Bitcoin S2FX, S2F, and Evolution From Collectible to Financial Asset

Hello everyone, welcome to the show. This is the Stefan Livera podcast, a show about Bitcoin and Austrian economics. So today I've got some very, very special guests. I have Plan B and Saifedean joining me together for the one podcast episode, and we're gonna talk about stock to flow and stock to flow cross asset model as well. But first, I need to introduce the sponsors of the show, so just a moment.

Okay. So, firstly, the first sponsor is Kraken. They are one of the world's biggest Bitcoin exchanges, they're one of the longest standing, they have low fees, they are a well-known brand in the space, they bring Kraken Security Labs also, and so they're testing some of the security, not just of Kraken, but of other counterparts and other parties in the industry as well. So they're really well-known brand from a security perspective. They also have Kraken Pro mobile app, so it's a beautiful mobile-first design that gives you all the best of Kraken. So make sure you check out the Kraken Pro mobile- App and there's also Crypto Watch, so that's crypto w a t dot c h, and they've got a range of charting and terminals there, and you can also, funnily enough, there's a stock to flow indicator inspired by Plan B, so check them out. Next up is Unchained Capital, Bitcoin financial services. So if you need to think about ways to secure your Bitcoin going into the halving, if you're bullish, you wanna make sure your security is good, so look up unchained dash capital dot com, they've got these multi-signature two of three vaults. You can use Trezor or Ledger. It's a, it's an easy to use web interface. They've got all this incredible material on their website. They've got vaults here, if, if you need help getting started, you can even book in and get some help from the team, or if any of you are interested, just give me an email or a DM and I can put you in touch myself with Parker and with the guys at Unchained who'll help you set up. And so they offer this vaults product, and you hold

meaning you can put up some Bitcoin and get USD, as, as part of that loan. they've also got some incredible content in terms of, their blogs, and they've also got Caravan, which is an open-source multi-signature coordinator, so keep an eye out for that because there'll be some updates coming on that very soon. So if you wanna sign up with them, make sure you go and check them out, the website is unchained dash capital dot com. Next up is swanbitcoin dot com. So if you are in the US and you wanna find an easy way to buy Bitcoin and do it automated without having to manually buy Bitcoins, and you want the cheapest way to do that, you can't go past swanbitcoin. You can set up your any major US bank account and automatically buy with every, every week or Every month, and you can start as low as five dollars. And so the guys at Swan Bitcoin, you know, they're taking the perspective that, look, timing the market is hard, so just buy regularly, and that's the strategy. And so there's a, there's a really great team there as well, and you can see down here, they've got, some content here on the blog, they've got the Swan team, Corey Eklipsten, I've had him on the show, Jan Pritscher, the CTO, he also wrote Inventing Bitcoin.

And lastly, it's the cipher safe. So you've got to, you've got to secure your seed, right? So if you've got a hardware wallet, if you're holding your, your Bitcoin keys, you wanna make sure you've got them backed up. So this is what the cipher wheel looks like. It's in a, it comes in a wheel shape, and you put in the words of your seed. So that's what you can use to help protect it. And in, in there, you can also check out some of the other products that they've got, such as

The entropy as well, you can also buy a cold card packaged with it as well, so that's, an option for you as well. So the website for that is saifedean dot io, okay? So that is, the, the sponsorship material, so make sure you check them out. Now, in terms of introducing my guests, now Plan B, first appeared on the show in episode sixty seven. He is a pseudonymous Bitcoin quant and also an investor in his day job. So he offers, some really incredible analysis and really set, you know, set the Bitcoin world alight, as well as the finance, finance Twitter world as well. and so he's, he's rejoining us today, and my other guest is Saifedean, the author of the Bitcoin Standard. He's an economist, and he also, was actually the first guest on my show. And he is also running safedean dot com, which is his academy to teach how to, you know, learn about Austrian economics. So I'm just gonna bring in the guests now. So welcome, Plan B and Safedean. Thank you for having us, Stephan.

Thank you for having me on, Stephan.

Excellent. So, look, Plan B, let's start with you. You've done some awesome new work with the stock to flow cross asset model. Can you tell us a little bit about why you did this and what, what's going into that?

Yeah, sure. the, S2FX, model, i-it was an, an, a long-standing wish of me, to integrate the two formulas that I had, one formula for the time series, Bitcoin model, and one formula for the gold and silver, so the cross-asset model, into one formula. It, it was nagging that, that, that it was two formulas, so I always wanted to integrate that, and it's, it's funny that, Raoul Paul Paul, from Real Vision, he, he, he read my article, well, almost immediately after it, was published, and he wrote an article on, on Bitcoin himself, much earlier than that, I think it was two thousand and fifteen. But he recognized right away, he said, "Whoa, you, you, you not only solved this for, for Bitcoin, valuation, but also for gold and silver." And back then, I, I didn't really understand him. because, yeah, there, there were two separate models, and, and it, it is right now that, that I merge them into one that I understand what, what role really meant, back then. So, so that, that's one reason, and the other reason was, I wanted to introduce a new way of thinking, a new perspective on the, on the same data. So, I'm not using any new, new data, just the, the, the, the one from, from the earlier model. But it, it, the whole discussion went into one,

perspective, and that's the perspective of, of time series, co-integration, R-squared, the drunken dog, that, you, you know, that, that, that narrative, and, and it, it, it brought a lot of quants, into the space, right? There's, there's, there's hundreds of quants now, now working on this, and, and that's really cool. On the other hand, it's a very specialized, very technical way of looking at, at Bitcoin, and, and well, we'll talk about In a minute, but this, this new model offers another way of looking at the same data, looking at it in, in phases and, and clusters. So, yeah, I, I really like that, and the hope is that this will activate, next to the quants also, yeah, other brains. We need more, we need more brains in the space, brains like, military thinkers, geopolitical, strategic thinkers, We really need those. So, yeah, those are the two reasons.

Fantastic. And look, Saif, let's go to you. I wanna hear a little bit from you around this concept of, transitioning, right? So, you know, there are different conceptions of money. We have, say, the charterless view, right? The government, the king, the god sets the money. We have, let's say, the David Graeber view, which, you know, we might disagree with, that money started as debt. And then we have the M

Development or continuation of that story is the Nixabo shelling out story of it started as proto money, as medium of wealth transfer, not necessarily small val-- small value transfer. So can you give us some of your views on that and how, how a money can evolve through those stages?

yeah, I think it's, I, I, I think Plan B's work is absolutely fascinating in this regard. It's, put, putting a quantitative, number on, on this is, something that I, I, I would have thought, initially when I first heard about it, I was extremely skeptical, and I thought, you know, it's just a bunch of nerds trying to put numbers on economics, and we all know economics can't have constants because there are no constants in human action, but- It's, it, it's, I, I have to eat my words and, just look at it because, the numbers speak for themselves and, you know, the, the, the, The, the regressions happen to have extremely strong explanatory power, and I think it's, it's extremely, it, it would be extremely disingenuous to just dismiss this when we see all these, extremely high correlation factors, and when we can tell very clearly how the causality works, because we know that the stock to flow for Bitcoin was, was laid out before Bitcoin was operational, so we knew that this was going to be Bitcoin supply according to the plan, according to the, schedule. Back in two thousand and eight, this was, the information, and then the price since then has, basically tracked what the stock flow does with extreme precision. it might not seem very precise if you look at it over the last year that we've gone from, say, three to thirteen thousand and back and forth. That doesn't sound very precise, because, you know, you're tripling in value and still the model still holds, but when you look at it over the, The entire period of ten, twelve years, this is, you know, the, the move from three thousand to thirteen thousand is still, is still a tiny little move compared to where we were, which is zero point zero zero three dollars, and to where we're going, which according to Plan B is probably a hundred, Trillion market cap. So, yeah, it's, it's, it's astonishing to think of it this way, and this new stuff on, cross-assets is, is quite fascinating because, it suggests something that I had intuitively also thought about, but hadn't thought of quantitatively as well. And that is, the idea that, at any given stock to flow ratio, Bitcoin becomes a different, kind of good. And that's just fascinating. So some people would have, some people that ha-have said Bitcoin is a Veblen good, in that as the price of Bitcoin goes up, people want to buy more of it. And while I think that is correct that yes, as Bitcoin goes up, people want to buy more. I don't think it's accurate to call it a Veblen good because,

