Latest / Simply Bitcoin / Giovanni Santostasi | Predicting $1M Bitcoin | Simply Bitcoin IRL

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Giovanni Santostasi | Predicting $1M Bitcoin | Simply Bitcoin IRL · Simply Bitcoin

• 0:00
  Hello everybody, welcome to another episode of Simply
• 0:03
  Bitcoin IRL. Today we have a very special
• 0:06
  guest, we have Giovanni. Giovanni, I'm going to butcher
• 0:09
  your last name, I apologize. Santo Stasi, and he is the
• 0:16
  discoverer of the possible association, the relationship
• 0:21
  between the power law and Bitcoins price.
• 0:24
  I've been looking forward to this episode for quite a while
• 0:27
  now because it seems to be making the rounds on YouTube and
• 0:31
  on Twitter. And it's interesting because it
• 0:35
  kind of allows us to predict the price of Bitcoin into the
• 0:38
  future. So I'm really looking forward to
• 0:41
  this conversation because I have a lot to learn and I'm sure the
• 0:44
  audience has a lot of questions as well.
• 0:47
  He also has a PhD in astrophysics, which is quite
• 0:52
  impressive. But before we jump into the
• 0:54
  show, I do want to give a very special shout out to the Bitcoin
• 0:58
  company that powers simply Bitcoin IRL.
• 1:00
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  Bitcoin platforms like bitcoinwell.com.
• 1:35
  So check them out. Anyways, I do want to bring
• 1:37
  Avani on to the stage. First off, with an apology,
• 1:41
  Giovanni, how do you properly pronounce your last name?
• 1:44
  You did a great job. Best is to split it into Santos
• 1:49
  Stasi Santos Stasi, but you did a great job.
• 1:52
  Thank you. Thank you, Santos.
• 1:55
  Stasi and people destroying my name all the time, so it's good.
• 2:00
  I I speak Spanish too, so I thought I would have like an
• 2:02
  advantage in saying it. So Santo Stasi.
• 2:05
  OK, perfect. Boom.
• 2:07
  All right, thank you, Giovanni. So love big fan of your work.
• 2:12
  I've consumed a lot of your content.
• 2:14
  I've consumed a lot of of you know, the podcast that you've
• 2:16
  been on, you've made the rounds and your work has has caught the
• 2:21
  attention of a lot of people. So first I want to start it off
• 2:25
  with this. What is a power law?
• 2:28
  So a power law is actually a simple relationship between two
• 2:32
  quantities. So it's, you know, if you go to
• 2:36
  the simplest definition, if you have two quantity, right?
• 2:40
  Because this is what we do in physics all the time.
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  We try to understand how different quantities nature
• 2:46
  relate to each other. And usually we use mathematics
• 2:50
  to explain how they work together, right?
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  So anytime you have a quantity Y, let's say it could be
• 2:55
  anything. There are many examples that as
• 2:59
  we talked I will show you. But in generally you have a
• 3:01
  quantity Y that's relate, you know, it's maybe 'cause or
• 3:05
  driven because power laws usually are also associated with
• 3:09
  some mechanism. You know, that is an important
• 3:11
  thing. It is not just that you know,
• 3:13
  some random association between two quantities that there is
• 3:16
  usually a link between these two.
• 3:18
  And so if you have a quantity Y and a quantity X, if you have an
• 3:23
  equation that says Y equal X, then the power, that is why it's
• 3:28
  called a power law, because it's the power, you raise it to some
• 3:31
  power square cube, it could be one.
• 3:34
  And in that case, it's a simple linear relationship, right?
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  Y equal X. There is a quantity that is
• 3:40
  proportional to another quantity X.
• 3:44
  In that case, it's a particular case of a power law one, right?
• 3:47
  But the general case says it could be anything.
• 3:50
  It could be two, it could be three, it could be five, it
• 3:53
  could be a negative number, it could be a fraction, you know,
• 3:57
  one other two or 0.3 doesn't have to be even an integer.
• 4:00
  It can be 1.34, you know, something like that.
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  And the relevance of these things arbitrary, I say why?
• 4:06
  Why would you focus on something like that?
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  This because believe it or not, a lot a lot of phenomena all
• 4:15
  around us, in particular a lot of physical laws, but also
• 4:19
  biological relationship in Physiology.
• 4:22
  Even different social phenomena like for example, the impact of
• 4:27
  an of an influencer on the on a network, you know, on a social
• 4:31
  network. All these type of phenomena can
• 4:35
  be often described with a simple relationship like that because
• 4:39
  it know it sounds simple. In fact, it goes in body like
• 4:43
  some people say it's complicated.
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  What is complicated about, I'm telling you there is a simple
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  relationship between two quantities, right?
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  That is relevant for Bitcoin. In a moment I will tell you what
• 4:53
  are this relationship in Bitcoins, what is the relevance
• 4:56
  for Bitcoin? But in general, it's of it, it's
• 4:59
  actually one of the simplest possible relationship.
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  And then people go the other opposite way.
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  They say, oh, it's too simple. It cannot really describe
• 5:06
  something complex like Bitcoin. So they oscillate from being too
• 5:10
  complicated, too simple. It's kind of funny.
• 5:13
  I know it takes time to think about this stuff, right?
• 5:16
  If you're not used, it takes time.
• 5:19
  But the idea is that, you know, it's a simple relationship, a
• 5:23
  mathematical relationship. It has very precise reasons why
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  we see them, but we see them almost everywhere in nature.
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  It's almost like a joke. Sometime in the physics
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  community, You know, I found that one time I found a shirt
• 5:36
  that says I, I went to a physics conference and all what they got
• 5:41
  was a lousy power, power law, Very funny.
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  But in terms of Bitcoin, it turns out that Bitcoin is a
• 5:49
  power law. In fact, it's not just a power
• 5:51
  law, it's a bunch of power law. I, I found at least six.
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  And in fact, there are other power laws like, you know, the
• 5:57
  relationship between the along for example, others hold of
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  their Bitcoin that is a power law.
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  So that the main one that everybody's talking about is the
• 6:09
  core one that also depends on other power law is the power law
• 6:13
  between price and time. So these two things that are
• 6:17
  very fundamental, right? Because we would like to know
• 6:20
  what if it is possible, how the price of Bitcoin grows in time,
• 6:25
  right? Is it possible to find a simple
• 6:28
  equation that describes how the growth of Bitcoin happens in
• 6:34
  time? Yes, I found it.
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  And This is why it's both fascinating for people but also
• 6:40
  controversial. Some people ignore it.
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  Some people think it's a big deal.
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  You know, some people are angry about it because, you know, they
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  say it's impossible that Bitcoin can be described as simple
• 6:52
  equation. But if you want to describe it
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  and then we can, we can go down, you know, the rabbit hole and
• 6:59
  explain you how I found it, why I think it's true, you know,
• 7:02
  what is the supporting evidence. But the bottom line is that the
• 7:06
  price is equal to the time and the time is measured in terms of
• 7:11
  how much time is passed since the birth of Bitcoin, right?
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  We can measure it in days, for example.
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  So you give me the number of days since any time, both in the
• 7:21
  past but also in the future. Because once you have a simple
• 7:24
  equation like that, that you can extrapolate the equation to the
• 7:28
  future and you can calculate what the price is in two years
• 7:31
  from now, five years from now, 10 years from now, now.
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  And the certain point, of course something is going to give, you
• 7:37
  know, because it cannot be that Bitcoin was up forever, right?
• 7:41
  But let's say at least for the next 10 years, maybe even 20, we
• 7:44
  can project these equation and calculate.
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  And the equation is very simple. It says that the price of
• 7:51
  Bitcoin is proportional to the time, to the power of 6.
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  Now it's not exactly 6, it's 5.83, but something close to
• 8:00
  six. So the power of 6, this is it,
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  this is it. It's crazy.
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  I know it's crazy, but there is a simple equation that can tell
• 8:08
  us the price, but it works. It works and there is a real
• 8:11
  science behind why it works. So that is a summary of what
• 8:16
  power laws are and the relevance for Bitcoin because Bitcoin is a
• 8:23
  power law and that power law determines so many things
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  because there are both scientific consequences for
• 8:32
  being a power law because it's, you know, given that they are so
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  common in nature, people have studied, they are trying to
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  understand why they get generated, you know, what is
• 8:40
  their significance. But also it's a philosophy.
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  It's a philosophy about what Bitcoin means, right?
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  The fact that this fall are very precise pattern, what generates
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  the pattern, what are the implications?
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  So it's an entire understanding, almost like a word view about
• 8:57
  Bitcoin. It's really essential I I say if
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  you don't understand these signs, if you don't understand
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  that Bitcoin is a power law, you absolutely don't understand
• 9:07
  Bitcoin. You, your understanding of
• 9:09
  Bitcoin is like you know pre signs, you know, it's a pretty,
• 9:13
  you can still leave, you know, and you still can buy, sell
• 9:16
  Bitcoin, but it's almost like you are a, a primitive person.
• 9:19
  You know you you, you are pre signs.
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  You know pre Bitcoin signs. So, so let me ask you something.
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  So I did a little bit of research on, on power laws.
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  It it's, it's found in nature. Why is it that Bitcoin, you
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  know, adheres to a power law versus, you know, the
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  traditional financial system or, you know, Fiat currencies?
