navigate. And so I think that, you know, in terms of being disciplined, what really makes sense for me, is to come up with essentially, indifference curves, right. And so I know it, I have them printed out. And you know, I can look down at a piece of paper, and you know, they get updated as economic data as and market data changes. But for the most part, these sheets are fairly stable day today. And I know that for any given level of evaluations, this is how much I want to own. And so, you know, it gradually keeps us moving, you know, in and out of equity continuously. It’s not like a daily thing. But in very fast markets, you know, we absolutely do adjust that on a daily basis.

Corey Hoffstein  08:01

I want to dive into this a little deeper pragmatically, I know, recently, I tweeted something about looking at sort of the relative returns of, say, the NASDAQ 100 versus small cap value. And you in the reply posted a sheet talking about how expensive a lot of these mega cap tech names were. And sort of the implications for the types of drawdowns they could see from these valuation levels. So I was hoping maybe you could just drill into this a little deeper, and how you think about it from saying, when you look at an index, you look at the valuations, how do you think about that risk underwriting versus valuation? Comparison?

Guillermo Roditi Dominguez  08:39

I think they’re very much related things, you know, your valuation framework is going to drive your risk underwriting, I think one of the things that is important to me is that with our valuation, and our underwriting approaches be relatively naive, you don’t want to be too clever with it, because the world might not work out the way that you thought it was going to. And so we try not to build too many things into this, one of the things that we do build into it is that these valuations are based on an earnings yield, using a peak potential earnings yield, you know, that’s the maximum that we can possibly expect. But then on the other side, when we’re underwriting these things, we’re saying, hey, what happens if next week, we are down in the left tail at a 95th five percentile valuation and maybe a week from that, you know, you’re at a one percentile valuation. And I think for most of my career, people have thought that that was kind of silly. And then last year, it turned out that it was actually really useful because I knew exactly where we were. And as we were, like, plumbing the depths, I knew exactly, you know, what we could do and what we should do. We didn’t have that kind of like paralysis of, hey, you know, everything is changing. Everything is new. You know, we kind of knew and so, what we do is we set these valuations where it’s not but just entirely like an earnings yield, there’s another couple of components there. But that’s the main part of it. And the earnings in this part, you know, essentially acts like a ratchet. Most part, it only really ratchets up unless we can get into this later. Because in the sector ones, it actually does drop. But at the macro level, it effectively doesn’t really I mean, it could, it just has never happened. And it would, it wouldn’t make sense unless we were experiencing like, extremely deflationary. And this an investment oriented kind of scenario. And so, you know, what we’re looking at here is me saying, hey, you know, historically, how cheap do these things get versus what their potential EPS is. And that doesn’t really change, I mean, things really do kind of price to that potential forward. And during these liquidity crisis, as we get really deep into that left tail, and, you know, we didn’t quite get there for large cap and mega cap last year, because as they were starting to get into that freefall mode, we got the policy response. But you know, in the mid cap space and the small cap space, in the value buckets, we definitely saw that happen, depending on how you’re segmenting the market, and which cross sections you’re looking at. A lot of these really did hit that, you know, one percentile valuation and these kinds of valuations that we associated with the depths in both 2008 or 2009, depending on which sector we’re talking about. And so, you know, that’s kind of the core part, you look at these things and say, hey, you know, the story looks good. And you know, the fundamentals look good. And maybe there’s a lot of expectations, but then you go back and you say, Okay, well, let’s take all of that away for a second. Let’s see, you know, historically what we could expect to see in a left tail. He’s getting these kind of really scary numbers, you’re starting to see, for large cap growth right now, a full on tail scenario would be a 70% drawdown, I think most people, you know, really can’t imagine that. But if you’re invested in pretty generic, you know, small and mid cap beta, at the beginning of last year, you saw over the next call at 10 weeks you got there, you went from a pretty generic, you know, probably 75 to 80% on valuation down to a one percenter.

Corey Hoffstein  12:09

How would you respond to the criticism that valuation is a really blunt timing tool, in that in many ways, comparing current valuations versus historical valuations is sort of short structural upward shifts in valuations that seemed to occur over time in developed markets,

Guillermo Roditi Dominguez  12:28

you got to take risks somewhere, right, you’re gonna have to take a risk of being wrong somewhere, you’re gonna have to take a risk of your framework being wrong, I think about that a lot. We’ve tried a lot of times to experiment with changing this for say, not necessarily lower rates, because then you will just kind of be double counting growth. But talking about this kind of like maybe like a Tina environment where you’re talking about very negative real rates, and you have like a really flat and really negative real term structure. And, you know, we find that in those cases, you know, you absolutely do deserve a slight premium on the equity side, especially because at that point, you can kind of achieve, you know, better results on corporate equities, through the use of, you know, really inexpensive leverage and through lowering your cost of capital. However, if you’re in that kind of environment, you’re not really dealing with like a growing capital base, you’re dealing with probably maintenance capex, and you’re really talking about liability repricing, which happens really slow. And I do want to say that the liability repricing cycle has been, you know, absolutely phenomenal these last 10 years, you know, a lot of people have really fought it. But if you understood the potential that liability repricing can bring to that residual equity. It’s a really, really powerful tool in it. But it moves really slowly, you know, liabilities, take anywhere in between five and 10 years to fully reset, especially now that we’re seeing corporates issue, you know, much longer. Aside from that, you can say that, hey, you know, these earnings yield doesn’t matter, our price earnings ratio doesn’t matter. But I mean, you’re talking about the earnings, which is your income as a shareholder, which you’re going to realize through dividends or through buybacks or through increasing book value and increase capital formation and the price you’re paying for it. It’s like saying that, like the bond yield doesn’t matter anymore. Because it’s structurally different. Well, maybe we can’t expect the same bond yields as we could five or 10 years ago. But the discount rate is always going to matter. And the price that you pay for an asset is always going to matter.