I think The definition of a weblin good is that it is, is that the quantity demanded increases as the price increases. But I think, you know, from the Austrian perspective, they don't like to think of anything as being a weblin good. Everything, works according to the law of demand. but what happens as the price of a good increases, is that,

is that the kind of good changes. So the common example is that for instance, people pay for a Gucci bag or for a Louis Vuitton bag, they pay because they're, they, they pay more when it's more expensive because they want it they want the status symbol, they want the, you know, you're not buying the bag because you need a ten thousand dollar bag, you're buying the bag because you want people to know that you can afford a ten thousand dollar bag. So if they discount it and if they put it on sale for five hundred dollars or for one hundred dollars, then that defeats the point, then people think that, okay, well, that's a nice bag, but you might have gotten it for a hundred. So the point is that as the price of the bag increases, then the bag is a different good, and this isn't, it, it might not be very easy to understand this in the case of the bag because Even, even at ten thousand, yes, there's, there are a lot of people who will want it as a, as a status good, although it's likely still to be a smaller demand than if the price was low. But in the case of Bitcoin, it's very clear because what you're looking for in a money is liquidity, and as the size of Bitcoin increases, the liquidity of Bitcoin, Increases as well, and so that becomes a far better money and a more liquid money. And so it seems that this is what this, equation is capturing, as the stock to flow increases, Bitcoin becomes a different kind of monetary good, and it's, and, and, you know, as the, liquidity increases, the demand for it increases, because if you had Bitcoin with a market, market cap of a million dollars There's very little demand for putting money in a global network that is totally worth a million dollars. So you've got a million dollars distributed all over the world that you can trade with. When it's a billion, that's a much bigger liquidity pool that you can trade with, so that you're more likely to put money into it. And at the trillion, it's going to be, an, an even, bigger liquid market, so it's, it's, it's still a more advanced, or, or it's a, it's, it's a good that is gonna like to attract more demand. So I find this extremely fascinating.

Yeah, I think so as well. And I guess to summarize, I guess it's sort of like tr-traditionally we would, when we talk about the law of diminishing returns, we're talking about the same good, and the more you get of it, the less you should want of it. But in this case, we're saying, we're distinguishing Bitcoin because we're saying it's actually one of those things where the bigger that network is, the more liquidity there is, the better it is as a money. So let's bring it back to you, Plan B. Let's talk about On the screen, and, do you wanna just talk, talk to us a little bit about phase transitions, Plan B?

Yeah, so, so the first, example is water and, and, Those who've known, who, who, who've had that at, at school know it, but, but water can exist in different phases. It can be, a liquid, or solid, like the, the ice in your, cocktail, it can be liquid It can be, gas and it can be ionized as well. So the-- it's all water, but it's, it's totally different things, totally different properties. And as a matter of fact, if we go to the second example of the US dollar, you also see that in finance, 'cause the US dollar, we always talk about US dollar. But those, the dollar hasn't been the same, with the same properties the last two hundred years. So first it was a very defined, quantity of silver and, and, and thus gold. So, so, the gold dollar phase, if you will. but that ended because gold, well, it's, it's, it's heavy, it's, it's clunky, and, and paper is much, much easier in portability terms and, divisibility terms. So, it changed to, to- A paper dollar, but, but that could always be, transferred to gold, so you could always get your gold with the, with the dollar, and it also, had that written on, on the note. So, so that's, that's okay. But then in, in nineteen seventy-one, Nixon, got the dollar of the, of gold, the gold standard was no more, no more, was gone. So, so the dollar was basically backed by nothing, and we, we, we, we call it dollar When it was gold, when it was, transfer- transferable in gold, and when it was backed by nothing. But if you do statistical analysis on it, it's almost impossible 'cause those are really different things, And then you, you can see it in Bitcoin, the, the third example as well, 'cause, Nick Carter and Hasu, they have this, this, narratives study, they, they already did it in two thousand eighteen, where the narrative of, of Bitcoin changes over time, and it looks very gradual, but I guess it's, it's, it's less gradual than it looks, but it, it goes from, from a proof of concept, thing, you know, a white paper that, that was actually, running on software and, and, and just, just looking, try, trying it out, proof of concept. And then it went into the, into the payments phase where, where, and, and it was a very distinct, transition there as well, 'cause, 'cause there was a period, I think it was April two thousand eleven, when, Bitcoin got, to the dollar parity, so it was worth, one Bitcoin was d-uh, worth one dollar, and that changed the narrative a little bit, people started thinking Of Bitcoin, not in, in, in terms of a white paper and some, some proof concept software, but in terms of a payment system that they can actually use it for paying small things like cup of coffee or, or micro payments was the talk of town at the time. and then it, it went really fast, so, so the price shot up and, and, even above two-- in, in two thousand and thirteen, above a thousand dollars, towards the price of an ounce of gold, which was twelve fifty at the time. So the whole narrative of digital gold, which was already, there from the beginning, right? The, the e-gold story that, that Saifedean, wrote, but it, it really catched on and, and, so the e-gold- Could be looked, looked upon as the next phase, and right now what we're seeing after, we, we crossed, one thousand for good and, And, and we have futures markets, professional futures markets, the CME in Chicago and New York, backed on the, on the ICE system that all the futures are, are on, we, we might be, talking, and, and you see that in the chart as well, about a financial asset. So in, in a way, Bitcoin, while we call it Bitcoin all the time, it, it, it, Transition from, from a concept, proof of concept into a financial asset, and that, that's very interesting, and that got me thinking about, a better narrative and, and also a better, mathematical model.

Okay, great. And so, we've got some of the, the concepts here that you spell out, so we have proof of concept moving into payments, into e-gold, into financial asset. And so on that, do- Do we have any evidence for these phases or do we just, we, we have to try to ascribe certain what we believe it is?

Yeah, I, I think the study that, Nick Carter did was, was, was not very quantitative, r-right? It was based on narratives and, and a bit subjective, if, if you will, but I, I recognize the, the faces as, as narratives that, that were in the news and, and in my head at the time. So, Yeah, I don't know if, if they're really there, and, and that's why I wanted to quantify it, 'cause that's, that's when you know, it either really faces like that, and that, that, that, yeah, that was a wish I had for a long time. So, I think that's, that's where it gets real for me as a quant.

Yeah, yeah. A-and Saifdeen, I think a-a good question for you at this stage would be around the, the concept of de-monetization, right? It's like, think-and I think recently you commented as well that, silver, is not coming back. Can you tell us wh-why is that?

Yeah, I think, you know, I've, I've made a name for myself in the Bitcoin circles as being the shitcoin hater, and, I'm now moving this to the analog space as well by, Going after silver bugs and continuously reminding them that what they're after, what, their beloved monetary metal, isn't a monetary metal. Silver, I think, is an industrial metal. It's like copper, it's like iron. There was a time in which iron was used as money, and then there was a time in which copper was used as money, but they were demonetized, iron first and then copper, and I think silver has followed. And, You know, if we look historically, we see that the price of silver to gold historically used to be much higher. Silver used to, be worth much more. So about, two hundred years ago, it was at around fourteen, fifteen to one, so fourteen ounces of silver for one ounce of gold. then the, the turning point, and before that, it was much, it was higher as well. But around 1870 is when silver really started to crash in terms of price. That's when, I think the turning point, is, Was the, Franco-Prussian War in 1870, when Germany asked for its indemnity in gold and then switched to the gold standard. So when Germany switched to the gold standard, that was, really the You know, the, the, the, pivotal moment, because before that, most countries, most countries used both, and some countries were on silver standard, some country were on a gold standard, so the world was largely bimetallic, but, you know, Britain, Switzerland, Holland, and, some of the main, economic powers were already on gold, and then when Germany switched as well, then that just, made it, that really, strengthened the network effects, and from then on, the price of silver has just been crashing because, You know, the, the, the, there was no more good reason to hold on to silver. of course, I should add that it's not just the Franco-Prussian War, it was more importantly the fact that, with the development of modern banking and banknotes and bills and checks and letters of credit and all these financial instruments, less and less of the transactions was, were taking place with physical gold or physical silver. And so therefore, you know, silver's raison d'être, which was that it was useful for doing small transactions disappeared. So then the interesting thing is that after that happens, we see that there is a, there is a change in the way in which silver, is, acting on the market, and that people no longer are using it primarily as a monetary metal, or a lot of people are using it as a monetary metal because they still think of it as a monetary metal, but it's- functioning extremely badly for them as a monetary metal, and the, the value of the silver holdings continues to decline in real terms, while the industrial uses of silver continue to expand in real terms because of the declining price of silver, or relatively declining price of silver. So we see that what ends up happening then is that, because people aren't using it as money anymore, more and more of the production is being put into industrial uses, and then when it gets put into industrial uses, we're talking about the stock declining, and so that effectively means that the stock to flow ratio will decline as well. So, you know, historically it used to be that the stock to flow ratio for silver was around twenty or thirty, but I think it's, it's probably more accurate to see it that it's somewhere around three or five these days. It's continued to decline because more and more of the stock keeps getting eaten into industrial, uses, and then the flow continues to increase every year because, You know, we get better at finding things, so the stock to flow continues to decline, and we see how it, silver has really gone through this phase transition, the opposite direction from Bitcoin, where it was being used as money, but now it's largely an industrial metal And we see the price of gold, the silver to gold ratio, in 1870, as I said, it was about fifteen, now it's around one hundred or one hundred and twenty, it just continues to go up And, you know, no matter how far, the price of silver crashes, we still find people who think of it as money and still think that, you know, if it crashes more, that just means it's going to rise more. But I don't see that happening because, Even if we were to convince people around the world to start buying silver, even if we had billions of people start putting their money into silver, that's not gonna work. The price is gonna go up, but silver miners are just gonna produce more, and they're gonna crash the price. And we've seen this happen with silver a couple of years ago, when there was, about ten years ago, when there was a big run up in the price and it reached forty or fifty dollars, but then came crashing back down again. We saw it in nineteen eighty as well. You can raise the price of