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  Like what is it about Bitcoin that you know makes it adhere to
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  this power law? Is it because it's based on
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  proof of work? It's anchored to the universe be
• 9:51
  AP of proof of work? Is it because of its cap supply?
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  Is it because of the halving? Like what makes Bitcoin unique
• 9:59
  that allows you to use your astrophysics background to
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  apply, you know, this power law on top of it?
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  Because I've seen the people that you know, that are, are not
• 10:12
  fans of your theory. And basically they're saying
• 10:14
  like it's impossible to map out the future price of Bitcoin.
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  So what makes Bitcoin as an asset unique in in in in the
• 10:24
  sense that you're able to apply this to bitcoins, just to
• 10:29
  Bitcoin, and then have a pretty good understanding of where the
• 10:33
  future price is going to be at any given time.
• 10:37
  Yeah. So it's a, it's a the major
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  question, right, The most fundamentally important
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  question. So I'm glad that you're asking
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  that question. And in fact, it's what as a
• 10:45
  scientist you want to ask yourself, right, what is going
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  on? Why?
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  So yes. And first of all, you know, in
• 10:54
  science, we always want to understand before we answer why
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  we want to understand more about how and what.
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  So, you know, you go deeper and you ask a bunch of question and,
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  and at some point, if I could show you some of my slides, I
• 11:08
  can show you how we arrived to certain conclusion, right?
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  Because before answering, why you want to go deeper and say,
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  OK, where, where this comes this power law comes from?
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  What is the right what that what is driving it?
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  Is there any other explanation? And the beauty with Bitcoin,
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  which we have all this information from the from the
• 11:27
  chain, right from from the blockchain.
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  We can learn about the adoption, for example, through addresses
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  we can learn about we can learn about the energy that is in the
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  system. We can learn about the many
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  transactions. You know, we have all this
• 11:46
  information available and so we can look at all these
• 11:48
  connections and get deeper and have a better understanding.
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  But again, because it's such a general question, I can give you
• 11:55
  kind of a preview of, well, it's not a spoiler.
• 11:58
  And then we can go deeper and then show you the links and all
• 12:02
  the steps to why we have reached this conclusion by the
• 12:05
  conclusion. When we look at all the
• 12:07
  information and they and also you have to understand it's a
• 12:10
  work in progress, right? Once you have the beauty of this
• 12:14
  approach that is basically using science to understand Bitcoin is
• 12:18
  that it gives us a framework where we can go deeper and
• 12:21
  deeper in trying to answer more and more of these questions.
• 12:24
  But right now my, my main conclusion, my main
• 12:27
  understanding, my provisional understanding, because in
• 12:29
  science you never write to one single conclusion.
• 12:32
  You always improve, improve, you know, you get more information,
• 12:35
  you're expanding your understanding.
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  But my understanding is right now is this Bitcoin is really
• 12:41
  what many of us says it is, right?
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  Because many of us maybe didn't go deep in besides, but we have
• 12:48
  a very strong intuition. Some of our also say points of
• 12:53
  reference like Sailor or Amos, you know, with these Bitcoin
• 12:58
  standard, people say things about Bitcoin because once you
• 13:01
  deal with it, you have this intuition.
• 13:03
  But you know, maybe they don't have the evidence and the proof,
• 13:08
  the mathematical proof. But it turns out that a lot of
• 13:11
  these intuitions are true. So the intuition is Bitcoin is
• 13:14
  this huge big network. It's a network.
• 13:17
  It's in fact, I will say it does have some elements of other
• 13:21
  things that we had in the past, but it's unique.
• 13:24
  We never had anything really like Bitcoin.
• 13:27
  And This is why Bitcoin is different from NASDAQ.
• 13:30
  It's different from gold. Silver is the first time, but we
• 13:33
  have something that behaves exactly like Bitcoin, OK.
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  And so it's a network. It's a network of what it's.
• 13:40
  We make all of humans first of all, because it's all of us or
• 13:43
  the bitcoiners. How we interact.
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  We interact in in a way that is no similar to how people
• 13:51
  interact when we buy a stock because you know how many
• 13:56
  podcasts there are on, you know how to with the significance,
• 14:01
  the meaning of the beauty of the passion behind buying NASDAQ,
• 14:07
  You know, not me, right, Or even Tesla.
• 14:10
  Maybe there are some people that love Tesla, but it's not
• 14:13
  anything compatible with the passion of the involvement of
• 14:18
  the understanding that we have with Becon.
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  Becon is much more than just buying an asset.
• 14:24
  It's a it's a way of life almost right.
• 14:27
  So you have that element, you have data.
• 14:31
  It's almost like a religion, right?
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  The quote UN quote in in the most positive aspect of the
• 14:36
  religion, it links people, it creates passion, it creates, it
• 14:41
  opens your window. So there is all that element of
• 14:44
  it creates this network effect because that is one of the most
• 14:48
  important elements of why we have a power law.
• 14:50
  It's an expression of a network property of Bitcoin.
• 14:54
  Then you have a machines, you have a it's not just humans,
• 14:56
  it's also machines, right? It's these a combination of the
• 15:01
  mining machines that are increasing the security of the
• 15:04
  system. They are solving mathematical
• 15:05
  problem. Because in the end also what we
• 15:08
  call is is a code, right? So you have a code that is very
• 15:12
  precise, It does its own thing. It's it's cannot be modified.
• 15:18
  It has machines that are running the code.
• 15:20
  We're like humans interacting with the code.
• 15:23
  And then there is a market where you buy, sell, you know, because
• 15:26
  it's also an expression of human value.
• 15:28
  So if you actually show my slides, if you don't mind, I
• 15:33
  have this initial slide that is kind of what the theory, you
• 15:38
  know, in essence behind the mathematics behind the science.
• 15:42
  It's really like a a philosophy also, right?
• 15:45
  So it's told it tell us and that I use these Hurroboros with its
• 15:49
  ancient symbol for eternity because it's basically like a
• 15:53
  feedback loop, right, where all these things interact.
• 15:56
  And can you close the loop? You you have this human value
• 16:00
  that is expressed by Bitcoin because we are putting more and
• 16:03
  more of our earned money. You know, it's a trillion
• 16:06
  dollars now, Victor Capital, but eventually would be $10
• 16:10
  trillion, hundred trillion dollars.
• 16:12
  So it's representing in a very symbolic but also direct way all
• 16:17
  the values, all the things that we desire about the world.
• 16:21
  You know, and people have different desires, have
• 16:24
  different wishes. You know, like it's almost like
• 16:27
  a mirror. Everybody is putting inside the
• 16:29
  coin what we think. And then because of a network
• 16:33
  properties, the beauty of it is that is not proportional to how
• 16:38
  many of us enter in this network.
• 16:40
  It goes up with the square because this is what is called
• 16:44
  the Metcalf flow. So Bitcoin follows is actually
• 16:47
  one of the reason why we see that six that I will explain in
• 16:50
  a moment. These are amplification.
• 16:53
  There is an amplification of the impact of each of us.
• 16:57
  So I when we bring me a few double the number of big
• 17:01
  corners, we don't get two times the value.
• 17:04
  The the network doesn't become two times more valuable, it
• 17:07
  becomes four times more valuable.
• 17:09
  If we triple the number of the corners, the network becomes 9 *
• 17:14
  4 * 6 times. So it's a non linear effect that
• 17:17
  amplifies more and more. Ten of us 10 times more the
• 17:21
  corners 100 times the value. So it's a beautiful thing that
• 17:27
  we have this non linear effect that is a network property and
• 17:32
  it's expressed in the value directly of Bitcoin through the
• 17:36
  price. OK, because enough, as you see
• 17:38
  all some of the comments, people say one Bitcoin is one Bitcoin,
• 17:41
  but it's not true because Bitcoin is also interacting with
• 17:44
  the external world. And it's actually the fact that
• 17:48
  it's growing relatively to the dollar.
• 17:50
  It's an important thing. It's an expression of how
• 17:53
  valuable it is. And it's also the fact that, as
• 17:56
  I told you, it's a function of time.
• 17:58
  It's a direct function of time. You know how people say Bitcoin
• 18:01
  is time? Well, exactly.
• 18:03
  This is what we found scientifically, the Bitcoin is
• 18:06
  time. In fact, it's time to the six.
• 18:09
  OK. So it's amplified by a factor of
• 18:12
  6 because you have a growth of the corners.
• 18:16
  So the growth of bitcoiners goes up with the cube of time.
• 18:20
  It's not an adoption code. It's not a simple adoption code.
• 18:24
  It's actually also power law. So how bitcoiners grow, it's a
• 18:28
  power law. It's a fact.
• 18:29
  It goes up with the Cube of time, and then the price
• 18:35
  responds to this growth with the square of the bitcoiners.
• 18:39
  So This is why you get these power of time to the six.
• 18:45
  It's the combination of these two effects, the growth of the
• 18:49
  corners and how the system responds to this growth.
• 18:53
  When you combine together, you get six.
• 18:55
  That is crazy. It's an incredible a big number
• 18:59
  because you know when people say price goes parabolic, well, a
• 19:02
  parabola is the square, right? It's you know, the power is 2
• 19:08
  for the coin, the power is 6. So it's super parabolic.
• 19:12
  It grows really fast and then it turns out there is another power
• 19:17
  law, that is the power law between price and ash rate and
• 19:22
  that goes where the ash rate is equal to the price square.