Corey Hoffstein  14:27

So one of my favorite quotes that I’ve seen come from you, you know, something you put out on Twitter, was you’re talking about when it comes to beating a 6040 portfolio. It’s all about either the, quote path or destination, but not both. What do you mean by that?

Guillermo Roditi Dominguez  14:45

This is what I say is my golden rule path, your destination but not both, you know, is something that that goes back. I’m going to probably talk about it for about 10 years, and it really comes to a function of if you’re a highly skilled market participant, you have a decent shot at looking at an asset, and thinking what it should ultimately be valued, at some point in the next five years, right, you’re gonna be able to say, Hey, this is cheap. And I think at some point in the next five years, I don’t know where it’s going to be in five years. But I know at some point, I’m going to have an exit at my objective price. And likewise, you can say, hey, this thing is trending. And you can identify a trend and you can be like, you know, what, this is a trend, this trend is gonna keep going. If you try to do both things, you’re gonna get both wrong, you can get a decent hit ratio at identifying kind of a market context and short term price path, you can get a decent idea at identifying, you know, large dislocations that may take some while to get worked out. If you try to do these both, you’re gonna get them wrong. And I think the easiest analogies for these that I think most people will understand our value and momentum, right? Values, destination and momentum, this path, and they pair well, you know, and I think doing them systematically. And pairing them systematically is one of these things that has really worked out, because there’s such different approaches. And so they really provide like, an actual diversification benefit. And so I think that’s the main way to look at it. And I think a lot of people have tried to be clever over the last few years. And there’s been various attempts at pairing value plus momentum into systematic products. And we’ve largely seen that, that that’s kind of a disappointment. So in

Corey Hoffstein  16:35

a lot of your writing, the idea of positioning, and really, in particular, constrained positioning is a really common theme. I know you started your career in a back office role. Can you speak a little bit to us about how that vantage point informed your view as to why positioning is such an important feature to keep track of?

Guillermo Roditi Dominguez  16:55

I think I first became aware of this, when I was working in the back office, and I was either working with trade ops, or sometimes with ops, there is just an incredible amount of herding behavior that happens, I don’t really necessarily want to know why. I mean, I remember when I started, there was the Kramer effect, you know, after Mad Money, or what is it called Mad Money. After that show aired, you know, whatever the guy was telling you to buy, or someone telling you to sell, it would move, you know, we’ve seen it in the barrens effect. We’ve seen it in this kind of like collective imagination that takes place. And I think it’s very hard to sit next to somebody that’s making money. And when you’re not making money, and you start kind of looking over the shoulder and saying, hey, you know, what are you doing? Maybe you start looking a little bit of that, we saw that a lot of times when conditions lend themselves to uncertainty as to what was going to likely work, people crowded into ideas that somebody else gave them, you know, it’s it was easier for people to follow what the Southside was giving you what the analysts were offering. And obviously, we see these in things like investment FADs. We’re seeing it right now, in like the SPAC ecosystem, where there’s a lot of excitement in it. We saw it earlier this year, and these hyper growth companies where the collective imagination really thought of all of these possibilities of these kinds of unbounded potential for growth and for profits, and for new technologies. And people hype each other up, and then they go online, and they talk to each other, and they hype each other up even more and, and you kind of get these crowding and positioning. And so one of the things that I’ve really tried to do is try to see where that kind of fast money is moving. And normally we think about, you know, hedge funds as fast money. But I think lately, we have to really consider the individual investor as even faster money, because the things that hold their attentions, and their imaginations change awfully quick. One of the ways that we do this is, you know, just tracking these narratives and, and tracking how they manifest themselves in investment instruments, whether that be it used to be, you know, mutual funds, or they’re not really worth tracking anymore, especially when you’re getting daily data from ETFs. And that stuff is, you know, really high quality.

Corey Hoffstein  19:17

So you mentioned retail investors being the fast money now. Are there any other bigger players that you’d like to keep your eyes on in terms of positioning? And if so, how do you think about tracking them?

Guillermo Roditi Dominguez  19:28

Yeah, I think if you’re doing this here, so you need to keep track of systematics systematic strategies are humongous. And as their name might clue you into they’re kind of predictable, and you can absolutely model what a vanilla CTA is going to do or what multifactor fund is going to do. You can absolutely model what the 6040 rebalance is going to look like or what the target date fund rebalances are going to look like. And I know you and I have talked before about the growing importance of the target date industry. And whether these rebalances happen through, you know, somebody actually going in there and selling something and buying something or just diverting inflows or organic cash flows from dividends and coupons to assets that are currently underweighted. These things are all happening, you can track them, you can identify more or less when they’re going to happen. And obviously, the big one, and I think the one that gets the most attention, whenever I tweet about it, is these equal risk contribution portfolios. And some people talk about it as risk parity, both levered and unlevered, we have these portfolios, and they’re kind of related portfolios, which are the risk controlled portfolios, where depending on where realized volatility has been, you can get a pretty decent idea of how they’re going to be positioned. If you want to stretch it, you could do the same thing for call it like auto callable notes, structured notes. I mean, if you have an uptrending market, you can just basically pocket in that every month, you’re going to be ratcheting up the barrier, and the amount is going to stay stable. And you know that you start breaching those barriers, anywhere between 10 and 20%. Below the highest closing month, you know, you’re gonna start seeing things kind of spiraled down a little bit. But, yeah, I mean, to stick to the answer to your question, I think the easiest way to do this is to replicate what the most kind of naive implementation of a strategy is, like, if you want to get a feel for what, like the CTA universe is doing, then go out there find like a 1015 year old paper about time series momentum, and reimplement, that you’ll find that it’s fairly easy, they’re given it away to you in the papers. And they’ll give you a very, very good start, you know, you don’t want to build a model that that is better than the models that people are using your you want to build a model that is the highest common factor of the models that everybody is using, right? So walk me