But because it has a low stock to flow ratio, it's always going to, be brought crashing down again.

Yeah, yeah, and I think that's, fundamentally the lesson that we have to learn from that. so Plan B, perhaps you should, let's get you to take us through the rest of the model, so if you could just take us through the clusters and some of your thinking around that and, what the eventual predictions of the model are

Yes. so, so if we're, thinking in, in, in phase transitions and in phases, and we look at the data, the chart you, you show now, you know, it's, it's just the stock to flow index on the x-axis and the market value of Bitcoin on the y-axis. It's, it's, about, Ten years of monthly data points or a little over a hundred, data points. But if you just look at it, no models, no statistics, nothing, just look at the data. You see clusters. You see, well, top right big cluster we're in right now, you see in the middle around, stock to flow ten, you see a big cluster with some dots before that, and, And, and b-b-between one and three, you see, well, you could, yeah, is arg-arguably, you could say that's one cluster, or you could say it's, it's two clusters. I always had this, this feeling in all the statistics I did on the model that we- Of course, we didn't have a formal halving before 2012, but it sure felt and looked like a halving that we had there, and, and that's the 2011, jump in price, that we see there. so I tend to look at it as two, clusters, but well, that, that's arbitrary. Point is, you can see clusters there, so, that could underline this, this phase, story. And, yeah, well, the next logical step then is to quantify the clusters. So, I added a- it's, it's a, a ge-genetic algorithm, but it's unimportant, you can do it with a lot of algorithms, the cluster algorithms. Those are looking for the centers of the clusters. So you just input, I'm looking for two or three or four clusters. You also have, algorithms that find the clusters for you, but I just inputted four, and then it looks It, it looks for the absolute centroid of the cluster, so there where the, the most dots are. It's not an average, it's a median. It's, it's there where the, where the, the clusters are dense. So in time series, terms, if you, if, if you think ab-- about the last four years, the price has been hovering around seven, seven thousand for, for four years basically, So, yeah, well, there you have it. The colored dots are, are the exact four cluster, clusters that the algorithm finds. And, yeah, it's, it's maybe, maybe if you go up a little bit, so the clusters go, they are around stock to flow one point three. Say one. about, about three, ten, and twenty-five. Stock to flow one, three, ten, and twenty-five, and the market values that are associated with it are also from a, a different order of magnitude. So the first cluster, the total Bitcoin market was one million dollars, so really, really small, and everybody could, could buy up the whole market if you wanted. And the second cluster is, fifty-eight million, third cluster is five point six billion, totally different league, and the, cluster we're in right now, of course, it's a hundred and plus, so a hundred and fourteen billion, hundred plus billion dollars, which is small, but not, not very small too. It's, it's like a, like a, a large cup, cap at the S&P five hundred, right? The big bang, like, I don't know, Merrill Lynch or something. So, those are the, the clusters, and I think it's a better way of looking at this data than looking at the time series, 'cause if we go up a little bit, to the chart again,

yeah.

Sorry about that. It's, how I see it is, this is monthly data, but you could look at, and others did that, at weekly data or, or daily data even, but it would all only make the dot, the, the blobs, the blue blob, data blobs thicker. It wouldn't move the center of the data blob, it wouldn't move the cluster or the phase, so I thought, well, the phase, the center of those data blobs, that's the real signal we should be focusing on, and not all the noise that we add when we add More data. So, so yeah, g-going from those four clusters, you can see it, v- visually w-with your eye, they, they lie on a straight line. So, so the next step was to bring in gold and silver in the next chart.

Yep.

Which was, the step to make it a, a real cross asset model, if you will. And then, well, so, so, so, and then you have six data points, so the four, Bitcoin data points, but I, I view those four points as not, as different kinds of, of, of Bitcoin, right? Bitcoin in different, in four different phases, so actually four different assets. And then I add silver and gold, and, I fit a line, re- just an ordinary least square regression line, through it, and, well, the R squared is amazing, it's, it's ninety nine point seven percent. very high. yeah, sure. So, so, so now we have it, one formula with, with multiple assets in it. and of course, I know, right? It, it's only six data points. I'd like to add diamonds and real estate and, and all the other, well assets with a stock to flow higher than one, because below one, yeah, that, that wouldn't help much, oil, copper, et cetera. but there, there isn't much, there, there, there aren't much, assets or, or, or metals, if you will, that are, really scare, really scarce. So, yeah, basically this is it, this is the model.

Fantastic. And so, can you give us some insight around, timing then? So, because now time has actually been removed from this model, it's purely looking just at stock to flow. So I guess, do you have any thoughts around that, around whether that might mean,

like, say, the cycle, people are used to thinking of Bitcoin as, oh, four-year cycles and so on. Do you still-- Does this graph and does this model essentially still convey that concept of a four-year cycle, or do you think that actually changes now?

Well, there is a link, it, you know, s-statistically the time is out, right? There's, there's no time in the model, no time in the formula. Yeah. So we can't do, we're n- we're not doing time series analysis here. We can't do co-integration stuff, we can't do, well a-auto regression stuff or, or moving average stuff. It's a, cross-asset model. It's a, yeah It, it's a model that, that is totally different from the time series world,

yeah, so I think that's, that's, that's the important part, and I, I think that's how we should look at it.

Yeah, yeah. And, I guess we should just kind of put the high, the headline kind of pr- projection as well. So as you're saying, the estimated, next, you know, market value is, here, the two hundred and eighty-eight thousand, given nineteen million bitcoins across the years twenty twenty to twenty-four, twenty twenty-four, which is that, era or epoch, if you will, reward epoch. so I suppose the other question then is, i-it, do you have a conception here of whether the model, this model breaks down at some point, as you've mentioned previously, the stock to flow model potentially would break down in the late twenty twenties? Do you have any similar idea with this one?

Yeah, yeah. Let, let me say, three things. So the, the numbers that you're seeing right now, the five point five trillion and the two, two eight eight K, those are really big numbers, right? They're, five times the earlier numbers and they're, they're hard to believe, i-in today's world. and we should, we should look upon them as a order of magnitude prediction, so a forecast. It's, The whole model is, is order of magnitude basically, and that's what I'm interested in. It's, it's not like, you know, you see the tweets that, today the, the, the stock to flow model value is o-is almost the same as the actual Bitcoin price, and to me that's, that's actually pure coincidence, and it's, it's not what the model is about. It's, it's nice, but, the model is about orders of magnitude. So how would a- Stock to flow fifty-six asset be valued order of magnitude, wise, and, and that's what we're seeing here. So, so that's one. The second thing is that, and that's, that relates to your, your, your earlier question as well. W- of course, we know that the stock to flow of Bitcoin will only go up. It's, through the halvings, it will go up to, to, to fifty, a hundred, two hundred, et cetera, et cetera. so we can associate it with the time, frame that it, it, so, so, so the next timeframe, with the stock to flow fifty-six, that will be twenty twenty, that will be, I think it's next week the halving, in May twelfth. to, twenty twenty-four. So yeah, you, you could relate the assets, although it's not a time series model, to the time epoch that this asset i-is in, like, well, gold, if you will. and that's, that's by the way, a very interesting, topic of further research, and Saif and I already looked upon that, but data is very fuzzy and, and, and it's, it's, it's difficult, takes time. how is, how is gold and silver historically going through this? stock to flow, value line, and especially the things that Saif said about silver losing stock, so you know, going down in the line, those are very, very interesting things, of course. yeah.