• 19:27
  So as the price grows, more miners are coming in, they bring
• 19:32
  more security to the system. They make the system stronger
• 19:36
  and more reliable. But it it requires from the
• 19:40
  manner more and more commitment in the sense that now you have
• 19:43
  to put the square, right. So if you want to as the price
• 19:48
  goes up, you have to go up with the square of the price.
• 19:51
  So if the price double S, you have to put four times the ash
• 19:55
  rate, that means that the ash rate is also predictable, not
• 19:58
  just the price. And it's an equation that says
• 20:01
  ash rate equal time to the 12. So it grows really, really fast,
• 20:07
  and it's OK because, you know, it's energy.
• 20:10
  Well spent, You know, it goes in this monetary system of the
• 20:14
  world. You know, eventually we'll take
• 20:16
  over an entire world where all our values and our energy and
• 20:21
  our time, it's conserved, you know, so it's really a beautiful
• 20:26
  complete theory of what become is, where it's going.
• 20:32
  Why is important. And you know, when people say
• 20:34
  it's not big cap by anything, it is the cap.
• 20:37
  It's the cap about us, the cap about people putting the value,
• 20:42
  their energy with time, with dollars, with their thinking,
• 20:46
  their aspiration inside the network.
• 20:50
  So. Well response in this non linear
• 20:52
  way. That is amazing.
• 20:54
  So first of all, it is incredible.
• 20:56
  This is good stuff. It's obviously over my head.
• 20:58
  You know, I don't have a background in astrophysics, but
• 21:01
  I, I will say this, there is some things that you mentioned
• 21:06
  that I, I, I found quite fascinating, which is the
• 21:11
  spiritual component of Bitcoin, right?
• 21:13
  The, the reason that we all care so much about this, the aspect
• 21:19
  of the aligned incentive structure of model of Bitcoin.
• 21:22
  So, you know, node operators are running nodes because they don't
• 21:28
  want to trust someone else's copy of the blockchain.
• 21:30
  Bitcoin miners are mining Bitcoin because you know,
• 21:34
  they're following it, they're following profit.
• 21:36
  In the process of following profit, they're making the
• 21:39
  network stronger. The network gets stronger the
• 21:41
  higher the value proposition. The higher the value
• 21:44
  proposition, the more people buy it.
• 21:46
  So I'm, I'm instinctively understanding what you're saying
• 21:52
  and I do believe in number go up over time.
• 21:58
  What is fascinating to me is the fact that you've been able to
• 22:02
  apply, correct me if I'm wrong here when I say this, but this
• 22:07
  mathematical theory on top of that kind of documenting how it
• 22:11
  grows. Now my question to you is, how
• 22:15
  is this any different than for example, the the the other
• 22:19
  extremely popular kind of predictive model, which is plan
• 22:24
  BS stock to flow? Is that like a more, you know,
• 22:29
  archaic version of the power law model?
• 22:33
  What's your take on that? OK, so first of all, I get a lot
• 22:37
  of criticism about this because people say, hey, focus on your
• 22:41
  model. It's not a model, it's a theory.
• 22:44
  It's a full complete theory of how Bitcoin works.
• 22:47
  And and you know, don't talk bad about other models, but this is
• 22:51
  not how science works. Science.
• 22:53
  And by the way, somebody called me an astrologist.
• 22:55
  I am an astronomer. That is science and science and
• 22:59
  science people have worked in finance for a long time.
• 23:02
  We are among the most successful analyst of the stock market,
• 23:07
  etcetera. You know, they scientists.
• 23:09
  In fact, actually we have a problem in physics where too
• 23:13
  many physicists are going to Wall Street instead of
• 23:15
  discovering the laws of nature. So we are among the best experts
• 23:20
  in financial matters. Financial people don't
• 23:23
  understand the market, physicists do.
• 23:26
  Because physics understands everything.
• 23:28
  I know it sounds arrogant, but it's true.
• 23:30
  You know what a finance people ever done for us?
• 23:33
  Nothing, right? They invented quantity easy.
• 23:36
  While physicists make everything, almost everything we
• 23:40
  see around is made by physics. So anyway, S to F.
• 23:45
  So first of all, science doesn't work like that.
• 23:47
  Sometimes you have to point out also what is wrong, right before
• 23:51
  you build something new. You also have to point out what
• 23:57
  went wrong in other analysis. When, for example, my countryman
• 24:00
  Galileo came about with all the other people that created this
• 24:04
  revolution about, you know, our understanding of the universe,
• 24:09
  they had to tell, well, Aristotle is was wrong, right?
• 24:14
  They had to tell the Earth is not at the center of the
• 24:18
  universe. We needed to tell, you know,
• 24:20
  they need to tell both the new information, but also say what
• 24:24
  was wrong with the old information.
• 24:27
  So let me say a few things about S2F.
• 24:29
  The first thing is many people don't know that actually Plan B
• 24:34
  copied me literally because what happened historically is that I
• 24:41
  work on this field since 12 years.
• 24:45
  I in fact, the other day I was posting on my ex account all the
• 24:50
  different posts from I found all these old posts from Facebook
• 24:54
  and it was nostalgic and they started to show people my track
• 24:58
  record. I have 12 years of data analysis
• 25:01
  in Bitcoin. I analyze Bitcoin even before
• 25:04
  buying it because actually this is what convinced me to buy
• 25:07
  Bitcoin all the way to 2012 when I analyzed the price for the
• 25:13
  first time. I started to do my first model
• 25:16
  of Bitcoin even before buying Bitcoin, 12 years of Eastern and
• 25:20
  2nd. What happened?
• 25:21
  You know, this big breakthrough that Bitcoin was actually a
• 25:25
  power law, a direct power law between price and time up in
• 25:29
  2018. And I posted on Reddit because,
• 25:33
  you know, different from other scientists, because there are
• 25:36
  other physicists that actually write physics papers on the con.
• 25:41
  It's in my website. If you go on my website, I have
• 25:44
  actually a list of these papers and some of them were very close
• 25:48
  to find exactly the same things that I found, but I found them
• 25:52
  before them. But instead of publishing on a
• 25:54
  scientific paper that eventually I'm going to do because I'm
• 25:58
  writing actually right now a real paper on this theory that I
• 26:02
  want to send to a journal. But you know, I did it on
• 26:06
  Reddit, I read it on Reddit, I did it on Facebook, I read it, I
• 26:10
  did it on the social media because I want to interact with
• 26:12
  other bitcoiners at the end, want just to publish and nobody
• 26:16
  reads it. I wanted to interact with the
• 26:17
  public with it all because like sharing my information with
• 26:21
  other bitcoiners and I posted on 2018 this Reddit post where I
• 26:28
  show that the trajectory, the general trajectory of Bitcoin,
• 26:32
  so price versus time is a power law.
• 26:35
  And so I, these are another things where many people don't
• 26:38
  know I have five years of what is called out of sample.
• 26:41
  So when I make a prediction, you know, I say I'm going to make a
• 26:44
  prediction. I already made the prediction
• 26:46
  for five years and I've been right for five years, OK, in in
• 26:50
  the sense that the coin as follows this general path that
• 26:54
  I'm describing. So I have a really track record
• 26:57
  and it's almost unheard of because almost nobody makes
• 27:01
  predictions five years ahead about anything, right In
• 27:04
  particular stock, you know, kind of assets type of things.
• 27:07
  Now what happened? Plan B saw this act.
• 27:11
  So this post, I know for many reasons why because he told me,
• 27:16
  he kind of told me and 2nd, I talked with him and 2nd, this
• 27:22
  idea of using power law is not something common in finance and
• 27:25
  he has a finance of the ground. In fact, many finance people
• 27:29
  don't even understand it. They don't have the tools to
• 27:31
  understand it. I talk with them, I can see how
• 27:35
  they talk about it. They don't understand the basis
• 27:37
  of it. So he took idea and he changed
• 27:40
  it where he introduced this new quantity called S2F instead of
• 27:45
  doing a direct relationship between price and time.
• 27:48
  It is the beauty of a model because it's simple.
• 27:51
  That is a beautiful thing. That is why for me was a
• 27:53
  breakthrough, because you don't need to introduce anything else
• 27:56
  now. You can go back and say where
• 27:59
  this derives, You know, what are the causes for this interaction
• 28:03
  between price and time. But the beauty, it's a simple
• 28:06
  relationship. He made it more complicated
• 28:09
  maybe because he was trying to find out the 'cause that is a
• 28:12
  noble thing. He did a good thing.
• 28:14
  He did a what the scientist will do the first effort in trying to
• 28:18
  understand A cause with a 'cause right, a causative link between
• 28:23
  the price and the time. So he thought maybe is stock to
• 28:27
  flow. Where did he get stock to flow?
• 28:29
  He got it from the Bitcoin standard.
• 28:32
  OK, so he kind of try to put together my idea in 2018 and
• 28:38
  what with coin standard says with S stock to flow is a big
• 28:42
  deal for things like gold, silver, and he thought maybe
• 28:46
  it's a big deal for Bitcoin. This is what plan before the
• 28:49
  problem with that is stock to flow.
• 28:52
  It's a horrible measure for Bitcoin.
• 28:54
  It's a horrible measure because the supply grows in a very
• 28:58
  predictive way. It's a it's an equation.