Corey Hoffstein  21:53

through a little bit why you think the most naive implementation is ultimately the one that’s worth tracking? Is there any risk that looking at something that’s too naive, might take you too far off, what actual implementations might be positioned as

Guillermo Roditi Dominguez  22:10

sure that’s probably a risk, I haven’t found that to be true in practice. I think that if we’re being practical, and you go out there, and you look at some of these alternative options to you know, indexing and market cap weighting, call it like, equal weighing, or some of these mentum ETFs, that have come out some of these different factor implementations that have come out in the long side. And we’ve discussed it previously. I mean, some of these implementations are extremely naive, and how they do it. And I think the complexity of implementation, when you are doing a systematic product is it’s a double edged sword, you can try to improve on call it your academic factors, but you’re going to be benchmarked to those academic factors. So you better make sure that your implementation is going to outperform at the correct times, or at least not underperform when you’re up for review. Because you know, that could turn very ugly for you very quickly. And, you know, if that’s the benchmark, there’s really, I mean, obviously, everybody wants to do better. But there’s also this incentive of like, well, that’s what they’re paying you for, like, that’s what they asked you to do. Like, that’s what you should deliver, you could try to like upsell them on something better. But ultimately, these institutions are sophisticated, they know what they want, you’re not talking to like Joe retail that needs hand holding, you know, if that’s what they’re asking you to implement. That’s what you deliver. And so that’s one of the reasons I think that a naive implementation works best. And the other one is that you’re gonna get a mix of a lot of different implementations. And if you start getting into the details of some of them, you’re going to miss how the collective behave right? You need to have that common root implementation, right, and you’re going to miss details, you’re going to have information loss at the edges, but ultimately, it’s going to catch the right signals, when you really need them, you’re going to lose a lot of smaller signals, but the big ones you’re not going to miss.

Corey Hoffstein  24:03

So tie this all back for me to the 6040 positioning. Let’s say you have your naive risk parity or equal risk contribution. You’ve got your CTA, you’ve got your auto callable. How is that positioning that you’re looking at informing how you’re underwriting risk in the 6040?

Guillermo Roditi Dominguez  24:19

I think we’ve been running this particular strategy formally, for I want to say it’s at least seven years, we’ve never actually held a portfolio that looks like our benchmark ever, I think, except for one year, we actually delivered returns that were, you know, above the benchmark, we did have a couple of drawdowns that were not pleasant. But I think one of the ways that you do this, as you know, you look at decision and you say, hey, the people who move quickly, where are they concentrated? Right? Because you don’t necessarily want to be concentrated where they are and if CTA is our I’m going to use an example that is timely to when we’re recording this but you know, CTAs right now are extremely short. or treasuries, the trend has been really strong, the prices have been cratering week after week, and that’s delivered signals to them that they should follow the trend. And the way that they position a lot of times is they pyramid, you know, that means that they increase their position, every time the trend is confirmed. And so the more the trend goes, the bigger their position becomes. So I look at that, and they say, Hey, I may not love where interest rates are right now relative to like, our expectations of Ford growth and inflation. But these people can and will change their positioning on a dime. And they could go from being short $50 billion of tenure equivalents to being long $50 billion of 10 year equivalents in the matter of a few weeks, the same thing where you get the fast moving retail crowd, especially the people that are looking for active stories, trends that are moving, you know, places where they’re getting the volatility that they need to get that exciting trading that they find that fills their interest and their the risk profile that they seek. And we say, well, do we really want to be in here? Do we really want our short term performance to be predicated on whether this stock is still considered hot by the people who are on these investing forums, or mailing lists or whatever, we look at the hedge fund, you know, the so called hedge fund hotels, right? Where, well, you know, if all of these hedge funds are extremely long, these names and in large size, well, who’s the exit, like, who are they going to sell to, and it becomes this kind of approach, we’re not building a portfolio from scratch, we’re taking a portfolio and we’re hacking pieces away. And one of the things that we found is that, through the magic of statistics, one of your other guests could probably explain this very well, I’m not the person for that, it’s actually really hard to deviate substantially from a benchmark, if you have a big enough sample sample doesn’t have to be that big. As long as you you know, you’re sampling across sectors, you’re going to do pretty good. And even, you know, within sectors have you look at like the historical returns of like an equal weighted and market cap weighted index, you’ll find that they go through periods where one of them outperforms the other, but ultimately, they just kind of ended up coming back to having the same returns, you look at like the returns of like, you know, mid cap versus small cap, you find the same things, obviously, there’s some places where you’re not going to where that’s going to be impossible, just because the structure at the firm level is different. And so that’s not going to happen. But once you kind of accept the fact that if you have a big enough sample, over time, it’s going to be very hard to deviate, then you can feel a lot more comfortable and just hacking things out of your portfolio. It’s like, do you really need a bunch of like, investment grade corporates, you know, that are leaving you a few basis points of extra spread? I mean, I don’t think so. I mean, I think that sometimes there’s a use for them. And we have these big market portfolios that include like, the fixed income, the AG, which was a big ball of noise. And on the equity side, you have a market cap weighted index. And you can, you know, you can feel free to just take entire sectors out. I mean, we do it all the time. I mean, right now, you know, we’re running a grand total of three sectors. And that’s it. And once you kind of understand the individual drivers of the sectors, and we can talk about this more, you can start feeling really comfortable in building these portfolios by looking at them and saying, Hey, okay, the index is giving me these risk scores. And so right now, I think that a broad market cap weighted index has a left tail where you could possibly lose 70%. And then you can drill down and say, Okay, well, where’s the risk coming from, right? And sometimes that will come from a sector, sometimes it will come from a factor. And you can get to these places where you can just kind of like, chop one out and be like, okay, you don’t want this all right. Don’t have any momentum exposure, or, I mean, I want to, please don’t take that as a recommendation because momentum is notoriously unstable, and unpredictable. But you can say, hey, you know, I want to overweight value or I want to underweight value, or like, hey, I really want to overweight quality or like, you know what, like, I don’t want to overweight quality, you can say I want to really heavily overweight, like small cap or mid cap. Or even if you’re using, you know, a more basic logical approach where you can say, hey, I want to overweight growth, or I want to overweight value and that two dimensional kind of classification system. And there’s lots of these risks that were they, they’re correlated, and often they co integrate relatively well. And you can trade back between banks and insurance and utilities and staples. It’ll be fine, you know, energy and basic materials. And I think that’s kind of how you use all of these ideas to build portfolios. You say, hey, what am I really not willing to do is and for example, for us recently, it was like, Well, I’m not willing to take you know, that small probability of taking a very nasty loss. If all of a sudden retail traders decide that hey, I need to like focus on my job. I got taxes to pay. I got like, kids that are going back to school. Well, I don’t have time to be sitting around day trading all day, and you have the sudden loss of interest. And then who’s the bid for a lot of this stuff. And I like to say, you know, it’s a long way from growth value. So that’s essentially how we use it. In practice, we look at where we see an intersection of risks that we find higher than we necessarily need. And where the positioning tells us that maybe it’s not the right time to take that risk.