Sure. A-and, the other question that, might come up is something like lost coins, right? How many coins have been lost? Do we estimate that? Do we account for that in the model, or do we just- Say, "Oh, look, those coins exist in somewhere."

I, I guess at first you might think, "Okay, they're not part of the available supply, they're not on the exchanges, so no one can sell them." but, Saifedean, did you have any thoughts around that? And also the concept around, Satoshi's schedule, if you wanted to expand on that as well.

Yeah, I mean, I think the, the, the, the lost coins is, i-is interesting philosophically maybe, and, and, and the- In, in a, in, in, in a police investigation kind of way of trying to find out what has happened, but, mathematically and statistically including them or, excluding them from the analysis doesn't seem to make much of a difference, so it's, it's a pretty moot point. But, yeah, on Satoshi's schedule, this is something else that I, that I found really interesting, which is I, I asked Plan B if he would run the regression using the, stock to flow variable, as if the schedule of Bitcoin had been, as if the block generation for Bitcoin had happened exactly every ten minutes, as, As per the schedule put in by Satoshi. So the way that it worked, the way that Satoshi put in the schedule for Bitcoin supply, as we know, is every ten minutes a new block, and for the first two hundred ten thousand blocks, it's fifty, bitcoins per block And then for the next two hundred and ten thousand, it's twenty five, and it keeps dropping by half. So I thought it's, you know, the, the, the interesting thing would be to use that schedule, which is very similar to the, actual stock to flow with the variation in time, it'll change only slightly, but I thought it would be interesting to use this. And to see the correlation with it, because, statistically, this is clearly without a shadow of a doubt an exogenous variable, as they say in statistics, and I think this is extremely important. we can, we can, we, we can get lost and spend a lot of time talking about the, you know, the, the mathematical specification and doing all kinds of tests, for the way that this relationship is set up, but there really is ultimately no replacement for thinking about things and just, you know, having a solid, Theoretical reasoning and understanding for why things work. And in statistics, you know, the, the, the problem of reverse causality and the problem of correlation versus causation is always one that is, Present. And it's something that is, that, that can never really be resolved mathematically. I think this is something that, good statisticians will admit, which is we can use all of these tests, we can look at all kinds of different statistical indicators to try and establish a relationship, but we'll never be able to mathematically determine and establish causality. You can't do that. Y-um, I mean, you can't establish it and prove it. I think my, my favorite example, is, From, if, if, if you imagine, if you buy a puppy and there's a construction site next to your house, and then you did a graph that plots the growth, in the size of the building next to you and the size of the puppy, you're going to find a very strong correlation. you know, the two of them will grow for about a year or two in size, and then they'll stop growing once they reach their full adult size, or the building reaches its full size. And so you could plot the two, and you'll find a very Very strong correlation. There's absolutely nothing that you can do mathematically that will tell you whether it was the puppy that caused the building to grow, or if it was the building that caused the puppy to grow, or if it was just random coincidence that the two of them happen to grow very similar to one another, at similar rates. This isn't something that can ever be established mathematically. you just need to use your brains and think. And, this isn't a very popular thing amongst economists these days, but among the Austrians, you know, we're not afraid of thinking and we're not embarrassed to admit that you have to use your brain. There's no other way of figuring out, how the relationship between Puppies and buildings works. If you've used your brain and you've lived on Earth long enough, you know that there can be no correlation and there can be no relationship. It's, it's purely a correlation and it's a function of the fact that puppies grow and buildings go up and, there are- Billions of animals growing at all times and thousands of buildings being built at all time, and there won't have to be a coincidence. So you have to think about things, And, and think about the foundational, premises of for these analyses. And in the case of stock to flow, what I found really compelling about this example of the regression that I asked Plan B to run is that we know that the schedule of Bitcoin, as it is presented in this equation, as the, as the, independent variable, we know it is without a question an independent variable. We know it is exogenous to the model. In other words, we know that it is not The price that is driving the stock to flow, that there is absolutely no, feedback mechanism from the price to the stock to flow, because the stock to flow, according to the specification, is something that was laid out in two thousand eight. In two thousand eight, people already knew this was going to be the stock to flow, and so the data for the independent variable in this equation was all available in two thousand eight. We know that the stock to flow today is, say, going, it's, it's going to be fifty. If you'd run this equation in two thousand and eight, you would have gotten a stock-to-flow of fifty today, or next week, because of the, Because this is what the schedule looked like. So for me to get this, indicator, which is clearly exogenous, it's clearly independent of the price. And have the numbers laid out as they were back in 2008, and then let the price, and then cor- try and correlate that with the price which happened, started to exist in 2010, so we've only had ten years of price now. There's absolutely no way that you can argue that it is the price that shaped the stock to flow. There's definitely no reverse causality. The stock to flow was there first And it's very clear that the stock to flow will have a link with the price. You can't deny that there is a connection between the supply and the price. It's, it's impossible to argue that, you know, if today the supply of Bitcoin instead of increasing at a rate of four percent per year, if it was increasing at forty percent per year And all, you know, all these, let's say five million new coins were being added to the supply this year, it's impossible to say that that would be immaterial to the price. We can't go from four percent to forty percent supply growth and think that there's no impact. So there's definitely a connection, and there's definitely, we know definitely the direction of causality is from the stock to flow to the price. And yet when we run that regression, we get an even higher R squared than you do with the The, actual, stop the flow, so it's about ninety-six point four or point nine six four for the R squared, which is absolutely mind-blowing. I mean, I think, people can get lost in, the, mathematical, details and miss the absolutely astonishing fact that we've got an exogenous variable, a clearly exogenous variable that is clearly independent of any, reverse causality. And we're predicting something that involves human action, that involves humans, acting and buying and selling over a market that spans the entire world and includes millions of people and is worth now more than a hundred billion dollars, and we are able to get this much, precision and, and, and, and this much accuracy in the, in, in the model's ability to forecast. It's, it's absolutely mind-blowing. I've never seen anything like this. And I think, you know, the, the, the, the, the punchline that people continue to miss is that, look at regression analysis, you will never find these kinds of numbers of an R squared that is this high For anything that is related to human action, for anything in which human beings are acting. So if, if you got a machine that shoots, say, that, that shoots balls, or if you got a gun that, shoots bullets, and you did a very precise scientific, Mechanical calculation of the weight and the speed and the energy, and you predicted how far the bullet would go, and then you carried out that experiment over ten years of shooting a bullet every day, depending on, the parameters, y- and then you plotted the, The actual distances in which the bullet traveled versus the predicted dis-distances, you'd get something similar to the R squared that we get with this model It's absolutely unheard of. I've never heard anybody mention it, and I've asked, and I, I, but, I've found nobody. It's absolutely impossible to imagine something like this for something that involves human action, for something that involves human beings acting on things. And generally, when we're building models of things that involve humans acting in them, we will have three, four different factors, or many more factors, we'll have, Interaction variables where it's, a function of the two variables together, you multiply them together or something or the other, and include all these variables and you still get an R squared of point five, point six, point seven if you're lucky, and then that's really, pushing it wh-when it comes to things that, involve humans, because human action is, is unpredictable, there are no constants to it, and human beings aren't, simple, machines where we can just predict what they do. And yet we see with this, stock to flow with only one variable, and it is clearly exogenous, we get an R squared of around Practically one. It's, it's absolutely mind-blowing.

Right. And the typical, right, if we're thinking from an Austrian perspective, we're thinking, well, hold on, economic law, we must understand that praxeologically, you know, we can't divine that merely from statistical, examination of prior existing relations, because those relations may not hold into the future. And that's kind of the fundamental way to think about that. I'm wondering Plan B, if you have any thoughts to add on this idea of the Satoshi's schedule R squared?