• 29:02
  It grows, you know, in fact, before Alving, before the 1st
• 29:06
  Alving, the supply grows directly with time.
• 29:10
  So it's kind of a function of time and and then we are the
• 29:14
  Alving. So his idea was because we are
• 29:17
  decreasing the amount of Bitcoin available, the price will jump.
• 29:22
  But if you go and look at the data, you look at issuance and
• 29:27
  now issuance relate to price, there is absolutely no
• 29:30
  relationship. It's 00 relationship and there
• 29:33
  are many reasons for that. One of the reasons is that the
• 29:37
  issuance itself, how many bitcoins are produced, it's a
• 29:41
  drop in the ocean in comparison with how many bitcoins are moved
• 29:45
  every day in the market. So it doesn't matter if you
• 29:49
  reduce it by a factor of two, it does almost no impact at all.
• 29:53
  I can show you a graph and you know, if I, if I found in my
• 29:55
  slides where I can show you the volume, but imagine this, right,
• 29:59
  the volume is over there, you know, like here, like I draw a
• 30:03
  line volume versus time. And then here below almost like
• 30:08
  100 times less is where the issuance is.
• 30:11
  How many issuance means how many bitcoins are produced?
• 30:15
  So imagine you have this Amazon River and then you have a like
• 30:18
  little Little River or 100 times smaller that contributes, you
• 30:24
  know, to this big river, but it's 100 times smaller.
• 30:28
  Now you say, hey, this small river, the flow of this river
• 30:32
  went down by a factor of two. Who cares?
• 30:35
  You know, it doesn't go to make a difference.
• 30:37
  So it's a theoretical idea of using S2F was a good attempt
• 30:42
  because it's great to try to find the causes of this
• 30:45
  relationship, right? But he went in the wrong
• 30:49
  direction and and then he created this model that are more
• 30:53
  problems with S2F. The fact that really it depends
• 30:57
  on these jumps, right? It depends on the jump that are
• 31:00
  only a big time. When he actually published his
• 31:03
  first article, we had only two jumps.
• 31:06
  So he used two jumps to justify this relationship between Price
• 31:11
  and S2F. It's ridiculous from a
• 31:13
  mathematical point of view. It's absurd because you cannot
• 31:16
  really determine anything from 2 jumps.
• 31:19
  OK, But it turns out that mathematically, if you create an
• 31:24
  illusion of correlation, and I wrote entire papers on this and
• 31:28
  I can like for example, I use random noise instead of issues,
• 31:32
  instead of coins. I say, OK, let's substitute the
• 31:36
  number of produce of the coin produced with complete noise,
• 31:39
  just random noise. And I have a beautiful graph
• 31:43
  that matches it almost 100% S to F with noise.
• 31:49
  Then I did it. People were not convinced.
• 31:51
  They say, well, maybe, you know, if you work with the noise means
• 31:55
  he works with everything. OK, So I went and they got
• 31:58
  soccer prizes like every four years where is the World Cup?
• 32:02
  And the price goes up by a certain amount.
• 32:05
  I have a table again. I've wrote a Medium article
• 32:07
  about that. I use these prices and I use
• 32:10
  them instead of the alding. OK, so arbitrary time instead of
• 32:16
  being the Alding, but it happens every four years.
• 32:18
  And again, I have a beautiful S2F mode.
• 32:20
  It works with anything. I took the issuance of Bitcoin,
• 32:24
  the price of Doge. I put them together, I get an
• 32:27
  S2F for DOGE using the issuance of Bitcoin.
• 32:31
  I can do it the other way around.
• 32:33
  I can take, you know, it doesn't work.
• 32:35
  It's crap. I don't I don't know how to
• 32:38
  explain it. Today I saw a pause from Plan B.
• 32:42
  He blocked me on a certain point and he has like 5000 people
• 32:46
  liking this stuff. You're lacking a ghost.
• 32:49
  You're lacking something that doesn't work.
• 32:51
  It's literally trash. I don't know what else to tell.
• 32:55
  It makes me sad because it's not me being jealous of Plan B if he
• 32:59
  was Like when there are analysts that says they do good work, I
• 33:04
  am the first one to say fantastic work, amazing
• 33:08
  beautiful because I am a scientist.
• 33:09
  I love when people explore Bitcoin, which is the love of my
• 33:13
  life and the subject of my studies, so I appreciate them
• 33:18
  discovering, exploring, you know, more things we know about
• 33:21
  Bitcoin. Wonderful it is.
• 33:22
  I'm very upset with Plan B because he's selling literally
• 33:27
  because he makes money through YouTube.
• 33:30
  But you know, he has a million people following him on Twitter
• 33:33
  by selling trash, you know, and he knows it trash.
• 33:36
  He knows because he has enough information from my interaction
• 33:39
  with him or the people telling him he blocks anybody that
• 33:43
  contradicts him, you know, so This is why I'm so mad about his
• 33:47
  model, you know, and I actually I want to be even more mad
• 33:49
  because there are too many people they got hurt by this
• 33:53
  absurd model that is, it doesn't have any information.
• 33:56
  It doesn't have any predictive power because it's based on an
• 33:59
  illusion, an illusion between there is a correlation between
• 34:02
  stock to flow and price and it doesn't exist the the data
• 34:07
  shows. So you know, so I'm sorry for
• 34:09
  this rant, but you know, as a scientist, I'm also upset when
• 34:14
  somebody's selling trash, you know, and is telling this is
• 34:19
  what Bitcoin does. It does.
• 34:20
  It's not. It doesn't have anything to do
• 34:23
  with Bitcoin. No, I, I think, I think it's
• 34:26
  really important that you said that 'cause, you know, Plan B
• 34:28
  does have an enormous following and a lot of people are buying
• 34:33
  or a lot of people believe in the stock to flow model.
• 34:35
  I'm, I'm just observer and just kind of, you know, make content
• 34:38
  and just kind of observe, but everything's going The general
• 34:42
  idea is I know that, you know, Bitcoin will go up over time.
• 34:45
  Now, one of the things that I wanted to talk about Giovanni,
• 34:48
  because, you know, if this theory is correct, it's really
• 34:52
  fascinating because in a way that allows you to predict the
• 34:57
  ups and downs of Bitcoin in a way.
• 35:01
  Here is one of these websites that I found Bitcoin Fair Price
• 35:05
  Calculator and it's based on, you know, the power law stuff
• 35:10
  that you're talking about and you can just kind of put into
• 35:13
  the future. So the end of 2025 and put in
• 35:18
  the month and it will give you the fair price of Bitcoin which
• 35:21
  is $120,000 which is you know the fair price and then the
• 35:27
  bottom price is about. Yeah, I, I didn't, I didn't make
• 35:31
  it. So I'm not sure 100% of the
• 35:35
  authenticity of the calculation. We can double check it, but it's
• 35:39
  great with other people have contributions, you know, and
• 35:43
  they are exploring because that is the entire point, right?
• 35:49
  When you do science, you can actually verify yourself.
• 35:54
  And it should be all about this. It should not be about trusting
• 36:00
  somebody like, you know, trusting me because I have a
• 36:02
  PhD. No, science is the contrary.
• 36:05
  The science is all about. OK, here I'm sharing this piece
• 36:09
  of information. I found this.
• 36:11
  Why don't you verify and the beauty differently from S to F?
• 36:15
  It is a complicated model because it's based on two or
• 36:18
  three steps and nobody beside you know, I spend a lot of time
• 36:22
  studying it. Many people don't, you know, but
• 36:25
  with the power law, everybody can verify.
• 36:29
  It's very simple. I have tutorials where I show
• 36:31
  how to do it. You can take the data, download
• 36:34
  it and you know from online and then draw.
• 36:37
  If you know how to use Excel, you can verify, you can look at
• 36:40
  that, you can download price and time and you can make that
• 36:44
  beautiful straight line. You know, this is just to show
• 36:47
  to your viewers. Let's show a chart that I made
• 36:52
  and then I can tell you about prediction, about where we are
• 36:55
  going and stuff like that. OK, so let me show you a more
• 36:58
  direct chart. So, for example, we can look at
• 37:01
  this, this chart that is actually was made by another
• 37:05
  person with Explorer, this power law.
• 37:07
  His name is Berger. He took my ready post.
• 37:10
  He gave me credit that you know, then he made it popular for some
• 37:15
  time people thought that actually that he was the author
• 37:18
  of the power law. But the beauty of this chart is
• 37:21
  that in the blue you can see where is more the model that he
• 37:28
  was based on my ready post. He reproduced it.
• 37:31
  You know, that is the beautiful thing.
• 37:33
  He was one of the few people that actually went got the data
• 37:36
  and reproduce the model and the beauty of it.
• 37:39
  Taste vector. It's very simple to recreate.
• 37:41
  OK, so the, the the critical thing now you reproduce this
• 37:47
  behavior because it's not really a model.
