Value After Hours S06 E04 Validea’s Jack Forehand and Justin Carbonneau on value, growth and momo

Value: After Hours is a podcast about value investing, Fintwit, and all things finance and investment by investors Tobias Carlisle, and Jake Taylor. See our latest episodes at https://acquirersmultiple.com/podcast

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ABOUT TOBIAS CARLISLE
Tobias Carlisle is the founder of The Acquirer’s Multiple®, and Acquirers Funds®.
He is best known as the author of the #1 new release in Amazon’s Business and Finance The Acquirer’s Multiple: How the Billionaire Contrarians of Deep Value Beat the Market, the Amazon best-sellers Deep Value: Why Activists Investors and Other Contrarians Battle for Control of Losing Corporations (2014) (https://amzn.to/2VwvAGF), Quantitative Value: A Practitioner’s Guide to Automating Intelligent Investment and Eliminating Behavioral Errors (2012) (https://amzn.to/2SDDxrN), and Concentrated Investing: Strategies of the World’s Greatest Concentrated Value Investors (2016) (https://amzn.to/2SEEjVn). He has extensive experience in investment management, business valuation, public company corporate governance, and corporate law.

Prior to founding the forerunner to Acquirers Funds in 2010, Tobias was an analyst at an activist hedge fund, general counsel of a company listed on the Australian Stock Exchange, and a corporate advisory lawyer. As a lawyer specializing in mergers and acquisitions he has advised on transactions across a variety of industries in the United States, the United Kingdom, China, Australia, Singapore, Bermuda, Papua New Guinea, New Zealand, and Guam.

He is a graduate of the University of Queensland in Australia with degrees in Law (2001) and Business (Management) (1999).

This meeting is being live streamed this is value after hours I am Tobias car joined as always by my co-host Jake Taylor our special guests today are Justin carer and Jack forehand of Validia how did I go fellas how are you good how are you how are you welcome

Jens good to be here what’s uh what’s FIA for the folks who haven’t um encountered you before so Validia is um there’s really two different businesses but let’s just we’ll talk about the research business because that’s what most people might know us um as is Validia is a independent investment

Research company um the the website is Validia V idea and on Validia we run a series of investment strategies based off of the publicly disclosed methods from great investors people like Peter Lynch Benjamin Graham Oren Buffett and then a whole host of other strategies that have been written about in books

Books Andor academic papers um and you know what we look for is strategies that have kind of proven the test of time for the most you know some of the guru strategies don’t have back test behind them but all the other strategies Beyond those famous investors kind of come with

Significant back tests um and are all based on sort of fundamental do you guys recreate the BST what do you use there we use the we we kind of codify the model start running the model and start tracking the performance of it from the time it goes on the Validia site

Actually there’s a little bit of um actually should let me restate some of our models start way back in 03 those are all live and then there was a second set of models that we rolled out and some of that performance is back tested some of it is actually like live out a

Sample perform yeah a lot of the strategies are tested in the research a lot further back than we can go I mean they’ll go back decades so we don’t do that but we will try to you know when we put a new model on our site people want

To have some idea how it’s done what they’re getting because if you put it and like start the performance on time zero there’s really nothing there so we typically will put you know we haven’t added a model in in many years but when we do we typically will include some

We’ll run testing historically and include some performance with it as well that’s one of the reasons I love chatting to you guys because you have a good idea what sort of worked last year that was actually uh what actually implemented so let’s start there what what happened last year what worked what didn’t

Work so I’m going should have had this up pre and how and how did you create the uh the Cathy model that’s what which one Kathy Wood oh yeah that is one thing you cannot model um as far as I can tell at least not with factors so it’s funny

We have like a separate tool that’s like an ETF Factor report where we try to get like value and momentum and all these different exposures of ETFs and if you look at that ETF it is like zero across the board there’s like no quality there’s no value there’s no nothing um

There’s no low volatility like not not to say that it’s a bad strategy but it’s not a strategy that’s driven by any kind of the investment factors we look at is it negative is it like yeah invest to any factors well we we percentile rank everything so one to

99 so the lowest you could possibly be is one but there’s a lot of a lot of the scores like last time I looked at least were 10 and Below which means you know yeah basically no exposure to any of these factors and it’ll have momentum sometimes when those types of stocks are

Doing well but outside of that you know I’ve never really seen seen it have much exposure to anything else so last year was like kind of an interesting year I mean you guys have talked about this and we know it like obviously the leadership was super narrow coming into whatever October

November then like things exploded so like when you get that type of explosive move because we run such on validity we run 10 and 20 stock models so it’s so super concentrated that just from a rebalancing and like timing standpoint if like a model like the best performing

Model last year um was a value model based on Ken fiser super stocks book which goes Way Way Back to like whenever he wrote that in like the 90s or something like that Ken fer doesn’t even follow that but it’s like kind of the value a lot of cyclicals get in there

And um but then also at the top of the pack was some growth models which is what you might expect so it was a weird year in the sense that like it’s not like all the growth strategies or all the value strategies were like on top or

Leading the way it was was kind of a weird mix and then it’s a lot of times important to look at like what didn’t do well and So like um the green black magic formula model didn’t keep up with the market uh we run a strategy based on

And we’ve had him on the podcast he knows this pin vanite at Robo he runs like a low volatility conservative strategy that was actually like the worst performer um the surprising thing there is that’s kind of high on quality but you know something about lowall just didn’t work last year probably because

Of what happened at the end of the year was it a hard year it’s you know it’s kind of weird because we aren’t a great judge of like whether value is working or whether quality is working because of their 10 and 20 stock models there’s a lot of like idiosyncratic things with

Individual companies like the extreme version of that is like back in 2021 we had a couple models that had GameStop and so like whatever happened in those models doesn’t NE in that year doesn’t necessarily tell you a lot about the model itself because if you have 10

Stocks and one of them’s GameStop you know the whole thing is going to go crazy so we we can kind of see a little Randomness there in terms of yeah if value is doing well like on average our value models will do better but we also have like the liers in both different

Directions because they’re such they’re so focused and they’re so dependent on the individual names in there that’s one of the reasons that I like it though because that the sort of idiosyncratic application of it is so much more valuable than like the back tested you know theoretical application of

It yeah like we like the high octane version of these things um which is which is why we have them there um but you know and we we think you know if you’re going to have these these strategies with these criteria let’s find the stocks that meet them as

Closely as possible you know let’s not go to 200 names let’s really do it aggressively but it goes hand inand with the idea that you know you’re going to have these individual positions they’re going to have a huge impact and you know sometimes if one of them’s a really bad