Corey Hoffstein  30:30

So I do want to get into some of these nuanced views on equities, and we’re going to talk about them. But before we dive in there, the last sort of big picture positioning thing I wanted to talk about came from some of the investor letters that I read of yours, where you’ve written quite a bit about, I guess, what you call the fractal nature of economies. And I know that one factor you put a lot of weight on is tax data. Why are taxes such an important input for you both from a philosophical and pragmatic perspective,

Guillermo Roditi Dominguez  31:02

a lot of times when I’m talking about the tax data, I’m talking about the daily Treasury statement data. This is not a sample, this is not a survey. This is a daily one day lag data that gives you information as to the deposits and withdrawals of the federal government, one of those line items. I mean, I think the ones that are most commonly talked about are deposits for income and employment taxes withheld. And the other one is for tax refunds, where you can get a live look down to the day as to how fast tax refunds are coming out. And sometimes that’s more relevant than others. Right now, I think it’s pretty relevant. I think pretty soon, we’re going to be able to see real time, the stimulus money going out. If you’re fast money, that’s probably of interest to you. But on the employment taxes, what it does is it gives us a live look at the employment situation, right, you could wait five days after the end of the month, and get the jobs report, which is going to be based off a survey that happened about four weeks before that release, which is based off a sample that may or may not be right, which also subject to revisions, and has like a margin error of error of like 100k. And so I don’t think it’s particularly useful data. I think that if you look at income and employment taxes withheld, and I’ve been looking at the stuff for probably about a decade, and we’ve developed a fairly sophisticated model for detecting the patterns of cash flows in there, there’s probably about a dozen patterns in there, whether what day of the week, it is whether it is the 15th calendar day of the month, that’s when small businesses deposit their taxes withheld. There’s all sorts of these patterns that manifest themselves, you know, we have monthly seasonality, we have weekly seasonality, we have daily seasonality, we have special days of the year, the days surrounding Tax Day in April are irrelevant. The a couple of days around Thanksgiving, Christmas are irrelevant, you could try to like come up with some big explanation as to why these are but they’re so reliable in the data that we’re getting, you know, our margin of error for estimating what a day’s deposits is going to be is really small. And I can forecast these out, probably about three or four years out. And so as we see them as we see them how they come with relation to our forecasts, we have a pretty good idea of how the economy’s going to be doing, I just want to say that these are absolutely not useful for forecasting the employment report, because the employment report is based on a survey, which is based on a limited sample, which has a margin of error, and you have other things to take care of. But it’s an incredibly accurate way of predicting, you know, what is going to be one of the biggest components of personal income, which you wouldn’t find out for another four weeks if you had to wait for this data. And that gives us especially around kind of like inflection points, and the economy gives us really, really valuable information where we’re not needing to wait for confirmation of like aggregate macro data. I know that these days, there’s a lot more like alt data kind of things, you know, people are looking at like restaurant reservations or like some of these like scheduling online applications for jobs and things like this. But this is like if you had access to every single Americans pay stub, and sure you don’t know what everybody’s getting paid, you’re getting an aggregate and you don’t really know what the distribution is of this, whether it’s like a few more people making a lot more money or a lot more people making a little bit more money. But it gives you a really, really good look as to how much money is being generated from employment. And if you’re kind of continuously calibrating the effective tax rate based on once like the jobs data comes out once you have a couple of revisions in and you’re kind of sure that it’s pretty good. You can start using some of that to estimate what the effective tax rate is. And once you Know that you have a pretty good idea of distributional how that is moving. And we find that for like, informing our macro views, it’s been invaluable because it’s put a brake on our risk taking at times where we’re didn’t really feel like we shouldn’t, you know, market signals didn’t tell us to. And it worked. And likewise, it has given us really quick turnarounds, not necessarily during market bottoms, because market bottoms happen faster than the real economy starts getting better. But during periods where people had kind of become disenchanted with a macro forecast, and people had been kind of thinking that this economy is not growing, I came into December with kind of lowest expectations. And then got December, January and February, we had these indicators just absolutely ripping and, you know, in the jobs report, December and January was not good. And then we got February’s and we got all that makeup. And, you know, eventually the jobs report catches up to the cashflow data and the tax data. And to answer the second part of your question, the reason that this is important is because the economy is fractal. And what I mean by that is very, very literal, like the economy’s a bunch of self similar processes, scaled up. And each one of these is made up of other processes that are very similar in structure, but just smaller in size. You know, the same way that a national economies made of state economies and state economies and major city economies and city economies of like, etc, we have these self similar patterns. And one of the things that I think is very important, and that I’ve really tried to stress the last years is that, because of this structure, the economy can absorb incredibly large shocks, they can absorb really long shocks, and the kind of sort of shocks that affect simultaneously a very wide number of industries or geographies, what it can’t do is absorb many of these shocks at once. Once you have these shocks kind of coinciding, the losses that you see to final output and to potential output, start increasing nonlinearly I think you can think about that if you’ve ever lived anywhere that has extreme weather, you know, whether that’d be fires, or hurricanes or, or snow storms. And you know, you get a few, you know, a couple snow days here, the city comes to a halt, you know, nobody’s revising down their economic forecasts for the city, you’ll make it up. But you have too many of those days in a year. And all of a sudden, people are getting a little nervous, right? We started having extreme weather in too many places at once. And all of a sudden, like supply chains are not working that well. And when we talk about the fractional nature of the economy and markets, that’s really what we’re talking about, you know, you, you can have a couple of things going wrong in many places at once. You can’t have like, big shocks that lasts a long time occurring in lots of places that affect lots of industries at once. Because then you you know, the wheels come off. I think we started seeing that with the government shutdown in 2019, where, at first the government shutdown was not a big deal. But eventually we started seeing downstream beneficiaries of government spendings responding that hey, like, this is really bad, we’re getting really messed up. You know, we started seeing air travel disrupted, you know, we started seeing things that were significantly downstream disrupted, because this is one of the things that spreads out very fast and wide. And I think this was one of the risks that we had with the pandemic is that we had these huge shocks that happened everywhere at once affecting almost every industry, every geography, and they were all happening at the same time and for prolonged periods of time. The flip side to that is that if you understand that, then you also understand that once you start seeing improvement in any of these adverse effects or adverse factors, the recovery is also nonlinear, right? Like when you start getting the same way that it kind of spirals downwards. You do rocketship upwards as you start carrying these things. You don’t need to open the whole whole economy, you start opening parts of it and all of a sudden, the whole thing starts looking pretty normal again.