• 37:50
  It's a model is when you actually have some idea in mind
• 37:54
  of how something works. And then you do all these steps
• 37:58
  and you explain your, the observer behavior through these
• 38:03
  steps here. The only step I did was
• 38:06
  something that we do all the time in physics that is showing
• 38:10
  a quantity that it's a little bit more complicated than just a
• 38:15
  simple straight line. Even if a straight line, it's a
• 38:18
  power law. And the way to reveal that
• 38:21
  you're dealing with something that is AY equal X to some power
• 38:26
  is to do this graph. It is an unusual graph for many
• 38:30
  people because it's usual maybe to take the log of AY axis, but
• 38:38
  it's unusual to take the log of X axis in particular when the X
• 38:42
  axis is time. The beauty of doing it in that
• 38:46
  way though is that see if you do it in the normal way, like a
• 38:51
  clotting. So maybe we can start from there
• 38:54
  to give you a feeling of how we discover the power law and and
• 38:58
  what is the significance of the power law.
• 39:01
  So you see this graph that I'm showing, this is a typical graph
• 39:05
  that they usually show on TV because we want to put down
• 39:09
  Bitcoin, You know, like on CNBC or other financial news, they
• 39:15
  want to denigrate Bitcoin and the way they do it, they show
• 39:18
  this chart and this chart is linear, just the normal price on
• 39:23
  the X axis, sorry on the Y axis and then time the normal days,
• 39:29
  right, This case days, it could be dates or whatever in the X
• 39:32
  axis. When you do it in that way,
• 39:35
  Bitcoin looks very disorganized. It looks very crazy, right?
• 39:39
  The price goes up very much during the bubble, it went all
• 39:43
  the way to 65, almost 76,000, then it dropped to 16.
• 39:48
  So this big volatility ish, it's really up shown up in this
• 39:54
  graph, right? And it becomes kind of a signal.
• 39:57
  The signal here is Bitcoin. It's crazy.
• 40:01
  It's doing all these changes. It's not something reliable.
• 40:05
  You should not invest in it, right?
• 40:07
  So this is the message with the normal press, the normal media
• 40:11
  gives to people. It is a stupid message because
• 40:14
  this is not a signal. It's the noise.
• 40:16
  This huge, big variation in price are the noise now.
• 40:20
  It's true that. In general, you see a growth,
• 40:23
  right? It goes up.
• 40:24
  But by this graph you will not even know if it is really
• 40:27
  growing. You will think that is simply
• 40:30
  changing up and down like crazy, right?
• 40:33
  Then this graph is a little bit more common.
• 40:36
  And so forget about the rainbow, forget the straight line, you
• 40:39
  know the curved line in the middle, the asterisk are of the
• 40:44
  Alving. But you see it now by taking the
• 40:48
  log of AY axis. And what is a log log?
• 40:52
  Basically it's a very simple function, right?
• 40:54
  Sorry if you go in the math details, but basically it's a
• 40:57
  function where if I express numbers with these what is
• 41:04
  called the scientific notation. So I've write 10 as 10 to the
• 41:08
  one. I've write 100 as 10 to the two,
• 41:11
  right? Because it's 10 * 10.
• 41:13
  Then 1000 is 10 to the three, 10,010 to the four, right?
• 41:17
  The beauty of doing it in that way is that now you have this
• 41:20
  exponent and the exponent represent what is called the
• 41:24
  scale, scale of order of magnitude.
• 41:28
  And the log, what the log does if you put in like almost like a
• 41:32
  box, right? I put in in this box a number
• 41:35
  and it spits out an answer. Now the answer is this point.
• 41:40
  So if I put in in the log 10 it gives me one because 10 is 10 to
• 41:45
  the one. If I put in hundred that is 10
• 41:49
  to the two the log gives ME3. If I put 10 to the three that is
• 41:53
  1000, the log gives ME3, right? And you can see here in the Y
• 41:57
  axis I did that. I am using the log 10 to the -1
• 42:01
  by way means 1 / 10. So it's a fraction of a dollar.
• 42:05
  This when the coin was a fraction of a dollar and then
• 42:08
  zero is $1.00, one is $10, two is 100 and so on, right?
• 42:14
  You get the gest. The beauty of doing it in that
• 42:17
  way is that almost now we are flying with a drone or with an
• 42:22
  airplane above the forest. Instead of seeing these huge big
• 42:26
  trees, you know all these details of a noise, we are
• 42:30
  looking at the signal. We are looking.
• 42:32
  We have an overall picture of Bitcoin growth over its entire
• 42:38
  history. You see when I when I add this
• 42:40
  graph, the early history was almost hidden because the price
• 42:44
  was so small relatively to the latest price that look flat.
• 42:48
  But by taking the log, you're able to look at the entire
• 42:55
  forest and look at the entire growth of Bitcoin in terms of
• 42:59
  what is called scale. Because one of the most
• 43:02
  important concept in understanding power laws is this
• 43:06
  idea of scale. So you're looking at Bitcoin
• 43:08
  when he was a little baby, when he was a teenager, when he was
• 43:12
  a, you know, a grown man and so on and so on and so on.
• 43:15
  So in this growth, now you see by taking this look is much more
• 43:21
  organized. It's almost like a signal is
• 43:23
  coming out and it's telling you that these bubbles are not
• 43:27
  really where we should put the attention.
• 43:29
  We should put our attention in this general growth.
• 43:34
  Now this general growth is not exponential because many people
• 43:38
  want an exponential growth for Bitcoin because they think
• 43:42
  exponential is very fast. It's going really harp really,
• 43:46
  really fast. And exponential in a growth in a
• 43:49
  graph like this, it is called log linear because it's log in
• 43:53
  the Y axis and linear in the X axis will look like a straight
• 43:57
  line. And you can see the coin is not
• 44:00
  a straight line such a graph. So it's not an exponential.
• 44:03
  And this is not their kind of strike against S2F because S2F,
• 44:09
  if you look, if you understand it, then you look at the map,
• 44:12
  it's supposed to be exponential. And so if you, if Bitcoin was
• 44:16
  following S2F, we will see a straight line and we don't see a
• 44:20
  straight line. So it's another kind of mortal
• 44:24
  blow to S2F. The fact that we see a curve,
• 44:27
  now you get even a better pattern.
• 44:32
  In fact, a pattern of it is easier to understand because you
• 44:36
  know, a curve. It's reassuring, right?
• 44:38
  It seems that there is some very precise growth in Bitcoin is
• 44:42
  going somewhere. The fact that this curved down
• 44:46
  it mean doesn't mean that it's curving down because if you look
• 44:49
  at this graph, you see kind of tends to go up very, very fast,
• 44:52
  right? It's a kind of an artifact of
• 44:56
  this type of graph where anything that is not exponential
• 44:59
  is going to look bending down because it's basically losing
• 45:03
  ground relatively to an exponential of the same time.
• 45:08
  But it's still a very fast growth, right?
• 45:10
  Because we say already we kind of reveal it's really a power
• 45:14
  law with the power of six that is very fast.
• 45:17
  Now, the ultimate trick that we have in our arsenals as
• 45:21
  physicists and we try to understand a phenomena, we do
• 45:24
  these graphs all the time, right?
• 45:25
  We start with a linear graph, then we go to the log linear.
• 45:29
  And then if we don't see a precise pattern that we can
• 45:33
  recognize and the easiest pattern to recognize, it's a
• 45:36
  straight line. Human beings like straight line,
• 45:39
  we're kind of monkeys, you know, we're still monkey, me included.
• 45:42
  I am a big monkey. I like straight lines.
• 45:45
  Straight line are nice, you know, straight, easy to
• 45:48
  understand. So if you do this crazy
• 45:51
  transformation, it is you're taking the log of the prize and
• 45:55
  the log of time. That is something that you know,
• 45:58
  This is why I took all this time.
• 46:00
  Nobody did it for eight years, right?
• 46:03
  Seven years of history of Bitcoin when it was created
• 46:07
  2009, 2018, actually nine years, nine years of history.
• 46:12
  So it took nine years of history before somebody actually showed
• 46:15
  this graph. Then you see something crazy
• 46:19
  happened, right? It Bitcoin path, Bitcoin price
• 46:23
  is not anymore bent, but it's this beautiful linear growth,
• 46:30
  right? And it's not linear because we
• 46:33
  have to understand we are doing it in a log log space.
• 46:37
  It's actually a curve now though, it's a trick that we use
• 46:42
  that because if you see a straight line in a graph like
• 46:44
  this, it's a power law. We are trained to recognize
• 46:47
  immediately that there is some kind of relationship YY equal X
• 46:52
  to the north and the slope of this straight line in the
• 46:57
  middle. The straight line in the middle
• 46:59
  is kind of like a representation of this growth, right?
• 47:02
  It's a simplification. I know that it's not a perfect
• 47:06
  straight line because we still have a bubble.
• 47:08
  The bubble now are much more reduced in terms of size
• 47:12
  relatively to everything else. But you know, it goes up, it
• 47:15
  goes down, etcetera. You know, it's not a perfect
• 47:18
  straight line. Now I tell you that I have
• 47:21
  graphic I can show you where if I average the price.
• 47:24
  So imagine I have a moving window.
• 47:26
  I average the price every over four years.
• 47:29
  Now these bubbles almost disappear.
• 47:33
  And that price, it does became kind of like a little bit little
• 47:39
  bit WAVY line, but basically a line.
• 47:42
  But what that red line represents, it's what is called
• 47:45
  regression. It's a mathematical tool that we
• 47:48
  use where if you have a process like this with this, not exactly
• 47:51
  a perfect line, then you can say, well, can I simplify this
• 47:56
  behaviour with a line? And how much relying comes to a
• 48:00
  real representation of this behavior?