Position it can have a big negative impact in a year or if it’s GameStop it can have a really positive impact but I always try to keep that in mind when I’m looking at any the performance in any given year knowing that it could be like

One or two stocks that were a huge part of it and the other thing that’s just worth mentioning is that when we initially develop this we wanted to make it so these models were like actually followable and implementable for your average investor I me most of the people

That use Validia not all we have some professionals but you know we get a lot of retail investors so you know if you’re trying to follow a systematic strategy or portfolio and and remember this is back way back in 03 and we haven’t like expanded the portfolio size but following like 20 or

More stocks can get even if you’re doing it systematically it can get kind of tough to do so we tried to make it so these strategies are pretty easy and straightforward to follow how often are you rebalancing all depends on the strategy so yeah Go goe Jack we we do it four different

Ways for every strategy because we we try to give people as much information as possible and not to say here’s the best thing or here’s the best you know this works better than this so we do all of them we test them all monthly quarterly annually and then we have one

We call tax efficient which is basically a monthly one where it’s trying to limit the turnover so it doesn’t have like the regular monthly ones have pretty high turnover so the the tax efficient is like a lower turnover monthly and we have the performance of all of them

Using each one of the rebalancing so anybody can look at any one of the strategies and say how did this one perform annually rebalance how did it perform quarterly rebalance and you know what you find is kind of what you would expect the the value stuff tends will

Tend to do better or at least the same with the less frequent rebalancing and the momentum and growth stuff tends to need need to be rebalance more often for it to work um which is kind of what you’d expect probably going in do you ever show uh the correlations between

Them so you could find two that are you know yes uncorrelated we actually have we actually have like a correlation we have a little tool on the site for that site yeah so I can choose the acquires multiple which is a strategy we know very heard of it never heard of that

Never heard of that guy um but and look at like you know very uncorrelated with the multiactor pin bite conservative stock strategy interestingly enough and the next one is the momentum model which is what you expect um given what we’re looking at there is the correlation of the excess returns because obviously if

We just looked at the correlation of the peer returns they end up being pretty Corr because beta so yeah we’re pulling out the excess returns and looking at the correlation of the excess returns with each other to try to get a better picture of like what’s actually not

Correlated with what yeah that’s very interesting let me just give a shout out to listeners ptia Israel first in the house Senator Domingo Dino in Townsville what’s happening early stuff here Chapel Hill lenberg Sweden uh Montenegro showed Oregon Toronto Milwaukee Val Paro Antigonish Nova Scotia Canada Bangalore Brandon Mississippi Durham Savin lner Finland

Christina Kosovo kville Scotland dead cat Gully New South Wales yeah me too somehow uh I’ve jumped over if you sorry Braun schwag Germany Stockholm Sweden Nashville Tennessee Las Vegas Toronto oh my God Sweden Hamburg J Germany what wil wilit Illinois with a VPN through Nan Netherlands back in oilfield what’s up

Edinburgh Patrick Holland in Hong Kong what’s up Patrick I went to school with Patrick I went to primary school with Patrick what’s happening Patrick good author check his name out what’s happening fellas we’re back this this is your life Ro um just before we came on so Jake

Sent through this crazy chart that shows The Price to Book value of the China stocks want me to yeah yeah you you expl explain it uh yeah so it was NASDAQ 100 Price to Book and has eclipsed China price to earnings ratios so these ratios I mean you and granted like the

Caveat of NASDAQ being very Tech heavy and GAP not doing a great job of capitalizing on the balance sheet uh you know code so therefore book values are are uh you know they’re they’re ECT a little bit when it comes to to tech companies but with that caveat in mind

Um yes the relative just absolute disconnect in um valuations between China and US tech has gotten so extreme that The Price to Book of one is now higher than the price to earnings of the other yeah that’s crazy so what did you get book at was like book for book for

China was like sorry book for the NASDAQ was about five times you don’t have book yeah book for Nasdaq is yeah it’s in the five plus range it’s probably six or seven and then the uh PE for China is down below that number well think I mean think

About this think about with you know your average US investor portfolio now how much Home Country bias is just there because I mean you know us has just clobbered everything over the last 15 years and it’s just crazy and at some point you know it might not be China but International diversification

Is going to be important and that’s kind of something that’s probably being lost a little bit or a lot in investors portfolios I saw profit margins in China right now are roughly 5% and us is more like 13 okay so you know there’s a little I mean obviously the the business

Quality is is quite different too but boy I mean almost three times the margin I mean how can that go on forever I don’t know that seems like a a difficult bet to make China said pretty good consumer discretionary which unlike the rest of the so us has got unusual in

That it’s got so many big consumer discretionary got like I mean I like lump in Google and Microsoft and Netflix and all those sort of the Fang fan mag mag s whatever we’re calling them these days whereas a lot of the other countries in the world don’t a lot of

The other countries in the world are sort of heavily mining in resources or basic material and fi financials whereas China actually has some of that stuff so I always thought they had a higher quality stock market than many of the other countries in the world not reflected in the in the

Margins though no and like return on assets are are fair amount lower than us return on Equity is lower um it’s still a pretty heavy relatively heavy IND of course you have their national champions like the 10 cents and alib Babas and pend Doo Duo but

But yeah it’s it’s not quite one of your guys was saying that the that there’s a big bation between the performance of the economy and the performance of the stock market in China yeah well that was I think it was economic who uh Jake who shared that on Twitter like I think the

Economy is up you know several fold over whatever it is 20 years or whatever it is and like the stock market’s up zero so you know the whole idea of like the economy is not the stock market you know if you want an example to prove that that’s the example that the economy’s

Going crazy and the stock market is literally return zero um you know that that’s a that’s a pretty amazing stat there’s that famous uh Triumph of the optimists that uh it comes out once a year they update all the data for the world and it’s a Dimson Eloy Dimson

Marsh ston something like that Marian dson Dimson that’s right and they they they had looked at they they made the comparison I put this in one of my books like 2004 I think it was in deep valy where they looked at the performance of China as a an economy and the

Performance of its stock market versus the performance of England as an economy and the performance of its stock market and even though England is sort of eclipsed in 1950 and sort of losing its Global dominance since 1950 the stock market had massively outperformed whereas China’s been growing phenomenally quickly through that whole

Period but the stock market performance has been nothing like even England stock market performance and the the the the reason is that you’re just overpaying for China and it’s clear when you look at the chart that Jake was talking about earlier in Chinese stock market in terms