Corey Hoffstein  39:11

So I want to dive into some of the sleep specific aspects of what you do. We’ve alluded to it a little bit Within equities, where you talked about some of your current sector tilts that you have right now. But it strikes me in taking a top down view Within equities. There’s a huge number of degrees of freedom in which you could place these trades. You could talk about region’s market cap sectors, industries factors, you could even build your own thematic baskets, right, you might have a reopening basket or an inflation sensitive basket. How do you think about tackling this problem when there are so many different ways to play it?

Guillermo Roditi Dominguez  39:47

I think about it in the same way that I think about most things, it’s make it simpler, but making the problem smaller. One of the things that I think about as I think about our clients, I think about what they want, where they live, what they’re exposed to Do Do I need to have a view on Japanese banks? I do not. Do I need to have a view on whether, you know South Korea is going to outperform Malaysia? I absolutely do not do I need to have a view on what the British pound is going to do? I do not. There’s also, this is actually really great, because we have the immense privilege of being in the country, that one has the best capital markets, we have a low corporate tax regime, at least now, we don’t get taxed on transactions. We don’t have heavy taxes on dividends. We have indices that offer us broad diversification. You don’t have indices that are like 70%. Banks, you have these things that represent like a fully well rounded economy, they give us a really good sample of the economy. A lot of people like to say, well, you know, the s&p 500 is not the economy. And sure it’s not. But I mean, it kind of is, I mean, when you’re talking about capturing that much of the gross value added of an economy, just by the way that samples work, you’re not going to be able to stray too far off. I think, at one point earlier, before we had this very sharp recovery in small cap stocks, the s&p 600, you know, it’s 600, stocks diversified across a bunch of sectors and a bunch of industries, you have this really great sample of the smaller companies, but it was like less than a trillion dollars of aggregate market cap. And that’s not even like just the float that was just like the aggregate full cap was less than a trillion dollars for the whole index versus you know, like 30 trillion or something like that for the s&p 500. And what I’m getting to with this is, we have the ability to fine grained allocation with the s&p 1500 universe, I restricted the s&p 1500 universe, because my process is heavily weighted on using earnings as an input and the difference between the s&p 1500 and you know, the Russell 3000 universe is that you got to have earnings to to get into the s&p Club. And so I look at that, and I say, Okay, well, this is easy, first of all, eliminate anything outside of this piece, 1500 companies, and then I look around the world, and I look at their indices, and I’m like, Well, where else in the world? Can I get a well diversified index that has representation? That is an adequate representation of that economy, at the sector, and at the industry level, where I’m going to have friendly treatment as an owner of the shares? And the answer is, there isn’t, you’re not going to find deeper or more liquid or markets with more choice. I mean, the US is like the super Walmart of financial instruments, and I don’t see any reason to go anywhere else. I mean, I think at some point, in my career, I owned a bunch of like, European stocks, and they paid, you know, these big dividends, which was nice in theory, but then, you know, they withheld like, 35% of them. And it’s like, cool, that’s great. And so that’s, I think, one of the easiest ways to do it. If it doesn’t trade in the US, it’s really not a great asset, in my opinion, if it was it would have an ADR, or like a dual listing or something. And the other way that we look about is that you’re right, there’s absolutely too many degrees of freedom. So what you want to do is you want to say, Hey, these are the things that I’m where I can kind of like distill my macro views. And I think that comes down to factors, sectors, and approaches to how indexes are constructed, right, in terms of weighing. And the one that we use the most, is sectors, because you kind of get a pure play into something that is going to behave differently than the aggregate. So you’re going to be able to get that out performance, you’re gonna get that deviation, you know, if it’s out or under performance, you know, still in the cards, but that’s one way to have a portfolio that differs than the index. The second approach is obviously factors. And here, I think that there’s only three that matter and I would say that it’s low volatility, value and quality. And the reason I don’t include momentum in that it’s because it’s not sticky it changes and you’re at the whims of the implementation right like a quality stock today is still a quality stocks six months ago, most likely a value stock today still a value stock in six months, unless, you know, it goes up in price a lot. And in which case, you’re okay with it not being part of the basket with momentum, you’re just kind of having to trust the style. And so I would put when we talk about like low volatility, for example, we talk about stocks that exhibit a low volatility right. So you know, you’re probably talking about consumer staples and things that have like very little leverage. Now let’s talk about like low volatility as a portfolio concern auction style, right. And so I think in that respect, that’s where you have like momentum momentum is similar to a minimum volatility portfolio, where you’re not necessarily picking stocks with low volatilities or picking stocks that when pulled together are going to exhibit low volatility. And so these are things that happen more at a portfolio level and have less to do with like, the intrinsic nature of a specific stock. And so I think these are two different things. And finally, you have alternative weighting schemes, whether that be I think, right now, there’s some pretty popular ETFs that use momentum at the sector level, then you have your traditional market cap weights, and then you have your equal weighted indices. And I think, for us, you know, what we do is we use the equal weighted indices, the market cap weighted indices, and we use some selections of the factor exposures. Finally, we break it out by market cap classification, right, so, small, mid and large. And once you do that, you get to a manageable number of degrees of freedom, you know, you can kind of limit your investable universe to a couple of 100 instruments, which, you know, it’s still a lot, but you can basically hold most of them in memory. And you know, you know, what you need to add when you need to tweak the portfolio in one way or another what you need to subtract, you know, which of these exposures pair off? Well, if you want to amplify volatility, and which ones pair well, if you want to, like minimize volatility,