Yeah, it-it was a fun experiment that, that, that, Saif asked me to do, 'cause I, I-- In the beginning, I didn't understand what he, he wanted to do, and I did it wrong also, the first two times, but, Yeah, i-i-in the end, the original, release schedule, the, the stock to flow schedule was, was, was known in two thousand eight, and, and, projecting that to the, the prices is absolutely, a very interesting idea, and I totally agree with the, the no-- the notion that, that a model should be used to guide your thinking. It shouldn't be, you shouldn't be, be get, be married to the model and, and, and, and, and it's quants like me can get married to models very, very fast. So, so, and so that's actually the second reason, right, that I mentioned why I wanted to, publish the, the, cross-asset model, 'cause I think it, it- gives a, a far better way of, of thinking about and discussing about Bitcoin and its valuation and, and, going forward than the very strict, time series way that, that we've been talking about it before. So yeah, it's, it's, a-and the quote in my article also refers to that. So that was a quote of, Of William Lawrence Bragg, he's the guy who, who got the Nobel Prize for X-rays and stuff. So he says the important thing in science isn't so much to obtain new facts, as to dis-discover new ways of thinking about it. so I, yeah, I couldn't agree more with, with Bragg and Saifedean here.

Excellent. another interesting question I think is around inflation adjustment of the US dollar value of Bitcoin, right? So people like to predict out, okay, I think it might be however many hundred thousand dollars, in today's terms or in the terms of that day, so nominal as at twenty twenty-four. So do you have any thoughts on that idea, whether these models should try to account for inflation or whether they should just literally be a nominal value model? Plan B perhaps. So

yeah,

it's an interesting question, and I, I think it's especially if you go look, historically to the data. So if, if we go back like, like, like we were planning to do, a hundred or, or four hundred years back in time with gold, I, I do have four, four hundred years of gold data, supply, stock, stock to flow, et cetera. But if you then relate it to price, of course You have to, cor- you have to adjust for inflation, 'cause, 'cause, yeah, well, the dollar, but you run into all kinds of problems doing that. So, Yeah, you know, the, the analysis that I do on ten years of Bitcoin data, I ignore inflation, so I just plug in the, the data that you saw in the, in the cluster charts, and those are data straight from the exchanges, no inflation adjustment. I think we're fine with the ten years, of course, the dollar declined a little bit in value, in, in purchasing power, but, I think we're fine. And especially with the cross asset model, of course, you're, you're looking at, yeah, well, one, time, Time isn't a part of the model, so, so it doesn't matter. still, it, it would be very interesting to, to look at the historical path of gold or silver because it goes back, like Saifedean explained, it, it loses stock. on, on, on that, model line. So, yeah, no, I think, I think it's interesting, but also in the future, you know, if you, if you're going to predict, forecast, Bitcoin or whatever price in the future, which we're doing right now, right, with the two hundred and eighty-eight K, If we're gonna predict into the future, it's, it's also important to not to predict too far into the future, 'cause if we're gonna, you know, the, the, the well-known argument against the model is it goes to infinity, stock to flow goes to infinity, and the value goes to infinity, and well, you know, that's why the model isn't valid. That, that, that's a silly argument, if I may say so, because, y-you wouldn't never use that argument in, in weather forecasting, for example. If, if, we can, we can forecast the weather one day, for tomorrow, the day after tomorrow, maybe the day after, but, but forecasting one month or one year out, it's absolute nonsense, and I think that's true for a lot of models, also my model. So, yeah, I would be very it would be very interesting to see next, phase, the, the, stock to flow, fifty-six phase, and maybe the halving after that, the phase after that, and if we're very, very lucky, the halving after that. But to argue that when, stock to flow goes to infinity, which is in twenty-one forty, right? It's, it's, it's a hundred years from now. So, yeah, to argue that the model is still valued then I, I, I don't think that's true. And even if it were true, we had to, adjust for inflation. And, a-and of course, it measures market value in dollars right now, the model. So on the y-axis, it's dollars. and I- Really think, and that's why I think the phase metaphor, if you will, is, is helpful as well. I really think that if we go to phase, the next phase, the fifth phase, or the sixth phase, this is the phase after that, the dollar will be severely impacted, if not, killed in action.

Yeah, I think this is, I've heard you say this before, and I'm not entirely sure I agree with it. I think, the model, doesn't have to break down. In fact, it's built so that it doesn't break down, because if you're measuring it in dollar terms, you know, even before twenty-one forty, when the Bitcoin stock flow is at, say, four hundred or eight hundred, then, that's almost, that's almost as high as being practically like infinity. And, this could, you know, the, I don't think you can just say that the model breaks down because, it could just continue to fit the model as, the price of, as the market cap of Bitcoin goes up to infinity in US dollar terms. you know, we may not hit infinity at exactly the time that the stock to flow hits infinity, but, even if it happens, A hundred years earlier, twenty forty, twenty years from now, it's still going to be similar to infinity, and, and, and, you know, if we have a dollar breakdown, then, that's, that's your model, so don't write it off just yet.

Yeah, yeah, I agree, I agree. I, I agree. I, I think the, the model will not breakdown, the dollar will breakdown, and, in fact, that's the certainty, because all fiat-- Well, no, all, all fiat currencies, all four hundred of them

That survive and, and especially reserve currencies, right? They're, they're lasting hundred years and, and, but there's none that, that lasted for two hundred years. So it, it will come to an end, the dollar. It's not a, thing that's, that's even, yeah, debated much, but, yeah. So, so I agree. I think the, the, the, the model will outlif- outlive the dollar.

That's, I think that's a great quotable moment. The model will outlive the dollar. and look, while we're speaking about models, it might be nice to compare now to some other models historically. Now, there has been some chatter and some debate on Twitter, so, let me just, open the screen share. So here you can see just one example. So Eric Wall, I know, Plan B, you and Eric Wall have sort of gone back and forward, and also, Nick Emblow, has also gone back Chart model, right? And so there's a little bit of, you know, a bit of playful banter back and forward, and essentially Eric is trying to say, "No, you know, maybe the, the, the, it's, it's too, you know, it's just, it's, maybe it's setting the wrong expectation. And let's just, let's just go back to the old rainbow chart. So, do you have any thoughts on that plan B?"

Well, first of all, if we, fight on Twitter like this, you have to know, and I do that sometimes with, with, with people, you have to know that we have, DM contact most of the time. So it's, it's really trolling and, and, all in good faith, and I like that, that's, that's part of, crypto Twitter, so, all good. but of course, I'm, I'm more interested in the more serious debate, that I have, having You know, with, Nick and Marcel and, all the German guys, So, so, yeah, I, I don't know, they, I could, we could go through that, that tweet storm a-about the rainbow chart, but I, I would, I would kill each and every one. I, I think they're all, very funny, but, but not, not helpful in the debate. Not serious, yeah. Yeah, and, and if I may, Yeah, show one thing, I mean, do you have that chart, the two thousand fourteen

one? Yeah, the two thousand fourteen one, yeah, I'll pull that one up. Yeah, one sec, there you go.

That's the one, 'cause the, the whole rainbow chart, it, I love it, it's, it's, you know, everybody loves rainbows, but it's based on a two thousand fourteen Power law model, it's a time model, so instead, it's the same model, a stock to flow, but instead of stock to flow, it has time, the number of days since January two thousand nine. And it's a model from Trololo, huh, he was a guy on Reddit, I think, and he, made this model. Oh, yeah, yeah, you're, you're right. so, and it's a two thousand fourteen model, just after the big all time high, in two thousand thirteen. So you see the, the, the first part of the line, the, the, the somewhat thicker, brighter line, that's the original model, and you see the red line that's fitted through it. It's, it fits really, really It started to, deviate in the, in the future, right? because I think it, it was Tui de Maisto who plotted the, the, the more recent green, dots in there, the more recent Bitcoin prices, and it shows that the model, the red line, the, the original Trololo Rainbow line, if you will, is far too high, over, overestimates the prices and has to be adjusted downward. So if you look at all the Rainbow charts, and in fact, all the time, time model charts that are out there They have a, log, log, line, so the red line that is much lower than this two thousand and fourteen line, and that's why I, well, that's why I find time series model less, useful than the stock to flow model. and less useful, I mean, I don't use it, it, I think it's rubbish.