Of a PE basis peaked in 2008 and it’s been compressing since 2008 which is a long time it’s like being a value investor multiples running against you for like 16 years something like that that can happen I mean that’s uh I mean Buffett’s pointed out that sort of

177e cycle in the US even of and that was like the 20th Cur yeah and before that though you had yeah 65 to to 82 where you you went nowhere um and on a real basis I think it was even worse but yeah there’s there’s lots of

There’s lots of doldrums to to sail through in this ocean it’s not always just up and to the right I guess what I don’t know about the Chinese market is you know how you know you think about us the US market and US invest and how you

Know much exposure we have to the stock market as investors here um and how that’s grown over the last like 25 years in terms of or even maybe since the 60s or 70s you know it used to be pension plans and then you know now most most of

The time people are investing in stocks to save for the retirement I don’t know in China how their consumers sort of embrace their yeah the penetration so it’s like you you could kind of see if that’s because you know you hear about the wages in China and how much I you

Know so it’s interesting and and you would think there’ be Global demand for their equities the shares in China but you know I think to some extent what happened in with Russia and Ukraine and and the sanctions there you know that could put that certainly puts some risk in terms

Of exposure to the Chinese market in the sense if something goes down with Taiwan or something like that so it could be that overhang as well that you know is kind of affecting things also as we’ve discussed in the context of Alibaba that you’re not entirely it’s not entirely

Clear what your ownership interest is it’s it’s through those vi those Vehicles which Jake knows a lot more about than I do but that you don’t have direct ownership you’ve got this like proxy ownership and it’s not clear what your rights are it’s hard to enforce them

Ultimately what do you guys think about like International investing in general has just been such a challenge like to talk to investors about because it’s been so bad for such a long time but you know the theory is is very strong you know it you’re more Diversified there’s

There’s probably no reason to believe that over like a really really long period of time the US should just beat the rest of the world how do you think about that like it’s it’s really hard like when when you’re talking to investors because the theory is really

Sound but the practice has been horrible for so long it’s kind of a challenge to think about like what do you do going forward like us only has been great it’s worked really well like people say why would I change it it’s been working but like the theory would tell you you

Probably should have the international too and in addition to that they would say all of the US companies have got this Global exposure but you get you don’t have to worry about the you don’t have to worry about that VI problem you don’t have to worry about foreign taxes you can invest

Domestically and get the foreign exposure because all of their revenues are increasingly from overseas that’s right and that’s Cory hofstein when he was on our podcast made that point like you’re you’re getting a lot of you are getting a lot of international exposure by owning us companies so you know you

You may not need like that additional International exposure I would say a few own Starbucks you’re making an implicit bet on the health of China or Nike is true or apple or any of those really Jack do you want to walk us through your data mining

Paper oh sure yeah we had a uh it was actually very interesting we had a couple researchers on our podcast that’s coming out this Thursday and so we have this idea like an investing like in Factor investing if if whether it’s value or whether it’s momentum that you

Know if a factor Works in testing and I want it to continue working go going forward I need some explanation as to why it works and so typically what researchers will come up with is these risk based and the behavioral explanation which is the risk Bas is pretty straightforward you know value

Stocks typically are riskier you’d expect you know they have problems with their businesses they’re cheap they’re riskier than the market I would want an excess return for that risk on the other side the behavioral side would be people overestimate the problems with value companies they beat down their stock

Prices that’s for people who are willing to buy those stocks if they’ve overestimated the problems that’s an opportunity so typically those are the two explanations for like any factor that we’ve used going historically to say here’s why they should persist in the future well we had some a couple

Researchers Andrew Chen from the Federal Reserve and Alejandra Lopez lero from the University of Florida on our podcast this week and the idea they came up with is they said all right let’s test this so let’s take all the factors that have a risk-based explanation let’s take the factors that have a behavioral

Explanation and then let’s do a third group and let’s just data mine the crap out of the accounting database so basically let’s just divide everything by everything let’s come up with the ratio that do the best and then let’s use those as on a stand load basis and

Then let’s take these three groups we’ll do it the same period F and French use so the testing period ends in like the early 90s and then let’s see out of sample from the early 90s forward how they work and the answer is there’s zero difference between the ones that have

The risk-based explanation the ones that have the behavioral explanation and the ones that were just purely minded um which is Will challenge a lot of the theory that a lot of us that are factor investors you know based what we do on if that ends up being true so for

Instance like I asked him on the podcast so like one of the examples I think was something like property plant and Equipment divided by cost of goods sold something like that something you would never divide in the real world but that had you know a similar return in Sample

And a similar return out of sample to something like momentum and so what they were saying is basically there’s really no reason you could say momentum is better than property plant and Equipment divided by cost of good sold um so it’s it’s a really interesting thing like

Just to say like and we were talking before we came on talking about like Robert Mercer um at Renaissance and you know they’ve said all along that like some of their factors that work best are the ones that have zero explanation or the ones that make no sense and it’s

Just an interesting thing to think about going forward we all rely on like these explanations as to why these factors work and if and if we test them and we we don’t have an explanation then we shouldn’t use them but what what if the ones that have no explanation perform

Just as well as the ones that do um you know I don’t I don’t know the answer to it I mean certainly academics that are smarter than me are testing this stuff but I thought it was an interesting paper and it’s an interesting conclusion yeah they’re almost like uh

You know they’re they’re almost polytheistic you know like let’s just worship all of the Gods uh you know whereas you know maybe Toby’s a little bit more monotheistic of worshiping the the value uh God yeah or like even you can even worship at like I have no idea why this

Is working which is like a which is a whole different change from like whether you’re a momentum guy or a growth guy or a value guy like usually have some basis for it like this is like I’m dividing numbers I have no reason to believe but dividing these numbers other than the

Fact that you know there’s a lot of evidence that accounting data does impact stock prices you know they did something else in the paper where they tested just mining tickers as opposed to accounting data and they found no results there like they they couldn’t get any good results out of just mining

Tickers so there is something about accounting data where it is Meaningful in terms of stock prices it’s just like the ratios we’re used to thinking about they were they weren’t thinking about like here’s what I should test because I think it works it was more like just

Throw it all together and whatever works you know that persists just as well as the ones we could explain I mean is it possible though in that in sort of a like you know monkeys typing Hamlet Way that there’s just simply not enough data there to actually make that kind of

Claim I mean I know they’re looking at pretty large data sets but if you’re going to just throw random numbers together like you can you can kind of like find things that will match over some period of time but I would imagine like you need a just a big ass data set