Corey Hoffstein  46:32

maybe as an example of how this framework ties together, you could talk a little bit about the current trade, you’ve been pretty vocal about, I think you’re sort of calling it your come home trade on Twitter lately, where you’re issuing the more expensive tech sector tilting more towards, I think, what people would consider to be sort of the defensive type sectors, can you walk us through your thinking there and sort of how it ties the big picture together?

Guillermo Roditi Dominguez  46:58

So yeah, the Coming Home portfolio, and that’s the joke here is that everybody, you know, individual investors have had a spectacular year, retail investors have had this really nice period of they got in when the market was cheap, they had these big gains, it’s been a spectacular environment for people that are willing to take a lot of risk or that think that they’re willing to take a lot of risks, and they’re not the same thing. And everybody’s kind of been, you know, really hyped. It’s been really fun. I mean, I think it’s felt like a really hot craps table. And anybody who’s ever played craps and has experienced a hot craps table knows that that’s like a really, really fun thing. I think it’s coming to an end, I think it already started. And I think as that happens, everybody that was on this kind of like risk seeking walkabout is all of a sudden gonna start seeing the virtue of these kinds of defensive stocks. Once that you don’t lose sleep over that deliver consistent returns, maybe some people are going to shy away from the day trading the act of management and start doing a little bit more indexing. In which case, you know, if you’re a retail trader doing individual ETF and security selection, you’re probably not picking, you know, staples and utilities and these boring companies. And so the idea is that people are going to find out that maybe their risk tolerance isn’t exactly what they thought it was, while everything was going up. Because 15 or 20, or 30%, balls on the upside are very different than on the downside. So I think people are going to, you know, have their moment and they’re going to see the error of their ways, they’re going to kind of start getting more into like broad diversified. And this is and that’s going to bring these defensives into their portfolios. Likewise, I think that the RIA crowd and the private wealth management crowd, they’ve gotten a little bit too hyped. I know, there’s a very popular blogger out there that came out with a blog post about a month ago, advising people to just buy everything, buy anything, you know, like, whatever it was, that was being sold, just buy it because everything is going up. That was probably an exaggeration. But I do think that there’s kind of this very heavy risk seeking attitude. And I think everybody’s going to dial back their bravery a little bit. And after you feel that fear of those draw downs, you know, the studies about the pain of the drawdown versus the thrill of the rally, people are going to see the value in having these as part of their portfolios. And that’s where I’m positioned, I think, the value crowd that has seen extremely positive results. They’ve really been compensated for their incredible patience over the last few years, and they’re finally reaping the rewards of that patience. I think they’re going to look around and see well, what was value, you know, three months ago is not really feeling so valued today. You’re going to be able to look around and maybe you see some of these defensive stocks where these things are not going to grow 10% a year, maybe you can get a low level of uncertainty on their for growth, and maybe that’s in the mid high single digits. And people are gonna say, Well, you know, like, that’s not so bad. Some of the gains that we’ve had to hear and rotate them out. And through that, they always say that the road to you know from euphoria to despondency is there’s a lot of stops along that road. And one of them is that relentless, you know, Relative Value trade. And so there’s a lot of factors that are growing there. In terms of where we’re seeing positioning, we’re seeing that end users of Exchange Traded products really did not want any of this exposure. They dumped it, you know, there was huge redemptions from these ETFs. There was redemptions from the 40 Act funds, these things are underrepresented in a lot of the systematic baskets, and I think it’s time to give them a chance, I think there’s a lot of things lining up, where whoever was going to sell these things is going to sell them. And as people realize that, you know, I think you had a tweet recently that, hey, you know, for the small cap ETF to maintain its current distance from its 200 day moving average, you would have to go up some really unrealistic number every day. I think, as you know, these things catch up to everybody in these realizations catch up to everybody. And maybe after we start getting some of that long term, capital gains treatment coming in, people are gonna say, hey, maybe it’s time in there, we’re gonna start seeing some positive price momentum there. And once these things start showing that they’re not bottomless pits of underperformance, you know, people are gonna come back to it. The other part of the Coming Home portfolio was, it’s actually really, really simple. And that’s banks and insurance companies paired with the longest duration you can find out there. I personally, I’m a very big fan of 30 year zero coupon bonds. But these things have very natural risk offsets, and where one might want to own financials now, because you know, we’ve talked about this before, they’re about to find their way into the momentum basket. And they’re, they have these relatively good fundamentals, they’re access capital, they’re about to be allowed to do buybacks. And so you’re going to have them falling back into favor with people who look at and value shareholder yield. But of course, you have the very high risk that if interest rates go down these things, these things are not going to stay where they are. And so like I mentioned before, once you have that big universe, you can find things that offset each other. And the Coming Home portfolio is really just about the idea that investors are going to transition from wanting a portfolio that’s constructed to maximize their Beta, because they think that everything’s going up. So you might as well get the most juice that you can get to a portfolio where they want to say, I don’t want to think about where, what it’s doing day to day, I just want to know that it’s gonna be fine. And that if I look at it in three months, it’s not going to have blown up. And that’s really what it is. I think that we’re just slowly moving in that direction. It’s not going to be overnight might take a couple of months, it might take a drawdown to put the fear of God in people, but it’s absolutely going to happen.