Yeah, yeah. Yeah, I, I tend to, I, I tend to agree. I think there's a lot of criticism of the stock to flow model, but a lot of people don't seem to understand that their objections are actually, just arguments for why this is even more amazing. So when you come up with an explanation, for instance, people will say, "Well, well, this is only measuring the price according to demand, but that's ridiculous," according to supply, but that's ridiculous because supply and demand should be there. Well, the answer is, okay, well then go make a model with supply and demand and put in other factors and show us that you can get a higher explanatory power. That's, that's really the, you know, you, you can come up with, with, with theoretical objections to why the model shouldn't work But you can't come up with a better performing model, and that's the tricky part. So it's, it, it, it, it sounds shocking that, yes, we're just calculating it based on supply. It sounds shocking that, yeah, doesn't take into account inflation, doesn't take into account all kinds of different things, and yet here we are, the R squared is still north of ninety-five percent, and all of these other models can't come anywhere near. So you can do a time model, you can put in all kinds of metrics for, demand, we've seen people try and build sophisticated models with the on-chain metrics and off-chain metrics and data from exchanges and all kinds of different things, nothing comes comes close. So, the fact that you can find the problems with the model and still not find anything better than it, or still not find a way of improving its explanatory power, should be giving people, reason to pause and think rather than just, you know, this, this kind of petulant, "Oh, well, here you go, I found a reason of something that shouldn't be in the model, but it's not there, therefore your model's wrong." I, I think that's, that, that's definitely the wrong way to approach

Yeah. one other idea as well. So maybe a skeptic might say, "Well, hold on, there's all these different models now, right? So the first model that Plan B you put out was for fifty-five thousand or prediction, that's the what the model would say, and then a later model was saying, you know, one hundred thousand, and that was, there are different, there were different versions of the model, and, you know, there are other ways you can cut the data. You could say, "Oh, look, I'm looking at the one-day model, or I'm looking at the three hundred and sixty-five-day model." Would, would that look like to an outsider, "Oh, well, you guys are just covering your bases for this coming bull market and it's just, you know, it's going up, and you just got all these different places that you'll just point back to and say, 'Yeah Fine, yeah. Yeah,

I can understand that critic, and especially if you're not used to investing or, Using models like this or even making models like that, that's even smaller group. and I, I must imagine, you know, I, I crossed the ninety-five thousand followers, today, but I, I bet you that eighty percent of the people, yeah, is, is not, is not used to using models every day, or, or let, let alone making them. So I really understand that critic, and it must look like, oh, they're changing. I, I think even Eric Wall, mentions this as, as one of, it's Changing, it, it keeps changing all the way, the formulas. But,

I, I think the main thing that I should say here is that we see science unfolding before our eyes here. us-- it used to be, letters between scientists in the, in the old days, right? The, the, the famous letters of mathematicians that were found and, and later, studied and discovered. But with the internet, it's, it's, everything goes so fast, and it's going through Twitter, of all media, it's going through Twitter, the fastest. So, you're seeing, the debate, the highly scientif-- scientific debate unfolding for your eyes, and it must look, you-- some things are better if you don't know how they're made. It's like, it's the same for sausage and, and the law, but also with models. So, so yeah, you, you see, it's all there Even the failures. And, and it's, I would say the main argument is it's, it's evolving. So yeah, you know, the first model, it adjusted for, for lost Satoshi coins, just a very a- arbitrary way. you could do that far more advanced, and that would give a slightly different model. And you could even skip all the lost, lost coins, just pretend it's, it's not very material impact, and it would give a slightly different model. So, yeah, you could lo- use daily data, weekly- Daily data, monthly data, it would give a slightly different model. so that I think we're, we're seeing his, yeah, signs un-unfolding for our eyes in, on Twitter. keep that in mind, and the other thing is It's order of magnitude, right? It's not a very precise thing. So it's, it's not like the bullet and the gun that Saifedean described. It's not, physics or, or chemistry even. It's, it's, a social science. So it's order of magnitude, and even if it's order of magnitude right, I think the models are very, very helpful.

Yeah, yeah, I think this is, yeah, this is the, you know, the idea that, first of all, yeah, there are all these different ways of, running the regression, and yeah, you'll get fifty or one hundred or one hundred and fifty or whatever, for next year. But, a-and that sounds like it's a very wide range, just like, as I was mentioning earlier, three to thirteen for this year sounds like a very wide range. However, it's a wide range when you're looking at it from the perspective of this year, but if you're looking at it from the perspective of Bitcoin over the last ten years and the coming ten years, it's actually a very precise, very precise estimate, you know, between, let's say potentially point three cents And let's say one million dollar Bitcoin, in ten years, for instance, if that were the case, then actually being able to pinpoint this year's prices to be somewhere between three and thirteen is astonishing accuracy. That's, that's, I think the thing that people miss in this model. So, and, and, and I think the other aspect of it is that even if, you know, even, even if the numbers don't exactly pan out,

The margin of error around this is large enough that you still, very accurate, the, the model is still very precise when you look at it over the long, o-over the long, o-over the long period of time it's, it's a lot of variation only because you're looking at it statically today, but if you're looking at it over the, ten, twenty year period, it's still, very small amount of variation.

Excellent points, both of you. let's talk a little bit about the future of Bitcoin modeling. I, I, over time, there have been models that have been tried and failed, and it seems that so far, stock to flow has Survived, basically. it's this process. How do you see modeling evolving? Do you see, are there other ideas that are coming down the pipe, down the pipeline, and how do you sort of see that changing over time? Plan B?

yeah, first of all, the quote, "All models are wrong, some are useful," is of course, appropriate here. so yeah, there will come a day that stock-to-flow model maybe is proven wrong. it's all part of the game, part of science. so for, like you said, it's, it's still standing. so, yeah, what one of the, very much discussed areas, was co-integration, of course. I think, most of the action right now is there.

yeah, I, I don't think it's, maybe for now it's a very technical, subject. On the other hand, co-- you know, if there is co-integration, you would have more confidence about it not being a spurious relation. and if there's no co-integration, 'cause the whole debate right now is, is, is about, hey, is, is, is stock to flow a trending or a non-trending, stationary variable, and if, if stock to flow isn't going up, is, is only going up beca-because of structural breaks, then there is no co-integration. Would that hurt the model? Well, yes and no. It doesn't hurt the model, the model's still standing, but it would take some of the confidence that you get from a series Being co-integrated away. on the other hand, a, an experiment like Safedean did with the Satoshi coins, would also give confidence. And of course, I chose the route, of including other assets, cross-- so making a non-time series model, but a cross-asset model, which, gets rid of all co-integration problem altogether. It, it introduces other problems, less data points, of course, but, but, you know, so I think there's a lot of, and, and there's, there's, totally other models as well that people look at, Metcalf, law of, of, of, adaption, if you will, the number of addresses, the number of transactions, and, those, those models are-- I looked on, on some of these models as well. Those are also very interesting, but, yeah. The, for example, the number of transactions model has the problem of, batching if, if, exchanges are, so they all went batching transactions the last couple of years. So that totally breaks the model, it takes the number of transactions down, so you have to look at UTXOs maybe, and, and so there's, yeah, there's definitely more modeling going on, but to be honest, as an investor, I'm only, going with the stock to flow model right now.

Of course. and let's talk a little bit about the implications of this modeling work, whether that is for Bitcoin, market participants, as in if you're a miner, you're, you're an investor, or the broader world. Saifedean, did you wanna start on that? The implications of this model onto, Bitcoin, Bitcoiners and the rest of the world?

Honestly, I think, I'm not sure how you're gonna like, how much you're gonna like this, Stefan, but I think the, the, the most important implication of this model for me personally is that it is Probably the most serious challenge, to Austrian economics I've ever seen. Like I've, the, I've, after learning Austrian economics, after studying this, I became extremely skeptical of mathematical models, and, I generally, when, when I, when I look into modeling, it ends up being an exercise of just finding out what mistakes people have made in order to get the results that they want to do. And if you're studying academic research, you look at, you, you're Generally dealing with garbage statistics, with an agenda of people trying to crowbar as many variables and, trying to use as much statistical techniques as they possibly can to try and, arrive at the conclusions that they want to arrive at. And so I was extremely skeptical of the idea that you could find, mathematical models that could predict human behavior. And I think, you know, when you read Austrian economics, human action in particular, you know, Mises is very clear about the fact there can be no constants in human action. individuals are acting and individuals are not reducible to simple, equations. There are too many complex factors that come into play and that you aren't able to, abstract from The complexity of human decision making and the human will and human action, you can't abstract away from that into numerical equations. And, you know When you see things that involve human action, you can't get, as I was saying earlier, this is something on which mechas and e-econometrisians would agree, you, you don't get an R squared that is high if something involves, human action. So if you're measuring the R squared for The gun, you know, you'll get something like ninety-five percent because there's always going to be an error margin in the, the, the speed of the wind or whatever when you're calculating how far the, the, the bullet is going to run. But here we've got Something that's just a very simple variable, which is clearly exogenous, which was determined by somebody in two thousand eight, and we have billions of people all over the world who every day wake up and make a decision about, whether they're going to buy Bitcoin, sell Bitcoin, or not do anything about their Bitcoins, but not, not buy or sell. You know, seven billion people every morning make that choice, and as a result of those seven billion choices, you get the Bitcoin price at the end of the day. Of the day. And the fact that it is so well correlated to the number that was made before two thousand and nine is absolutely mind blowing. I still can't get over it, and I think it is, it, it's the most serious challenge to, Mises' human action, is the idea that There can be no constants in human action, that you can't reduce human action to mathematical variables. Well, Plan B has done it. It's, it's, it's amazing. It's, it's absolutely mind-blowing, but we can find an equation based on a clearly fixed exogenous variable, and we can estimate the price of Bitcoin with astonishing accuracy. So I'm not gonna say that it's going to make me revise, my view on Austrian economics, and I'm not going to stop being an Austrian economist, but I think after a hundred years of Mises, or more than a hundred years of Mises making these points, we finally have one example of, something that emerges out of human actions that is, predictable according to a constant binary equation. So if this, if, if this, formula continues to hold over the next few years, it's, it- It's ins- I mean, it's the fact that it's already held so far is still astonishing, but if it continues to hold past one more halving and another halving, it's, it's, it's, it's amazing. I, I, I just can't stop. Thinking about it.