To actually feel good about betting on that going forward don’t you think yeah no I would think so I think there’s there’s definitely some Randomness to that but you could also the noise ele there’s like so much noise to filter that much noise out you just need a huge sample

Size yeah exactly um you know and also like there’s a behavioral argument for you know and they’re not saying that the factors that have explanations don’t work out of sample they’re just saying they work the same as the ones that don’t have explanation so it’s not really a challenge of like Factor

Investing doesn’t work it’s really a challenge of you know do we need these explanations you know for what we use Ian I don’t know the answer to it talk rationalization exactly you know but there’s arguments also like we asked them in the podcast like do you with the

Regular factors you know did people mine the data to come up with book to Market or and come up with the explanation after the fact or did they have the explanation first and then find book to Market and the data and like they said they really didn’t know like it depended

On who who did it and so you you could kind of argue the other factors did it as well so you know it’s not something have a strong opinion on yet but I just think it’s really interesting like I love The more I’ve been in the markets

The more I learn to like challenge you know what I’ve learned and to say like not to have like these hard and fast beliefs and say no matter what I believe you have to have an explanation for a factor you know I want to like be

Open-minded at this kind of stuff so I thought I was really interested from that perspective I’ll have to ask Jim O shanesy next time I see him what was he doing did he did he show up with the answers already and then try to back

Solve or was he uh was he following a more scientific approach I always thought it would be interesting to do like a uh like no one would ever buy it but if you did like a factor ETF like X the ones that actually make sense right

So you like did an ETF of just the ones that don’t make any sense and used it as like a diversifying complement to your your standard Factor exposure um it would be interesting I mean no one would ever invest in it but uh there’s so many I mean every atfs taken these days

That’s at least one that would be be I’m sure you could WP a narrative around it I’m sure you could say it’s like the uh we’re just looking for signals where like uh you know what’s the what’s the firm Medallion what’s what’s that from brief and Medallion s it’s called rch Renaissance

Oh rch so Renaissance they’re just open about the fact that they don’t have any there’s no explanation we’re just going to test everything but what you’d expect to find if you test tens of thousands of ratios through one data set and then you find all of the ones that worked in that

First data set then you test them again through a second data set there would be something that would survive just by pure chance there are going to be things that survive through both data sets I mean and then but the I think the more scary thing is what it says about

Momentum and probably value and other things too that you can’t even demonstrate that they are having survived two sets that even though there’s an explanation like they really they’re know better than the things that are cooked up by the computer and what was interesting too is they all out of

Sample they you know it’s widely known that like value out of samples had a lower premium than it did pre 1991 um these the ones that couldn’t be explain did as well not as much but you know I I could understand value going down you could say all right people became aware

Of it they started following it you know the premiums are less but like cost of goods sold divided by property plant and equipment like those also deteriorated um out of sample so you know I don’t really we tried to understand that and I don’t really completely understand yet why that

Happened that doesn’t make any sense at all wellow I heard uh I thought what the research show ja back to the tickers was uh things with Z definitely underperformed tickers yeah don’t don’t use Z you gota you gotta go Triple A that’s the get to the front

Of the phone book triple Z I’ve got a note here saying value but I can’t remember why I wrote down value just probably just came to my head often write that down on stuff were we talking value before we came on I don’t remember we might have been

I’m we always talk value so I’m sure we were uh when’s When’s Val going to turn around that’s that’s the question I ask all of my guests no motivated reasoning here I don’t you know it seemed to me like coming into this year it just seemed like the

Consensus was and maybe I’m wrong about this but it was like you know growth had a pretty good I mean a lot of things had a pretty good year last year if you include the fourth quarter which you got to include that so it ended up being

Decent for a lot of different strategies I mean growth certainly was the leader but then it it sort of seemed like the consensus coming into this year was you know small cap value catchup and you know anytime I kind of start hearing that too of anything too often

It seems like seems like trade yeah so I don’t know um and you know kind of with our experience in running these concentrated value strategies and we we’ve talked about this is you know it’s very episodic you get you know it’s the best performance comes off the times

When it’s sort of the scariest and when value’s been pounded and then you get that that massive return it’s not this like nice step up at least in our type of value strategies it’s not like this nice Step Up churning out you know smooth consistent return so yeah it’s

It’s not that smooth 12 versus lumpy 15 it’s more like zero and then 50 exactly yep yep absolutely I saw I saw a few articles over the last few weeks that say when small un value have a bad start to the year like this it tends to be not

An indication that the year’s going to be bad but the small and value will catch up over the course of the year and there’s not a lot of ends it was like eight or something like that but they said seven out of eight ends have been

The Year’s been very ended up being very strong for small and value that sounds like highly motivated reasoning to me oh my gosh my my my get my bearishness tends to suggest that when you have a a weak start to the year for small and

Value it’s going to be a weak Year all around but that’s not the case I’m I’m picturing you like it’s taped up to the wall there’s like strings running all over the place yeah I’ve given up the macro I’ve given up the macro fit this Mon’s resolution for Lent I mean you could

Kind of see if I mean when when rates were going higher you know stocks that were more dependent on financing in the small cap space you know you can make an argument that you know clearly they’re going to be affected by higher rates higher financing costs and so you know that

Kind of flows down through to profitability so on the back side of it you know lower rates um you know should be favorable for those companies that are more dependent on debt um and there’s a lot of that’s the thing with small caps as a group there’s just a lot of junky stuff

In there uh so and yet the high yield spread never went anywhere hardly I mean it’s even when it was like there was a lot of narrative about questioning yeah financing it was like that didn’t blow out right that’s the option adjusted high yield spread that data series that

The FED that that seems to be coincident with crashes it really doesn’t get going until you know you I I don’t know what information it provides like if you find that you’re in a big draw down then you go and check it it’s like it’s always blowing off yeah doesn’t really help you

It’s not predictive of anything didn’t Dan rasmas did some work around that and I thought it was like it it led things by a few months or something like that when it spiked I forget what it was but it was it was actually a good indicator

For Value you know uh when when you would see a spike in those in credit spreads he uses it as a trigger when it gets over a set I forget the number but when we get or% spread yeah yeah which is R rare like you can look through the

Data it doesn’t happen very often when it gets over that last time was 2020 right that’s probably right he he uses that as his definition of a crisis so it’s time then to get to get more invested it doesn’t get triggered very often though and but

You would know like you you could easily say you could also say 6% on the OAS it would be equivalent to whatever it is 10 or 20 just on the Spy being done what’s interesting I got I’m on this actually we’ve had him on the podcast um who’s