Corey Hoffstein  52:54

I think this coming home portfolio is an interesting juxtaposition, or, or perhaps, maybe it’s tied directly to a quote, I hear you say a lot, which is the right tail is harder to manage than the left. Can you explain what you mean by that?

Guillermo Roditi Dominguez  53:09

Yes, the left tail is scary, but the left tail is familiar. Anybody that has worked in this business for any non trivial amount of time knows what a crash feels like. And it’s actually pretty easy to know what to do in a crash. All you got to do is buy you know you got to do is buy you know, if you had things that benefited from that risk off sentiment, you can sell them you reallocate you reinvest your dividends, you make sure that you’re as diversified as possible. The left tail is not a time for having nuanced views, you know, when everything is cheap, just buy everything, don’t be the guy that bought the one stock that didn’t go up on the right tail, you have a very different dynamic. On the left tail, you have very very, very high realized correlations, very high implied correlations, everything is either uniformly cheap and then once you get to the right tail you get these things were very weird things start happening for example, anybody that I guess there’s probably not as many people that remember that anymore, but just because we tend to block out these bad memories but bubble was absolutely brutal. Because you had what everybody would have generally agreed were blue chip kind of companies that had nothing to gain or lose from the internet becoming a thing taking these humongous humongous losses at the end of that right and once you get into that deep right tail, like you have this kind of like everything’s pretty expensive kind of scenario where it’s like scary because you know that it could all come to an end and everything could go down in price, but then there’s like that deep right to where it just gets like terrifying because you say okay, I’m gonna sell these growth stocks because I think they’ve grown up way too much. I’m gonna buy these kind of like high quality blue chip stocks that they seem like relatively okay valued and then you wake up a month later and you check your account statement. You’re down 30%. And it’s at that point where the euphoria takes in, where you’re no longer feeding that bubble just from like new inflows into the market, you just got to sell anything that’s not part of that euphoric trade in order to feed it, and you start seeing things, not just like failed to keep up with the market, but just get absolutely decimated. And that, to me is terrifying. Because the way that my process works is, I would say, well, growth looks really expensive. Let’s avoid growth, let’s avoid the intersection of like high growth and momentum and like let’s maybe overweight value a little bit or overweight defensives, but if you had done that in like a real bubble, you would have lost 40% of the value of your portfolio by the time you got to the top. It’s an environment where like, you can do whatever you want, but I just would advise anybody to never try to like get short. I mean, people always tried to short these things everybody wants like that hero trade, but the dynamics of it are all against you on the left tail shore, you know, brokers are going to revise their margin requirements for levered traders. And you’re going to have some things that are on palpable there. But largely, if stocks go down 10%, well, your maintenance margin went down 10%. If stocks go up 10%, in your short while your current value is down 10%. And your maintenance margin is up 10%. These dynamics are absolutely murders. And I think we saw this in late January with a so called mean stocks, I really can’t believe that. That’s something I had to say. But you might have really great risk management, like you could be really good and have these great valuation models and these great risk management system and give yourself enough room so that if you get deep into the right tail, you’re not the person that gets blown out. But guess what, for every smart person like you, there’s going to be like two dozen idiots that say, Well, if we just add a little more leverage, we’re going to make more money, if we give ourselves a little more juice, we’re going to make more money, it’s not going to get that far. And then the first one of them is going to get blown up. And the margin clerk is not going to care about whether like the exit out of these things as well executed or not, they’re just going to enter markets sweep this stuff out, and then that’s going to trigger the next one. And that’s going to trigger the next one. And all the way until you’re very well risk managed process is absolutely blown up, right. And that’s the thing with being a systematic player that you have to internalize. And also, I think anybody that is a levered player has internalized or if they haven’t, they’re probably broke, is that you’re only as good as the worst risk managed position that overlaps with yours, it doesn’t matter how well you did it. If somebody else out there did it poorly, and they’re in the same trade that you’re in, it’s not going to be good for you. And, and that’s one of the parts that is scary for me. This time, however, I this is something we talked about just last night, this particular right tail has its own scary parts. And I know a lot of people don’t like to say that things are a bubble. And I definitely don’t like that term. But it’s undeniable that we’re in the right tail. And we’re pretty deep in there. I think yesterday I broke down the s&p 1500 universe across market cap classification and the growth or value distinction, right. And so there, you know, we had six different classifications and measured where they are in terms of their valuation quantiles. And I think they went between, you know, 74.7 and 99 percentile valuations, which is when my mind it’s pretty deep in there. But when you took like a naive, you know, equal contribution model that took equal contribution to each one of these six exposures and you mix them and you score that, you would find that you’re at the 99.9 percentile. And that’s because previously, we’ve had times where, sure there’s a few things that are really expensive, but there’s a few things that are also cheap. And so there’s places to hide. Sometimes those places to hide are places to hide and get really beat up like Blue Chips bubble, but right now, we have one of these scary, right tail scenarios where it’s like, well, where do you hide on it’s like, you could go out, you could buy some corporate bonds, you could lay low and have more cash, you can try to mitigate your exposure with defensives and low beta sectors, like I just mentioned, you could try to structure things but there’s no escaping the fact that once you’re here, managing a portfolio becomes very, very different. When you’re kind of in the middle ranges of valuation, you’ll call it like a 75th percentile. A one percentile movement might mean maybe 50 basis points to 100 basis points in price, depending on which thing you’re looking at. Once you’re deep in this kind of right tail scenario. You’re talking About a one percentile movement, you know, moving from the 98th to the ninth percentile, potentially being 5% in prices. And so if you want to hold, you know, market weighing here and a market portfolio, you better make sure that you’re going to get to sell in that point 10% of scenarios that have not happened yet. And I think that’s the hard part. I think, you know, being, being a person who gets hired to invest money in this scenario is really hard to manage, you have to manage people’s expectations, which is difficult, you have to explain to them the risks, you obviously want to outperform the benchmark, you have to be very careful about how you do it. And you have to manage your own emotions, it’s very easy to either say, Okay, I’m just going to go right to the benchmark, because then that way, you know, nobody can fault me, because I’m just going to do what the benchmark does, where you can go in the other direction and just decide that you’re gonna go all cash because it’s scary. And I think you have to, I mean, I certainly tried to find a middle ground in there and find a way to do it, but it’s not easy. During a market crash. I don’t lose a lot of sleep. I know that all I got to do is make sure that I’m fully invested in well diversified during a market like this gets a lot scarier.