Yeah, that's, well, we'll, we'll have to see, right? and, I might take a couple questions out of the chat here. I've got one here for Plan B. So, we've got the question here, I'm putting it up on screen now. The question is, "What does Plan B think on Burger Crypto AM's analysis of co-integration for structural breaks? Any thoughts? "

Yeah, that, that's what I talked about earlier, so that's the time series world, not the cross asset model. It's the, discussion about co-integration, if it's there, and both Berger Klipptow and, and Nick, of course, in earlier studies and, Manuel Anders from the Landesbank. we concluded there is co-integration, so if there is co-integration, it really adds confidence to the model that the model, the, the, the relationship between stock to flow and price isn't spurious, so it's real Now, the state of the art, top of the spear thing is structural breaks. So all the co-integration tests, they, they say there's co-integration But there is some tests that test for structural breaks in the dataset, and of course, the halvings, you know, the stock to flow doubling, well, twice now and, and, and, and in a week again. Could be seen as structural breaks, and if you adjust for those structural breaks, that-- so if you use the tests that adjust for structural breaks, then the co-integration, falls away. And, Berge Crypto, I think, didn't test yet, for co-integration with structural breaks, but Nick, Amblow did. it took his computer, by the way, two days of, twenty-four seven running, but, so, and it concluded, if I'm I think it was yesterday, so I, I, I'm not quite sure, but I think he concluded that there is, if you account for structural breaks, there is no core integration so that we would take some of the credibility of the model away. Point. Yeah. That's, that's just how it is. Yeah. Gotcha. Thank you for that. On the other hand, maybe I should add, because even in the early article and the early tweets, I, I, I didn't mention core integration, but I mentioned that, the stock of, of the Bitcoin price So the stock to flow model value every single year, and in essence, that is what co-integration is about, right? So, we might find a third group of tests that, that eventually, agrees with co-integration again. So, but, but the, the concept and the basic of co-integration is that the series keep together very tightly, and that's what you see in the, in the series. So, so, yeah, I guess we have to do more tests and, but we also have to, yeah, notice that this is the time series world with co-integration, co-integration is very important, et cetera, et cetera, and, and of course, I'd like to broaden that space of thinking, I'd like to go to the next level to the cross asset world.

Great, okay, thank you for that. And Saifedean, I've got a question for you from the chat here as well. So the question here is, please ask Saifedean what the implications are having a money with an expected increase in value better than any productive investment in terms of ROE, return on, investment, I guess.

Yeah. Well, I think, this is, fittingly enough for today's episode, this is a phase question, so it depends on what phase are we talking about. In this current phase, when Bitcoin is still less than one percent of the global money supply, it's in-investing in Bitcoin beating other, possible investments is essentially,

I, I like to think of it here, you know, at, at this point, although, although Bitcoin is a savings technology as, Our, great leader Pierre Rochard likes to always remind us, it's, I, I, I, I'd say that at this point, Bitcoin is a little bit more of like a, an, a venture capital or angel investment in, a startup And it's as if you're investing in a little startup that's going to, it, that's, angling for replacing central banks. So imagine, you know, just like Uber against the taxi commissions, Bitcoin is like a decentralized Uber for central banks. And it's, it started off being very tiny, but it has the potential, put, one day, of a total addressable market that is all the money supply in the entire world, kicking, you know, taking away all the market share from all the central banks. So now Bitcoin is like a growth stock. Now Bitcoin is like a, it, it's, it's a highly,

it, it, it's an investment with a very high potential return, because, you know, you're, you're gambling, you're betting on the fact that something that's one percent of the global money supply is gonna have a much bigger number. So at this point, it is like an investment, and it might, you know, for me, the fact that Bitcoin is beating all other investments, in my mind, the way that I interpret And, and, and the societal value, the, the value that society attaches on hard money at this point is enormously, high, and Bitcoin is addressing that market. And so,

S2FX So the fact that, Bitcoin beats other investments is essentially the, what the market is saying is that, you know, there are no better investments for the human race to be making right now than, getting rid of central banking, and I think that makes a lot of sense. you know, the more people stop investing in other things and they start investing in this new startup that's going to displace central banking, the faster we can be done with central banking and, get back to living like civilized human beings. So this is It is a high return investment because it has a massive return, because, when people are able to move to Bitcoin, they benefit enormously from it. So I think at this point, you know, this is very good that Bitcoin beats other investments because we want to get stop people from investing in, other pointless things and invest in something that's more important, which is, you know, putting central banks out of, business. So I think that's great. Now, once that's accomplished and once central banks are out of business, it's not going to be possible for Bitcoin And others, to be beating all investments, because I'll assume the point at which Bitcoin's supply growth has stopped, Bitcoin will only rise in value to the extent that the production of other goods and services increases. In other words, once we have the, Bitcoin supply is fixed or the growth has, dropped, the growth rate has dropped to be Almost equivalent to zero. Then, when, you know, the Bitcoin supply's not increasing, but our supply of apples and oranges and homes and cars and goods and services is increasing, and so over time, the price of Bitcoin in terms of those things rises, and so Bitcoin is, increasing in value in real terms, but it can only increase in value in real terms if People are investing and making more apples and more oranges and more cars. So it's basically, you can't beat the market by holding money, in, in, in a situation which Bitcoin is the only money, you won't be able to beat the market just by holding money. you, what you'll achieve by holding money is the expected rate of return on the market or, or the real growth rate in production, but that has to Happen because people are investing, and that's gonna happen because people are-- who are investing, they're going to be investing because they're getting better returns. So eventually, you're gonna get your money supply, you know, your bitcoins will buy you more apples next year than they will this year, but the apple farmer who engaged in production will not just benefit from the appreciation of their money, but also they'll benefit from the fact that they're-- the, the profit that they're making is higher. So you won't be able to beat the investment Adjustments for the long run. So enjoy these gains while you can.

I, I think I agree very much with that answer. I've got one interesting question here for Plan B. the question is, what does Plan B think Phase Five is? He keeps mentioning military thinkers. What is he envis- envisaging?

Yeah. I have, I have my ideas about, about, phase five, of course. you know, it, it, it, it- Only making it an institutional grade asset, financial asset, would be, would be enough of a jump for me to, to justify the, valuations. So it's not even a state level investing or, or a central bank starting to invest in Bitcoin, just, just make it an institutional grade investment, as, investing asset, and, and which it is not now, absolutely not. It's, it's, you know, hedge fund are, are investing in it, gold investors, everybody with their own, their own money, but banks and pension funds, well, maybe some very, very liberal, pension funds, but, no, phase, phase five, phase five will be a totally different thing And, and think-- and, and that's why I mention, strategic thinkers, military thinkers, and, geopolitical thinkers, 'cause it's a global money, and it, it-- if the next phase is five point five trillion, it will be bigger than the mil-- than the, the monetary base of the US dollar, which is three trillion. So it will have geopolitical consequences, and it will-- I know the Department of Defense is writing papers about Bitcoin. You know, how, how to attack it, how to follow it, how to, well, whatever. so I think we're, we're, we're sort of understaffed in, in Bitcoin, with only developers, miners, and, a-and now some, some, some very early investors and quants and economists, some very liberal thinkers in those areas. We need more. We need, and, and really, I, I have, of course, I know some of the geopolitical thinkers and military thinkers, 'cause I- I invested, you know, the, the company that I work for, I invested like, like a hundred billion dollars. so we, we talk to those people and they think differently. They map out a route to this fifth phase. They, they make multiple scenarios. They would put markers on the way and you could recognize, hey, this is, you know, if, if you think about it be-before and market and plot it and make it a scenario, you could recognize those, those points on the way. And I really- To miss that thinking right now in Bitcoin and hope, and maybe I, this is the opportunity to call upon those brains to join this journey, because I think, yeah, Bitcoin will be much bigger than a, ju-just, just an investment, just an asset, it will be money. So the, the thing that humans choose in all their, trading, in all their as their unit of account eventually. So it, it will be big.