• 48:03
  And the answer is, so you get 3 pieces of, you get 3 numbers,
• 48:08
  one is the slope. And you do this.
• 48:10
  So basically you have an algorithm that tries to find a
• 48:14
  line that minimize the distance of all the points.
• 48:17
  It's a you can think about an average, you can think like a
• 48:22
  representation, like a, a simplification of this behavior.
• 48:26
  And so the algorithm gives you the slope, it gives you the Y
• 48:30
  intercept of that straight line. That is all what you need to
• 48:34
  identify a line. You need just two pieces of
• 48:36
  information, the slope and the Y intercept.
• 48:39
  And both of them have some significance that I will tell
• 48:42
  you in a moment. And then you get also a number
• 48:45
  that is called the R square. The R square is basically a
• 48:49
  measure of how well the behavior that you're observing is
• 48:53
  described by this line. And the answer is 0.95.
• 48:57
  If it was perfect, we will get one.
• 49:00
  So in this case, 0.95 means that this straight line, even as
• 49:06
  simple as it is, represents 95% of a behavior of Bitcoin.
• 49:12
  And so it's a pretty good model, right?
• 49:14
  If you have something that is supposed to represent 95% of
• 49:18
  what is going on with the price, it's a pretty good model.
• 49:20
  And you will object to say well, but what about this up and down?
• 49:23
  Well, we're up and down because we are up and down.
• 49:26
  Sometimes we're above, sometimes below.
• 49:28
  They kind of cancel each other. This why the straight line is a
• 49:31
  good representation. You sometimes you have a price
• 49:33
  below, sometimes above the cancel.
• 49:36
  It's almost like they don't exist.
• 49:40
  And so the slope, when it's 5.7 something, it's close to six.
• 49:48
  And the intercept is a small number.
• 49:51
  And so we can write an equation like this that represents what
• 49:56
  Bitcoin then is. It's the price 10 to the -17
• 50:02
  that is the Y intercept, right? You can do a simple
• 50:05
  transformation and show that you go from a straight line to this
• 50:08
  equation. It's a use the log property to
• 50:12
  show that this is what the real relationship between these two
• 50:16
  quantities. It's a price equal 10 to the
• 50:18
  -17. We get this from the Y intercept
• 50:22
  the days. How much time is passed from
• 50:25
  when the coin was created to this power.
• 50:28
  You know this number, it is close to seven.
• 50:31
  Now this number can vary a little bit.
• 50:33
  It depends where you calculated. If you calculated close to a
• 50:37
  top, if you calculated when you're close to a bottom, it
• 50:40
  doesn't matter because you get very, very similar results,
• 50:43
  right. And you can show that over time
• 50:45
  with number stabilizes because really probably there is a real
• 50:49
  number. But because of the influence of
• 50:52
  the bubble influence of the bottom, it gets changed a little
• 50:55
  bit. But you can draw it over time
• 50:56
  and show that it oscillates over a very precise number.
• 51:00
  It's part of, you know, doing the calculation and set.
• 51:03
  Now there is something even more amazing that they can show you
• 51:07
  that really probably the real power law.
• 51:11
  I'm sorry for this. The real power law is this one.
• 51:18
  So if you go and actually say look at look, you know, I think
• 51:25
  there is 2 signals, there is a general trend of Bitcoin.
• 51:30
  And then there is another signal that are these bubbles, they are
• 51:35
  interacting with each other. But these, they are kind of also
• 51:39
  separated in a way. And you say I want to focus on
• 51:43
  the general trend. So you have another mathematical
• 51:46
  method where basically you throw away anything that is too much
• 51:54
  of A deviation from the trend. And what turns out then in this
• 51:59
  way you get the blue dots, that is really the inliers, right?
• 52:03
  What are called the inliers. And the outliers are the black
• 52:07
  dots that are the bubbles. And then you can draw a line,
• 52:11
  you know, using regression to only the inliers with our the
• 52:16
  thoughts that are more closely flow following the trend.
• 52:20
  And it's almost scary. Look at the blue dots, how
• 52:24
  incredibly they are aligned with each other.
• 52:27
  So you see this why it's really not a model.
• 52:30
  It's just an observation of the behavior of Bitcoin.
• 52:34
  How can you deny what is the argument?
• 52:37
  How can you debate these? This is data, you know, this is
• 52:41
  what the data shows. And look what the data shows.
• 52:44
  It shows that we move along these blue dots in general and
• 52:49
  then once in a while, let's say in fact that once in a while is
• 52:53
  every two years. So it goes like this, a story if
• 52:56
  you want to give you the story of the corner and it goes like
• 52:58
  this. We spend 2 years at these
• 53:01
  bottoms if you want. It's not really a bottom.
• 53:04
  It's like a resist a support line where we still go up, right
• 53:09
  during these bear, bear market, we still got up.
• 53:13
  That is one of the beautiful conclusion by starting the data
• 53:18
  that we spend two years in what many people call the bear
• 53:22
  market, but we still go up with the power of 6.
• 53:25
  We spend 2 years along these blue dots.
• 53:28
  Then after the Alving, usually that happens after the Alving,
• 53:32
  we leave the bottom, we go up for a year and then we spend one
• 53:38
  year going down and they say it's almost like, you know this
• 53:42
  very good student that does everything right And then you
• 53:45
  know, it goes to Cancun and that's fine and it's OK.
• 53:48
  You know, it goes to Cancun it that's fine.
• 53:51
  The price goes up like crazy and then it crashes and it goes.
• 53:54
  Down so so Giovanni so let me ask you something is it going to
• 53:57
  continue that pattern of but you're saying that the
• 54:02
  oscillations are going to decrease right so the.
• 54:05
  And but in a sense, the, you know, this, what this graph
• 54:08
  shows is that the oscillation don't even matter because look
• 54:12
  at these, right? They almost cancel each other
• 54:14
  because you go up. Look at every single bubble,
• 54:17
  they go up, we go down. And it's almost like it didn't
• 54:21
  exist, right? You could have put up a bunch of
• 54:24
  blue dots along with red line. And the bubble is almost like
• 54:28
  they don't care. And, and notice how they the
• 54:33
  price goes down to that blue dot.
• 54:35
  How in the heck the price knows where to go back to?
• 54:40
  Yeah, something deep is happening here because it will
• 54:43
  not something that cannot happen by chance.
• 54:45
  It's not me drawing some crazy line or making up some stuff,
• 54:49
  but it's something deep there. Now, but I guess it's useful.
• 54:53
  And what's your question about why we can say that this is we
• 54:56
  continue, OK, because it's very deep important part of a theory.
• 55:02
  The fact is when you have a system like this that behaves in
• 55:06
  this way where the growth and let me go back to even this
• 55:11
  chart, right? So this is another way of
• 55:15
  expressing and showing the bubble as red at the top of the
• 55:18
  bubble the the bottom line like green etcetera.
• 55:22
  This type of behavior is called in physics scale invariant.
• 55:29
  What does it mean? Invariant is because the way
• 55:33
  that the scale is changing. So let's repeat one more time.
• 55:37
  What scale means? Scale means these changes in 10,
• 55:41
  so 1000 thousand. So if you focus on the growth of
• 55:47
  Bitcoin not in terms of a single dollar, but how the price change
• 55:52
  by a factors of 10, so 1000 thousand, then you notice
• 55:59
  something very precise. You can even do it by hand.
• 56:01
  You could take a table of prices and ask yourself, OK, the price
• 56:05
  was this, let me go up by a factor of 10.
• 56:09
  How long did it take for the price of 10 to happen?
• 56:13
  And you can make yourself a table, OK, It's something that
• 56:16
  you should do, like almost a sanity check.
• 56:19
  Everybody should verify instead of trusting me, you can do it.
• 56:23
  So you notice that as we go up by factor of 10 in price, it
• 56:29
  takes factors of 10 in time. And so the scale of price and
• 56:37
  the scale of time, they are proportional to each other.
• 56:41
  When that happens, we call it scaling variant.
• 56:45
  And the beauty of that is, and this is very universal, there
• 56:49
  are so many phenomena all around us in nature and social
• 56:54
  phenomena, they behave in this way.
• 56:57
  It means that doesn't matter how big the system was, it could be
• 57:01
  very, very little. Now, in the beginning, systems
• 57:03
  like these are very fragile. Like something can happen
• 57:06
  externally where you kill the system and then the system
• 57:09
  doesn't grow. But once it grows and it
• 57:12
  continues to grow, it continues to do it in a very regular
• 57:15
  fashion. And the regularity it's
• 57:18
  expressed by the straight line. So the straight line means it
• 57:21
  continues to do this growth by increasing the price in
• 57:26
  proportion to the increasing time.
• 57:29
  And it's something that is very inherent, very fundamental about
• 57:34
  a system because what happens, power laws are not created by
• 57:38
  chance. It is not something that this
• 57:39
  happens by chance. It's a very precise behavior.
• 57:42
  It means there is some kind of mechanism behind the growth of
• 57:46
  the system, in this case Bitcoin, that makes it behave in
• 57:50
  that way. And he makes it behave when he
• 57:52
  was like a little baby, like a little.
• 57:56
  In fact, we have a video, you know, if you go online on
• 57:59
  YouTube, we have a, you know, we have a YouTube channel where we
• 58:02
  make these very high production videos, made-up a video about
• 58:05
  scaling variants. And we use animals.