The guy the Schaefer cullin Jack the um the value investor guy that wrote the book I’m blanking out isn’t Jim cullin is that yeah Jim cullin I think he and I think I think the firm is Schaefer Colin anyways pretty decent sized value manager and so I’m on his distribution

List and they send out like a quarterly update and it was just interesting and he kind of writes like a like a letter it’s he’s you know talks about value investing sometimes but he was talking to an Institutional consultant who they actually like work with because they have some

Institutional business but that cons consultant was telling him that in the last I think in the last like three to five years like they’ve had very very little searches for Value so even institutions are who you would think would be having this like I was thinking

Like could you get like a a big rebalance like I think Black Rock recently rebalanced into some that Big ETF on the model portfolios they saw a huge inflow into their value ETS and so you would think institutions at the asset allocation level you know they’d be looking at their exposures and saying

Okay you know now we got to tilt more towards us value and that starts with asking Consultants to search the databases for Value managers well this consultant was telling this value manager that no consultant’s doing that so no one’s asking for you no no one’s knocking at your door buddy so it’s pretty

Crazy I I I definitely have seen something that there were major redemptions from value funds last year there were a lot of money taken out and I I had heard I’ve heard in other places that people were considering cutting their small and value exposure which I think they’re you know a little bit

Little bit of both I’ve actually got a question on the on the small do you guys have any theories on you know the continued kind of beatings that the size factor is taking sort of alongside value yeah not really um you know I’m not a big believer in the size factor in

General um you know I’ve kind of that’s that’s where a place where West Gray has helped me a lot like come come around in terms of like how I think through those things like I always used to be the guy that said like I was never a believer in

The size Factor but I would always be the guy that said well value works better in the small cap space yeah and I what I had wrong about that is that can actually be true but what I had wrong about it is why value doesn’t work better in the small cap space because

They’re small caps value works better in the small cap space because you can get more valness in the small cap space so if if I expand my portfolio to small caps I’m going to be able to get cheaper stocks so I’m actually getting more value more so than I’m just getting

Exposure to size and like coupling it with value so I’ve kind of come around over time to say like you know I I don’t really believe in using size really in any way you know I I try to use the other factors you know and and I think

Using like an all cap database where you get small cap in there gives you an opportunity to get more exposure typically to whatever Factor you’re looking at you know two Al that’s not necessarily true with quality two things that might be impacting that these are just theories I have no idea but you

Know and I think verdad has done some stuff that like the quality in the small cap space has deteriorated over time and so if that’s true then you would think the market you would those would trade at a discount versus maybe a little bit higher quality um that’s that’s one

Possible thing that could be sort of influencing that the other thing is I wonder if you know the number of companies correct me if I’m wrong here Jack I think the number of publicly traded stocks is it’s very low relative to where it’s come down a lot there there’s not

There’s not enough stocks to make the wheel cheer 5,000 there aren’t 5,000 stocks do you know how many there are it like I don’t it was is it closer is it way off 4,300 4600 something like that so Jack are you are you saying that

It’s it’s not the size it’s how you use it I think that is true what’s the what’s the aqr paper um it’s like size matters if you control your junk or whatever oh man that’s even better damn it Cliff that’s that’s the best research paper title of all time it has to be

I’ve never seen one better than that yeah stock Geeks got a good good sub ands Oxley and private Equity that’s what I think that’s what I I think there’s a big bation from Saban Oley when that came in because it increased the cost to be public by so

Much I heard back down though but like it it was at one point you know over a million dollars of kind of extra friction which could matter for a small company but that now it’s it’s probably maybe a fifth of that so I don’t know well the other thing too are the the

Good companies staying private longer where normally maybe they would have come public before you know early on in their life cycle and you get you probably still would have gotten some you know a lot of companies fail but you know the ones that survive go on to

Become mid and large caps and sort of dry as they migrate up the chain and now um you know they’re staying private longer and coming to the market maybe more mature I don’t know that’s another also like one of the things I’ve noticed is when we look at our investable

Universe like a lot of these a lot of the reduction in the number of public companies has come in companies you probably wouldn’t be investing in anyway because they’re very small and a liquid so like our our investable universe I think it’s like 2700 now that’s come

Down over time but it hasn’t come down nearly as much as like the overall Universe has because a lot of those companies were never in the investable universe anyway um they were kind of Fringe public companies that were you know we won’t invest in anything that’s not let say like below 150 million

Market cap and we need some liquidity as well like a lot of those companies that have gone away were outside of that you know those parameters one of the things I used to do when I was testing out of uh because I shly said I forget what the what his cuto was

But he used an absolute number cut off 25 million or something like that when I tested it um in 2008 or 2009 at the very bottom Russell 2000 the smallest company in the Russell 2000 was a $29 million market cap so you’re chopping off a lot

Of the Russell 2000 as you went through there so I I changed my definition to make it a percentile so you always have the same number in there but it was kind of interesting like you your Universe grows and shrinks if you use an which sort of makes Absolut makes sense but if

If you if you have that fixed number I don’t know man those Smalls are the smalls kill me a little bit because I I think that you can put together portfolios that are better quality and cheaper than in the bigger Market at the moment at least but they just seem to

Get they’re just punished regularly yeah know you you introduce the once you introduce the that serious tracking area you introduce and you know yeah you can you have to be willing to sit through it um but I agree with you I mean you you can find you know what you’re looking

For you can find it a lot more in the small cap space a lot of the time but you know you’ve just got to be willing to look different and you know for people like us who manage other people’s money they’ve got to be willing to look different too and that’s always been

That’s always been a balance like in our career is like how focused do we want to be and how much do we want to worry about tracking error and like trying to get those two right because you can’t run these things you know my biggest lesson like coming from like just

Testing these things to running them in the real world is you can’t just run the most aggressive high octane portfolio you want to in the real world and expect people to stick with it you know you have to have at least some standards in terms of like how much tracking era

You’re willing to take and how much tracking your people who followed are willing to take and you know that’s been a lesson and I’ll probably never get that balance right but it’s something I’ve gotten better at you know as we’ve done it over time to some extent you’re

Like Ken he had the CGM Focus fund which is famously one that it it returned something like 177% a year for for a decade he was manager the Morning Star manager of the decade in like 2011 or something like that but if you you look back a decade before the average cash on

Cash return on his funds was like 11% because people sold at the bottom and bought back at the top and it was yeah the actual return was like significantly positive right the funds were something like 17% compound but the average investor was negative 11% I mean you