Corey Hoffstein  1:01:11

Guillermo, last question for you. I know you’re in LA, the LA area where lockdowns have been pretty tough. I’ve managed to escape there myself. But it looks like vaccine rollouts are starting to turn a corner we’re starting to do pretty well. And hopefully by mid summer, things will have loosened up dramatically. What are you most excited about doing in perhaps what will be just the new normal environment?

Guillermo Roditi Dominguez  1:01:37

I really want to go see a movie, I want to go to the Arclight Hollywood I want to see a movie I want to sit there with like a big tub of popcorn and like a fountain soda and just sit in that quiet room with like a bunch of people all watching the same movie on like this big giant screen. I mean, that’s what I’m really, really, really excited for. I know that’s a very la thing to say. But that’s what I’m looking forward to.

Corey Hoffstein  1:02:02

Well, Guillermo, this has been a great conversation. can’t thank you enough for joining me. Thanks again. If you’re enjoying the season, please consider heading over to your favorite podcast platform and leaving us a rating or review and sharing us with friends or on social media. It helps new people find us and helps us grow. Finally, if you’d like to learn more about newfound research, our investment mandates mutual funds or associated ETFs. Please visit think And now welcome back to my ongoing conversation with Harley Bassman. You’ve made a career out of being long convexity. Curious as to why you think that incorporating convexity in a portfolio today is so important.

Harley Bassman  1:02:50

Those are two different questions. The reason why electing Long convexity is, I think having limited loss and unlimited gain, mind you and a fair price is a career enhancing profile. And the opposite, of course is problematic. If you’re picking up pennies off of a steamroller, eventually your coat will get caught in the gears. And so it’s a matter of pure concept and risk management. I prefer to be long convexity, and that’s I’ll spend my time looking for ways to get this unbalanced, asymmetric return where I can make a lot more than I lose. Thus why I love being at simplicity where we basically have a long convexity profile added onto our product mix. Why it’s important today? Well, we’re looking down the teeth of a giant fiscal package. And what’s going to happen with this money. First, we have the extra money from the Fed via monetary policy. And now we have the flowing of money in fiscal policy. This is going to be disruptive. However, unlike the Cassandra’s out there, it’s unclear which way it will be disruptive, you could make the case that we’re gonna get inflation, that fiat currency will be damaged and this financial assets will go south. You could also say we have a lot of money being printed, and that money will go into buying almost everything. And financial assets could be one of them. And so you could have a melt up or a meltdown in equities or in bonds. So owning optionality right now is a fine profile. And depending upon the price of those options, it’s probably a good idea to have their profile unless you have options at a very expensive level. Right now the next I’m talking the next year or so, I would not want to have a profile where I had unlimited loss, limited gain