• 58:08
  We, we show actually. And you know, Bitcoin was so
• 58:11
  small in the beginning. If you go, you know, the early
• 58:14
  days when people didn't even really transact it using
• 58:19
  dollars, The first US dollar transaction was something like
• 58:24
  10,000 Bitcoin for $1.00. OK, crazy.
• 58:28
  So if you look at all these changes in time for Bitcoin is
• 58:32
  almost like Bitcoin, you know, like a initially was nothing.
• 58:36
  You know, because that equation that tell us how much Bitcoin
• 58:40
  was worth it nothing zero. Then after a few hours was like
• 58:44
  an atom after few days was a a mosquito.
• 58:48
  Then it took about 800 days to go all the way to the size of a
• 58:54
  rat. So if I we use this analogy
• 58:56
  where we say if $1.00 is 1K, then you know a rat relatively
• 59:03
  large rat will be 1K. And so I took about 800 days.
• 59:07
  And you can check actually historically when the coin
• 59:12
  really became $1.00, it took about 920 days.
• 59:15
  So the equation says 880 days. It really became a a dollar 930.
• 59:21
  So we were off by a few weeks. That equation is so precise.
• 59:26
  And then you know, today we are the size of a dinosaur.
• 59:31
  My son made this video where he he came up with a dinosaur.
• 59:35
  It is more or less the size of what Bikoni.
• 59:38
  So we went all the way from the atom to something that is as big
• 59:43
  as a dinosaur, right. And when Bikoni will be
• 59:46
  $1,000,000. And the beauty of this equation
• 59:48
  is that we can extrapolate and we can say when is going to be
• 59:52
  $1,000,000. So 10 years from now, Bitcoin
• 59:55
  will be Godzilla. And it did it in the same
• 59:59
  regular fashion. And that is, you know, if you
• 1:00:02
  calculate, even if you just use exchanges or you know, you go
• 1:00:06
  all the way to like the first USD transaction, we're talking
• 1:00:09
  about 8 order of magnitude. That means basically if you want
• 1:00:14
  to translate it in more simple language.
• 1:00:16
  Bitcoin went through 100 million times transformation.
• 1:00:21
  It multiplied itself by a factor of 100 million.
• 1:00:26
  That is how crazy this thing is, OK.
• 1:00:28
  And so if you did it in this way, I'm asking you this
• 1:00:30
  question. If you have something, imagine
• 1:00:33
  you're studying some animals, some phenomena that in 15 years
• 1:00:37
  grew up by a factor 100 million, and he did it in this very crazy
• 1:00:42
  regular fashion. Do you think that growing
• 1:00:45
  another factor of 10 with that you know when Bekon is a medium,
• 1:00:49
  will he do it in a different way or he will follow what he did
• 1:00:53
  for 15 years and eight order of magnitude?
• 1:00:56
  No, clearly, I mean clearly it it's it's, you know, according
• 1:01:01
  to your data. And again, I just want to
• 1:01:02
  emphasize a lot of this goes over my head.
• 1:01:04
  I don't have a background in this.
• 1:01:05
  I'm a media guy, but just based on, you know, the graph and just
• 1:01:10
  based on, you know, the research that you've done and you've put
• 1:01:13
  together, it clearly seems like there is a correlation right
• 1:01:17
  now. Mike, my question for you,
• 1:01:19
  Giovanni, is if this is so predictable, wouldn't this allow
• 1:01:24
  you to trade in a way like wouldn't this allow you to, if
• 1:01:28
  you can anticipate where the next bubble is coming and have
• 1:01:34
  an estimation of where that bubble is going to peek at,
• 1:01:39
  isn't that, wouldn't that give you a advantage?
• 1:01:42
  Wouldn't that give you a trading advantage?
• 1:01:44
  In terms of. Going into the next cycle.
• 1:01:47
  Absolutely because I, I on top of the predictability of the
• 1:01:50
  overall trend, right, because we say it's almost like there are
• 1:01:53
  two signals. There are the bubbles and there
• 1:01:55
  is the overall trend, but also so, and sometimes people dismiss
• 1:02:00
  the power of the predictability power of the power law saying
• 1:02:04
  well, you know, but because of these bubbles, the price could
• 1:02:07
  be anywhere, anytime around that curve.
• 1:02:10
  So what is the big deal? Well, first of all, it's a big
• 1:02:13
  deal because if I can tell you 10 years in advance with Bitcoin
• 1:02:17
  in 2032 is going to be $1,000,000.
• 1:02:21
  It's a big deal, right? Because it tell us, it gives us
• 1:02:23
  a sense of how long it's going to take, you know, for Bitcoin,
• 1:02:27
  just to give you a feeling, because of this power of 6, if
• 1:02:30
  you double the time of Bitcoin existence with this 15 years,
• 1:02:35
  you double, you take the power of 6, you get 64.
• 1:02:38
  So in another 15 years we are going to get 64 times whatever
• 1:02:43
  Bitcoin value is, right? Something on the order of $4
• 1:02:46
  million close to that. In 15 years.
• 1:02:50
  Specifically, yeah, because specifically because it's easy
• 1:02:53
  to calculate, right? You, you double the time coin
• 1:02:56
  has existed for 15 years. You double it.
• 1:02:59
  You can use that power and say, OK, two to A6 to a six is 64,
• 1:03:05
  right? So you get 6433 time.
• 1:03:09
  If you triple it, so you wait another 30 years, you get 720,
• 1:03:14
  right? Is how crazy these powers are
• 1:03:16
  because it's nonlinear, right? You would think, oh, you know,
• 1:03:19
  I, I triple, I get, you know, three times more.
• 1:03:22
  No, it's 720 times more. It's visible beauty of having
• 1:03:26
  powers, you know, they are powerful.
• 1:03:29
  Now, on top of that signal, that is a general trend.
• 1:03:35
  We also get these oscillations. Now the oscillations and the
• 1:03:40
  problem with this oscillation, but we have only three of them.
• 1:03:43
  So, you know, we have to be a little bit more careful with the
• 1:03:46
  power law. We have thousands and thousands
• 1:03:48
  of data points. So the statistics are crazy.
• 1:03:51
  You know, it's almost, it's, you know, there is this
• 1:03:55
  mathematician, I don't know if you follow him.
• 1:03:57
  It's called Fred Krueger. He's also.
• 1:03:59
  Yeah, Fred. Fred's great.
• 1:04:00
  I've had him on the show before. Yeah, he's a, he's a a power law
• 1:04:04
  fanatic, very strong supporter of the power law because he's a
• 1:04:08
  mathematician. He understands.
• 1:04:10
  He understands the significance. He says this power law is as
• 1:04:14
  likely to be due to chance as you dropping a penny from the
• 1:04:19
  Empire State Building. And the penny fall falls inside
• 1:04:24
  the Dixie cap of the bottom of a tower, right?
• 1:04:27
  So you can imagine how difficult that is.
• 1:04:29
  And you say that is how likely with this power law is due to
• 1:04:34
  chance. OK.
• 1:04:35
  It's anybody that knows a little bit of math.
• 1:04:38
  Freddie's, you know, he has a PhD math from Stanford.
• 1:04:41
  He worked for many years as one of these quants with the, you
• 1:04:45
  know, mathematician, physicist at work for Wall Street, made a
• 1:04:50
  ton of money. You know, he knows his stuff and
• 1:04:52
  immediately recognized when he saw the graph that I was showing
• 1:04:56
  him for days and days. I was trying to get his
• 1:04:58
  attention. He finally say Bitcoin is on an
• 1:05:01
  unstoppable power law train. It's evident he knows.
• 1:05:05
  He knows and he did a lot of verification.
• 1:05:07
  He did this on calculation, reproduce the result.
• 1:05:09
  I'm glad because this is what you want as a scientist.
• 1:05:12
  So you really want other people come in and verify your stuff
• 1:05:15
  because you are the first one to put it in doubt.
• 1:05:18
  OK. But in on top of this very
• 1:05:21
  precise general trend, we have also this very precise
• 1:05:25
  oscillations. They are not due to.
• 1:05:28
  They are not random. Also for whatever reason they
• 1:05:32
  follow very precise 4 years patterns.
• 1:05:34
  You can identify them, you can identify them as deviation from
• 1:05:38
  the trend. Like for example in these
• 1:05:40
  graphics are showing I'm showing percentage difference in from
• 1:05:45
  the power law trend. And so you can color code it and
• 1:05:48
  say, well, when I have a certain big difference in the price, in
• 1:05:53
  the price relatively to the trend, I am in an area where,
• 1:05:58
  you know, I'm close to the top. When I have big deviations in
• 1:06:02
  the other directions, we are negative, negative because we
• 1:06:05
  are below the trend. Then I am in an area where the
• 1:06:09
  price is undervalued. And so it's a good place where
• 1:06:13
  to buy. So if you want to do so, how can
• 1:06:15
  you use this information? Because we always say it's like
• 1:06:19
  we have a science, but you know, science is cool and it's
• 1:06:22
  amazing. You don't need always to have a
• 1:06:24
  technology. Like you know, when you study a
• 1:06:26
  black hole, maybe, you know, 203 hundred, 1000 years from now,
• 1:06:29
  we're going to have black hole, black hole technology where we
• 1:06:33
  travel to war malls and say that, but we are not there yet,
• 1:06:36
  right? It was study because we want you
• 1:06:38
  are fascinated. We want to understand the
• 1:06:40
  universe. So we could stop here and say,
• 1:06:42
  hey, it's great to know what we coined those and the science
• 1:06:45
  behind, but you know, we actually can use technology and
• 1:06:49
  we can use technology to do things like what do we want to
• 1:06:53
  do as Bitcoin? We would like to have more
• 1:06:55
  Bitcoin I that is a goal. So if your goal is to multiply
• 1:06:58
  your Bitcoin, you can use this knowledge.