Probably find the same thing in Arc like the the the money Flows In exponentially as the as the funds go up and part of that creates some of the performance too but equally it means that your cash on the Investor’s cash on cash returns are always negative because when you take a

Header you’ve got the bulk of your money has come in at the very top and it all get Fair home CGM Focus I mean a lot a lot of those same idea like they all had the same thing but it it kind of creates a conundrum as a manager because like

Have have those funds added value for people or not like on one hand the fund could argue well here’s my actual returns this is what I put up if you could if you stayed the course this is what you got on the other hand like do you acknowledge the fact that people are

Going to do what they do and you know I’m gonna have a 30% investor return less than my actual return like I got to change the strategy because this is not doing anyone good like it’s hard like that that’s the balance as a managers how do you think about those control is

It’s outside of your control yeah no it is be worried about it I think it depends on the structure too I mean if you’re you know if you’re managing an ETF where it’s somewhat easier come easier to go I think it’s harder to do if you’re if you’re running smas like

And you have more of a relationship with the investor I think you have a better chance of bringing everyone along with you uh to the Finish Line maybe fund even more so I don’t know um but you can’t throw up Gates like nobody nobody likes Gates and I don’t think you can

Justify the M but it probably does lead to bit of performance well it is interesting I you know it’s funny you’re bringing this up because for some reason I went to this I heard somewhere else I was like what is going on with those funds and they’re actually they they closed those those

Funds liquidated at the end of 2022 so they don’t even CGM Focus fund doesn’t even exist anymore I don’t know if the assets trans but I mean you go to the site and it’s like CGM Focus funds have closed and it’s like there’s a an unclaimed State Property link to like

Click on to like claim your for everybody who yeah for people that didn’t redeem their shares you can kind of if you’re listening you can still go and get your money or at least some of it yeah Charles asks is that a good argument for closed in funds despite

Those funds immediately trading at a discount I think you need some ability to buy back your own stock as a closed in fund which you know managers don’t want to do because it shrinks their assets but equally it gets rid of that discount and I think that’s one of the

Reasons why you know Buffett it’s one of the advantages that Buffett has that he’s got when the market goes down all anybody can do is sell Burk share they can’t pull money out of Burkshire and so burshire can trade at a discount which creates an opportunity for him to buy

Back stock which you know as long as the stock is bought back at a good time it tends to be that generates better performance in the future and to to Jake’s point like I think it is a a case that like running these Focus things in smas to some

Degree is good because you can talk to the end investor on a regular basis you can help them stay the course and the other thing is Eric balunis has talked about this a lot like I think you are seeing people use these things maybe a little bit better than they used to in

The past like they kind of have the core and satellite thing so they’ll have their core portfolio and they’ll take something like Arc and they’ll size it smaller and so when it’s size smaller relative to the rest of your portfolio you’re going to do a better job of

Sticking with it and you know one thing you can say for Arc is you know they have not they should have gotten a lot more redemptions than they did given how bad the performance was coming off the peak so they have gotten Buy in I think from their investors um you whether you

Like the strategy or not like they a lot of these other funds in the past that have had those kind of performance numbers have had much bigger redemptions than Arc did so they have gotten Buy in at least yeah that’s one of the I think that’s the most impressive thing about

Those funds is that even as they fell over they were still getting positive flows for a for a long time I don’t know if they’re still positive but I mean they now they had a good year last year had a great year last year hell of a marketing machine

What do you think is the most survivable factor for outside investors I think an idea I think it’s got to be something that’s procyclical right it’s got to be momentum when you’re doing really well money’s flooding in and you keep on doing really well and then you have a 2009 where

Everybody’s just running for cover and everything’s kind of bombed out so it doesn’t work for you then but it didn’t work for anybody anyway but then you go back into the a booming bull market and you you’re back into momentum land what are the one of the cool things about

Momentum that a lot of people don’t think is a lot of people might think like value is a more consistent Factor than momentum but that’s actually not true like if you look at the consistency of like fiveyear periods you know producing a positive premium like momentum is actually better than value

Um it’s it’s more consistent in terms of like not having the long long periods of struggle than value is so it’s good from that perspective but you know my my big takea away from value and momentum my career has always been excuse me sorry um they work really

Well together and like that’s it’s something where people tend to get in these camps and they tend to say you know well I’m a value guy so that I shouldn’t use momentum in any way or I’m a momentum guy like they they make when

When you do the look at the date on them they work really really well together and that doesn’t mean you have to use them 50/50 like I mean value people can use momentum for entry and exit there’s other ways you can use it I mean I think

They work really well together and I think they’re great compliments so I try not to pick any more between them is that long short or or as the just the long only versions of them just the long only like they work really well together um there a really good chart by Larry

Sedro you can kind of Google it to find it you got to dig it up I think it might be maybe on like uh he writes for a lot of different places so you kind of got to look around but it’s like Larry Sedro Factor uh uh Factor persistence maybe or

Something like that and it he’ll show like value momentum and then and then periods you know 1 three five 10 20 the percentage of underperformance in any given year and how when you combine the factors together you know those percent those periods of possible underperformance fall significantly um it’s a really

Powerful visual um that’s out there that Larry’s done work on so that’s pretty cool to see I think I just realized fellas we haven’t done Jake’s veggies better do some vegetables huh all right so yeah we wouldn’t want to miss out on this one either we’re talking about slime molds

So God forbid that we miss that um so this passage that we’re going to go is inspired by uh some work that Robert spolski has done in in this new book that he has just came out called determined and uh so like what is a slime mold to begin with it’s like you

Know billions and zillions of of these single cell amibas that join forces and to grow and spread like a carpet over a surface and they ooze around mindlessly in search of food only maybe they’re not so mindless um the individual cells are inner connected by these tubules that

Can stretch and contract depending on the direction and somehow this collection of meba Buzz without any apparent centralization has this problem solving capabilities that you just like wouldn’t believe uh and researchers have done some really amazing experiments around this so here here’s the setup imagine that you like Spritz a dollop of

Slime mold into this little plastic well and it leads down to two different corridors and one of the corridors has a single oat flake in it and the second Corridor has two oat Flakes and apparently slim molds love oat flakes for some reason um but similar to The

Hive like insect strategy of sending out Scouts that you know bees and ants use theime mold expands into both corridors and it reaches both of the food sources but within a few hours the slime mold reacts and it retracts from the single oat flake Corridor and it heads to the