Excellent. so look, I think that's probably a, a good spot to start, winding it, winding this down. I just wondering if you gentlemen had any closing thoughts for the listeners. Saifedean, did you want to start?

well, somebody, in the chat asked a question. I, I can't think of anything, so I'm just gonna answer that question. They're asking me what I think about the future of gold. And I'll have to say that over the past few months and since I wrote my book, I've been leaning, leaning more toward thinking that gold is the new silver. I, you know, I go back and forth and I don't think, I, I, I'm not, my mind isn't made up, I'm not sure what's going to happen, and I'm highly, highly careful about writing off gold because that's been done many, many times by many people before and, we you know, the world laughed at them eventually. But I think, you know, the, all of the, all, all of the previous pretenders to gold were always designed by people who wanted to replace gold because they wanted something more inflationary that they can control. And Bitcoin, Bitcoin attacks gold in the, you know, in, in, in its weak spot, in its or in its strength. It attacks it really where it matters, which is at the stop to flow. So Bitcoin isn't an, just another way for somebody to get rid of gold so that we can, So that we can, so, so that we can inflate and, and have inflationary money, Bitcoin is a way that gets, i-is a replacement for gold that is less inflationary. And I think looking at how silver was- de-monetized and became more and more of an industrial method, makes me think of a way in which this would happen with gold. And so I think if the, you know, if over the next ten, twenty, thirty years, Bitcoin's monetary premium continues to rise, so people hold more and more Bitcoin, the value of Bitcoin goes up, but the value of gold doesn't go up significantly, the monetary premium around gold doesn't go up significantly, then gold d-is declining in value in real terms, and it becomes more- More and more economical to be used, for it to be used in industrial applications. So people will start using more gold in electronics because it starts getting cheaper and cheaper. And once you start doing that, once you start in-- once you start putting gold in these industrial uses This is, it's not exactly like consuming gold because you can always get it back out of the phone or out of the electronics, but it is similar because the cost of extracting it from those electronics can become higher and higher. So once gold becomes cheap enough that, let's say, an ounce is one thousand dollars, but you can put it in a phone, and then if you wanted to get that ounce out of phones, it would cost you something like ten thousand dollars to get one ounce, that gold is practically gone out of the supply, and so we're back to the situation with the-- we're back to a similar situation with silver, where the gold stock is now declining, and so the flow or the new annual production is becoming more significant compared to The stock price. So I can see this happening more and more as, if, i-if the situation continues as we have, and I think, what's, I, I'd say Kind of making me lean more toward thinking about this is that you look at the world economy and all of the fireworks and all of the disasters and catastrophes happening and Gold still can't get to a new all-time high. And so, you know, it's looking more and more likely that the limitations of gold, the fact that you can't clear it internationally, and the fact that banks, central banks control it and own a lot of it, are just limiting its ability to play its monetary role more and more. And I can see how with Bitcoin there There's less of a, there's even less demand for people to be using gold, and I can see how it could, switch toward becoming, more and more of an industrial metal over time

Excellent. a Plan B as well, if you've got any closing thoughts, and perhaps one last question for you would be, would you-- You, you've spoken about going dark, is that something you're still thinking about doing? And, you know, would-- When would you do that?

I'll leave that for the end. I'll, I'll first, go with Saifedean on the gold and silver, view. I think, that view aligns with my view, but, on a, on a bigger- Scale, I think Bitcoin is gonna suck out the monetary premium of everything that's out there. So you see this black hole, a metaphor sometimes. but right now a lot of things are, are used by, by investors and normal people to store their wealth, and, and, you know, everything that cannot be printed by the government is good. So silver, gold, real estate, there's a lot of, lot of monetary premium, premiums in real estate at the moment. A lot of apartments and houses that, that people don't live in, but they, they just hold it for investment, which is a waste, of course, for humanity. so I think, Bitcoin has a very- Important role to play as a, a monetary asset, the best monetary asset, the, the hardest money, the soundest money, without utility value. So it doesn't, it doesn't destroy the utility value like real estate and also gold and, and especially silver are doing right now. So that will be phase, phase six and seven stuff, I guess, but, but yeah, I, I could see that happening. Well, and, and in line of that, and what I said earlier about military, thinking and, and Bitcoin being, bigger than the monetary base of the US dollar me going dark, yeah, a lot of people think, that, that is a serious option. So, yeah, it would kill a lot of, a lot of, community followers, social media asset, if you will, but In the end, if my-- a lot of people think I, I go dark when the model breaks, when it-- when, when they shout at me for, being wrong, that's not the case. I think I'll stay then, 'cause, we need a different model and, et cetera. I will go dark if the model- is successful, 'cause if the model is successful, it, it will be an-- it will not be a pretty picture. It will be, it will be nasty. It will, it will maybe war. It will be yeah, people have Bitcoin, some people, don't have Bitcoin. it will be some countries have Bitcoins, others won't have Bitcoins. it will be the US dollar losing its reserve status. it will be geopolitical, it will be military. So, either I play a role in there? Which means I have to disappear from Twitter, or it will be too dangerous for me, to, to, to be there, and I will go dark. So yeah, that is a serious option that's, that's out on the flip right now.

Well, yeah, thank you very much for that. And, look, I, I guess I'll give you, gentleman, a chance to, tell the listeners where to find you. So, Saifedean, do you wanna just start? And I've put up on screen, your website, so just tell your lis-tell the listeners, where they can go to find you online or to get the book, The Bitcoin Standard.

Yeah, my website saifedean dot com, it has, links to the book. It's, books coming out to twenty languages now, the Bitcoin Standard, so you can, see all the languages and where to buy them from. You can also see some of my recent research, as well as my online courses, which is now my, full time job, having, left my university. I'm teaching, Austrian economics and Bitcoin economics online, and, you can sign up for my courses at any time. Because the, you know, you download the videos and you get to, see the lectures and the discussion sessions. we have a class right now that is in its last week, we finished next week, will be the last week for my Economics 12 class, but you can take it at any time, you can take the class at any time, and I will always be having weekly discussion sessions throughout the, ev- even after the course is done being taught live, I'll still be having a weekly discussion session so you can, do the lectures, on your own pace and then come join a discussion session with, me. at any time if you have any questions. So yeah, you can find that on, Saifedean dot com, and you can also see, you can also sign up for, my mailing list to stay, abreast of all of my, New announcements, and, you can see, you can also sign up to buy my, forthcoming book, The Principles of Economics textbook, which I'm writing based on my courses. you can, buy a, you can buy an advanced signed copy. of the book now and get access to the draft of the book as it is being written.

Fantastic. And Plan B, I've, got your, Twitter profile up on screen. Do you wanna just tell the listeners where they can find you and who you're looking to hear from?

Yup. So I'm on Twitter, you see the page right now, it's, Plan B at hundred trillion US dollars. It's also on the screen. And, well, there, you, from there, you can go to the, Medium articles, I wrote and to the data that is being used in the analysis, it's on GitHub. so yeah, maybe something new, I'll be launching a website, later this week that will have all the papers on there, but also all the podcasts, which is about ten podcasts right now, so people who wanna binge-watch, binge-listen, Plan B pod-podcast can, can do it right there. yeah, so I'm, I'm very much looking forward to debates and to critiques on the model, mind you, I, I'm looking for, the, scientific debate. So, preferably with models, with analysis, with data, if you have some very strong logic, preferably Austrian economic logic or, or, yeah, I would be very interested in, in hearing from you. And I, I'll repeat my, my call for, geopolitical Strategic and military thinkers to join the journey.

Fantastic. Well, look, I think that's, going to do it. So thank you very much, Plan B, and Saifedean for joining me. Cheers. Thank

you. Bye-bye.

Excellent. So, just, if you enjoyed the show, make sure you subscribe to the YouTube channel and you can also get the podcast online at stephanelivera dot com, and I'll put a transcript, and of course, this episode will be put onto the audio stream as well for those listeners who want to just listen on the audio only. otherwise, that's it. Thanks, and I'll see you in the citadels.