One with two how does it know like how do all these things that you know they it’s not like they’re talking to each other well uh if and if also like you could stick the slime mold into two different Corridor Mazes of different lengths and it ends up finding the

Shorter route uh you could stick it into a maze with a bunch of dead ends and this brainless slime mold finds an optimal solution to its beloved Oak flake uh and this Japanese researcher did an interesting study he took he plopped a slime mold down into this strangly shaped like walled off area

With oat flakes at very specific locations around it and at first the mold expanded and formed tubules connecting all the different food sources to each other in a bunch of multiple ways it’s kind of a mess eventually though the tubes retract and it it it end up leaving close to the

Shortest path length connecting all the different food sources now here’s where it gets interesting the walls that this researcher put it in outlined the exact shape of the coastline around Tokyo and the slime molds were deposited where Tokyo would be on the map so the oat flakes corresponded to the Suburban

Train stations around Tokyo and out out of this slime mold emerged a pattern of tubu linkages that were statistically similar to the actual train line linking the stations uh that had been built so a slime mold without a single neuron in it had done the work of numerous urban

Planners um so I’m just impressed that the humans got to the same point that the slime molds did well I was gonna make the joke that uh you know I’m sure if we asked our friend Moses uh Kagan what he thought about La city planners he might say they also were operating

Without a single neuron but sorry stepped on I know uh all right so actually even this like there’s a in computer science there’s this kind of famous uh it’s called like the traveling salesman problem and it’s like an optimization thing uh and it it follows like if you’re given a list of cities

And the distances between each pair of the Cities what’s the shortest possible route to visit each City once and return back to the origin city um actually U Carl minger uh who’s the son of the favorite uh the famous Austrian Economist Carl minger um was one of the

First mathematicians to to make real progress on the the traveling salesman problem in like the 1930s um and anyway so how does the slide mold actually do it like let’s get into that a little bit it’s it’s actually a three-step process and it which mimics kind of the ants and

Bees strategies um there’s Scouts that go out right and that’s the slime mold kind of oozing all over and then there’s quality dependent broadcasting and then Rich get richer Recruitment and so let’s go back to like our first version of the two corridors where like one oat flake

Or two oat flakes uh the slime mold will initially ooze into both corridors and this is like the scouting phase and then when the food is found the tubules contract in the direction of the food pulling the rest of the Slime toward it and the better the food source the

Greater the contractile Force generated in the tubules and this is that quality dependent broadcasting that’s that’s effectively a form of communication um and the tubules uh the tubules that are a bit farther away dissipate the force by Contracting in the same direction and increasing the force of contraction and

Recruiting more behind them basically and eventually it pulls the whole slime M towards the optimal pathway uh well I’ll spare you from going into all the Gory details but it turns out that the way that our neocortex wires itself is a very similar strategy to the slime mold

Uh your neurons will send out Scouts to connect with other neurons and they’re climbing along these things called like radial glea and they’re there there’s reinforcing mechanisms to to attract other neurons to hook up where there’s better connections found um so basically like bees ant slime molds your brain

Wiring it all happens without a master plan uh or constituent really knowing anything beyond their their own immediate neighborhood uh so and then there’s there’s one more little like branching mechanism that I’d like to share that just because it’s so freaking wild to me all right in your

Circulatory system right each cell in your body is at most only a few cells away from a capillary right and that’s where the blood feeds the nutrients expels the waste moves things around right like it’s the transportation system well this the circulator system accomplishes this by growing around

48,000 miles of capillaries in your in the average adult so 48,000 miles worth of capillaries inside of you and yet that 48,000 miles only takes up about 3% of the volume of your body I mean is it science is freaking amazing isn’t it um or nature I guess is so anyway there’s

More than you wanted to know about slime molds I don’t have any real uh investment takeaways from that other than just uh the the emergence of of solving things perhaps using simple systems uh can lead into much more complex Behavior than you would ever imagine well I’m wondering if I need to

Replace myself a slime molds to like build our multiactor strategies maybe I could like align oats in such a way that it can select a factors or something I don’t know something something I got to look at you know maybe I was worried about AI maybe I should really be worried about slime

Molds the original AI I got some investing sort of thoughts from that I was thinking like you know I kind of got me like momentum investing like the initial Scouts are the early guys in these stocks and then they kind of send the signal to the market that

There’s an opportunity here and then you got the reinforcement of more investors coming in which drives momentum and then I don’t know I was trying to like kind of weave in like some some things there so yeah that’s farther than I made it that’s great I mean it’s great stuff

Though Jake it’s you should have been a teacher dude well you are a teacher but you could have been a teacher science teacher do you guys have any strategies that look at biotics or anything like that no it’s hard to look at those with factors you know I mean those are a lot

Of you know figuring out what’s happening with the the latest drug or whatever you know it’s not the kind of stuff that you know you can really do do a good job with with factors has there been different points of like I know that it’s happened where

There the basically like you could buy them for the cash on the balance sheet and therefore the pipeline was effectively free yeah that’s where I was going to go yeah but has there I don’t know if anybody’s ever really like done a full Quant treatment of that before

I’ve only just heard anecdotal like you know gosh the farm industry is bombed out you can get all these pipelines for free yeah I don’t know I haven’t seen that either you know the problem is they’re always you know they’re typically bleeding cash and so like it’s

It’s hard to look at the cash in the balance sheet because you can’t get access to it and they’re bleeding it and so you know by the time you know if if it doesn’t work out like there is no cash and so it’s like those those ones

That trade like at a discount it’s just yeah it’s that’s outside of my purview I’m like I’m not great at that Toby what what about the studies on net Nets though that are somewhat comparable with losing versus making money and the return differences what what do you know

About that yeah I’ve never I’ve never seen anything looking specifically at biotech but it you just if you believe that the cohort will you know sort of justify its existence which it seems to in the sense that they’ll earn enough returns to justif to to justify the investment

In it over time even if it’s not in any single one because you’re going to have some giant winners and you’re going to have many Los losers it seems that if you could get them at a discount to cash discount to what everybody else has invested in that should when that

Happens on occasion when you get a whole Coho like that’s what generated the question that we’re in a point of time now where there’s a all of them trading at a big discount to cash the the whole industry or the sector or whatever you call it is trading at a discount to cash

It’s like free lotto tickets yeah this is or mispriced lotto tickets perhaps mispriced yeah you know the way people can kind of figure that out on on Validia they can go we we have a screener so you can go like it’s not all of it’s free but you

Can Noodle around with it it’s under stock research and Guru stock screener and then you can add in healthcare and biotech and then see you know what companies are you know trading based on price to cash flow and a bunch of other different things that people want to

Play around with that you guys want to make any predictions for what you think this year is going to hold in terms of is it a momentum year is it a growth year is it a value year like what do you think no I don’t want to do that if I

Did it would be the exact opposite of what I said so I’ve I’ve stopped calling value bottoms a long time ago because I I think I’m fighting against Myself by doing it so uh so I guess from that perspective I should call it a huge growth Year and hope I’m wrong like I

Always am I made a what was it what was my S&P 500 uh prediction Jack was like 5,800 on the S&P oh yeah we did a uh we did like a joke episode of our podcast you know we we’re very much against these S&P 500 targets so we’re like the best way to

Prove that that is garbage is to like actually do it ourselves so like the three of us on our podcast like we both came up we all all three of us came up with targets for the year and predictions as to what would work and what wouldn’t work and so now we can

Just make fun of ourselves at the end of the year and show like that we’ve proven just like all the other guys that we have no idea how to do this if you take the average if that’s if that’s more accurate probably there’s a wisdom of crowds

Thing that does seem to work in that stuff canceling of errors and either direction although if you take that approach and go back to early 2023 you know the average strategist had the S&P flat for the year so you would have been very wrong that way and I guess we were

We were on the optimistic side Justin right relative to the strategies for this year like all three of us were actually pretty pretty bullish um in our in our targets I took like 250 on the I tried to you know do a methodology to it

At least I took like 250 in earnings on the S&P I assigned I don’t know like a 24 multiple which is a little bit high but it’s you know if you get if rates are declining and you know we’re sort of soft landing and growing you know maybe

That’s not unreasonable to think the multiple could be a little bit higher and then but and so I try to back into it that way but then the counter to that is like I look at like the performance of you know these large cap growth names

And really what drove the market and I’m thinking to myself like okay Microsoft and Apple are both three trillion dollar companies they’re going to be the ones to have to drive this thing higher like what are we looking at like four trillion by the end of 2020 I don’t know

You know it’s just like I just have a hard time extrapolating that the past like two years of performance on those very large companies and kind of bringing it Forward because you just start talking numbers that are just like kind of ridiculous it’s AI don’t worry about

It yeah exactly I’m still trying to figure out how to put co-pilot in my Microsoft Office Suite I can’t figure it out I think I I would have come up with that um paper that you were discussing earlier Jack where fs and PP and or whatever the whatever the ratio was it

Feels like that’s a very AI kind of outcome yeah you know I’m sure they I’m sure that was partially used in the in the creation of it um yeah it’s I think it’s really I think it’s really interesting because I just think like challenging you know whether it proves

Itself as as it gets tested further or not like just the idea of challenging like these core beliefs is something I think is really good to do occasionally even even if the the end result is you still have the core belief that you always had like I I think the that to me

Has always been helpful for me when I can ever I can take a step back and like challenge something that I that I really believe strongly yeah it see it seems it seems hard to see where the bigger companies go from this point but then when they

Hit a trillion I probably would have said the same thing so why not t TR do you guys have any thoughts it’s probably too much to the end to talk about this but like what you think AI means for like the overall stock market it’s it’s

Something I think about a lot right now but I don’t really have like we had Adam Butler in our podcast and he was talking about how like a lot of the impact really could be in like small companies you know 2 3 four 5 10 20% companies

Could really be the big beneficiary and you know obviously Nvidia or whatever is going to sell a bunch of chips but you know Microsoft has open AI but you know it’s unclear like how this will actually impact the stock market you know because there’s some people on Twitter calling

For you know like a bubble that’s greater than the do bubble here because they see AI as a bigger technology and they see the bubble it could create being bigger so I think about that a lot I don’t really have any conclusions but I think about aot that a lot these days

There was an interesting paper that came out of uh there’s a good account to follow this uh I think he’s a professor Ethan molik he does a lot of AI chat GPT kind of research and post findings on it and one of the things he posted was

About and I think it came out of Bane I believe I might be wrong one of the big consulting firms and what they did was they took consultants and got like a baseline measurement of productivity output quality of the work and then they gave half of the population chat GPT and

The other half not and then had them do their work and then looked at the results and like how much what was the output what was the quality and it turned out that um the high-end consultant like the the people who were on the highest on the on the Baseline

Didn’t really move their needle very much upward however the people on the bottom were actually lifted quite a bit higher from off of the lows so it might actually be providing it’s more of a floor than really like moving the ceiling up um which shoot from a income

Inequality uh you know kind of average productivity per worker type of uh lens of the world like that actually could be really encouraging like you know we have a lot of disparity right now in the US in um you know wealth and and wages and the US worker hasn’t really participated

As well as the US corporations have in growing the pie over the last well our lifetimes really but um but yeah if AI was somehow to boost their productivity in a way that made them closer to you know the the higher end uh that that could be really encouraging I don’t

Know well and I think also to to that point you know if you can get a boost in productivity and it helps add to the profitability of companies that are really engaging in this whether they’re able to do more with less they’re able to get more from their existing Workforce

You know and then you look at all the future cash flows and then bring them back to now how much is that worth I mean that’s worth probably trillions of dollars if it comes to fruition um I think it’s more likely to be everybody’s going to be standing on their tippy toes

Trying to see yeah I think it becomes table Stakes too you just like when when at one point if you had a dotom in name you that that was enough to like list on the stock market and then after a while it just became like a website Doom or

Just table Stakes but I’m talking about the I guess the underlying profitability of of firms and how it could but listen margins are high already historically so you know there’s a lot of people that think that they have to revert down it’s just you know there is a upside case

Here which is you know AI is a technology that sort of level sets or sets the bar higher I should say or makes makes companies more profitable potentially and then what is that what is the true value of that in today’s terms I don’t know it’s just an interesting thing to think about

Whenever I try to predict this I always think back to myself like in the late 90s and the internet and like what I would have thought would have happened with the internet and what actually happened with the internet and they’re so different than each other that I I

Pretty much realize like I have no clue like what this is going to mean I mean I’ve used this enough to think it’s going to be a huge impact on our society in a lot of different ways but what that is like I’m just not smart enough to

Figure it out and on that not it’s it’s uh it’s time if we if folks want to follow along with what doing or get in contact what’s the best way of doing that yeah check us out at val.com we also have the podcast excess returns you can hit Jack and I up on

Twitter I’m at JJ Carbono and Jack is practical Quant thanks Jin good seeing you boys thanks for having us great to be back than JT we’ll be back next week see bye