• 1:07:00
  I'm going to use it. I have a community of about 500
• 1:07:04
  people. I have a Discord channel that
• 1:07:06
  people can join, you know, your listeners if you want to join
• 1:07:09
  our Discord channel. And we have indicators that we
• 1:07:13
  develop because we want to use this knowledge to create that
• 1:07:16
  technology. And the technologies, if you
• 1:07:18
  combine the power law with the knowledge of the cycles, they
• 1:07:22
  are related but distinct things, but you can put them together,
• 1:07:26
  then you have almost surgical precision in where these bottoms
• 1:07:33
  and tops are. And then what do you do?
• 1:07:35
  Well, it depends on your style. OK.
• 1:07:37
  And here is a little bit delicate thing because some
• 1:07:40
  people are very strong oddler and we always a Marvin because
• 1:07:45
  it's really the simplest possible thing, right.
• 1:07:47
  If you're a huddler, you know, glory to you, you are not doing
• 1:07:51
  anything wrong. But it's not the ideal approach
• 1:07:54
  in the sense that if you study Bitcoin, if you are careful, if
• 1:07:58
  you are not a degen, if you are very aware of what you're doing,
• 1:08:03
  you can use with moderation this knowledge to maybe multiply your
• 1:08:08
  Bitcoin. So one thing that you could do,
• 1:08:10
  for example, it's buying at the bottom and selling at the top.
• 1:08:16
  Now are you going to sell all your Bitcoin?
• 1:08:18
  No. What about 10%?
• 1:08:20
  Maybe you take a little bit of gains, 10% when you're close to
• 1:08:25
  the top and then you rebuy at the bottom, right?
• 1:08:28
  You put aside, you're not going to buy stupid things with this
• 1:08:31
  money that you saw it, you know you got from selling Bitcoin and
• 1:08:35
  then you go and buy back at the bottom and you can multiply.
• 1:08:38
  Now I did a calculation where instead of 64, remember I told
• 1:08:42
  you if you just although you get 64, if you play correctly, this
• 1:08:48
  we call it riding the waves, riding the Bitcoin waves.
• 1:08:52
  So if you play this Bitcoin waves riders game and I'm giving
• 1:08:59
  you the idea situation. So none, none of us are going to
• 1:09:03
  get the idea situation. But just as a point of
• 1:09:05
  reference, you get 1000, 200 in 15 years, you're multiplying
• 1:09:12
  your gains by 1200. So you go from 64 to 1200.
• 1:09:17
  Now nobody's going to do 1200 because it's an ideal case where
• 1:09:21
  you perfectly sell at the top, perfectly buy at the bottom.
• 1:09:25
  So, you know, use our inefficiency of 50%.
• 1:09:30
  So maybe you get 600 times or maybe 70%, right?
• 1:09:35
  So it's going to be at least 203 hundred times there.
• 1:09:39
  So 64 if you if you do this. And so again, don't do with all
• 1:09:44
  your Bitcoin, just do it with a little bit, right?
• 1:09:46
  And let the other Bitcoin run, you know, and then rebalance
• 1:09:49
  your portfolio. So if you, if we miss the top
• 1:09:53
  and we go even higher, then when you have related answer, it is
• 1:09:57
  going down because of these tools allow you to know that
• 1:10:01
  we're going down from the top, then sell a little bit more,
• 1:10:05
  right? And you make even more money and
• 1:10:06
  then you buy again at the bottom.
• 1:10:08
  The bottoms are really our strength because, you know, we
• 1:10:12
  we can really determine and I can show you some charts.
• 1:10:16
  You know, we have these indicators, for example, that we
• 1:10:18
  develop where we are very, very precise with the buttons.
• 1:10:22
  You know, it's, it's really where the theory shines because
• 1:10:27
  there are, you know, reasons, you know, like we we did find
• 1:10:30
  the causes. We know that has to do with the
• 1:10:32
  ashrae, with the miners. And you know, we have all this
• 1:10:38
  knowledge behind why we observe this phenomena.
• 1:10:42
  You know, it's a theory and people can read the theory in my
• 1:10:45
  website. I have medium articles, you
• 1:10:47
  know, I'm writing a book, etcetera.
• 1:10:49
  But the knowledge allows you to identify very correctly the
• 1:10:53
  bottoms. And again, it's not a question
• 1:10:55
  of, you know, you waiting for that particular day.
• 1:10:58
  It's a range, right? So when we are close to the
• 1:11:00
  bottom, you start to do more strong, strong DCA.
• 1:11:04
  So we call it weighted DCA. So let's say you want to save
• 1:11:08
  every month $100 and buy Bitcoin.
• 1:11:10
  Well, don't, don't buy the coin when we come close to the top,
• 1:11:13
  right? Wait, put it aside, wait until
• 1:11:16
  we go to the bottom. When we are a big bottom sell,
• 1:11:21
  you know you have how many chairs you have at home 3 sell 2
• 1:11:24
  chairs and buy more Bitcoin. You know this is the right time
• 1:11:27
  when to do it. If you can take a loan, get a
• 1:11:30
  loan. You know if you.
• 1:11:31
  So joining, joining, yeah. So what is let's, let's focus on
• 1:11:36
  the immediate term and then let's focus on 2030, right.
• 1:11:39
  So if we're using your model, what do you anticipate is gonna
• 1:11:43
  be the market top in 2025? So, OK, so this is where I need
• 1:11:50
  to make clarification, right? Because one thing is with
• 1:11:52
  general part that we think we got it and it's very strong is
• 1:11:57
  backed by all these idea of scaling variants etcetera.
• 1:12:00
  And then the other thing is trying to hide the knowledge of
• 1:12:06
  the cycles. Now there are two things.
• 1:12:08
  One is the timing and the timing if everything goes like before
• 1:12:15
  because that is the big if, right?
• 1:12:18
  If everything behaves like before and we don't know, but
• 1:12:22
  given that it has done it for three times, then we can kind of
• 1:12:28
  almost I don't I don't want to say the word guarantee because
• 1:12:31
  there is nothing guaranteed. But you know, we can follow this
• 1:12:35
  understanding, right? So I did this chart for example,
• 1:12:38
  you can see here where I took all the different cycles and I
• 1:12:45
  average them. And so this is what you see.
• 1:12:47
  Every dot represents a month. So you have every month is
• 1:12:52
  represented by one of these dots and the bars, the error bars
• 1:12:55
  these how you will do in a real scientific paper, right?
• 1:12:58
  You get the measurement, you tell how big your errors are.
• 1:13:01
  So the errors here represent the valuability of that dot
• 1:13:06
  relatively to all the all the data that you have.
• 1:13:08
  You have about every dot represents about 90 points
• 1:13:11
  because it's basically 30 days in that month for three cycles,
• 1:13:16
  so 90 points. And so you can see these bars
• 1:13:20
  sometimes are huge and sometimes small.
• 1:13:22
  Notice where we are the smallest.
• 1:13:24
  We are the smallest at the peak and at the bottom.
• 1:13:27
  It is great because if we want to do this, think of identifying
• 1:13:30
  the top and bottoms. That is exactly where we care
• 1:13:34
  right in a in a range. So we use we have this
• 1:13:37
  terminology. We we say it's like a clock,
• 1:13:40
  right? So we think if you think about
• 1:13:43
  four years been 12 hours, then in our terminology 0 or 12, it's
• 1:13:50
  the top, the historical top, basically the end of cycle
• 1:13:55
  around 3:00 is where you have the bottoms.
• 1:13:57
  So that is about one year after the top.
• 1:14:00
  So it takes about one year to go down and then we spend about two
• 1:14:03
  years here below the trend and then one other here to go to the
• 1:14:07
  top. Now it turns out that the real
• 1:14:11
  tops don't happen exactly at 12. They happen around year it's
• 1:14:16
  hour 11 and that is about two or three months before the end of
• 1:14:21
  the year. So if you want to translate all
• 1:14:23
  these in terms of very simple, practical, actionable
• 1:14:27
  information is we are going to start the bull run.
• 1:14:31
  So OK, I'm telling you the entire story from here to the
• 1:14:34
  next bottom. OK, ready.
• 1:14:36
  So right now we are about time 7:15.
• 1:14:41
  I did this a little bit a few days ago.
• 1:14:44
  So every every two days is a minute something like that.
• 1:14:47
  So we are about 7:15. This is where we are on the
• 1:14:50
  clock. Now the real bull is going to
• 1:14:53
  happen at our nine and that is going to happen in the end of
• 1:14:58
  year. And so probably because sometime
• 1:15:01
  you have it a little bit early, a little bit later.
• 1:15:03
  So we are not going to see the real bull until.
• 1:15:07
  Hour 9 and how long is that gonna last?
• 1:15:09
  So it's gonna be beginning at the end of the year.
• 1:15:12
  By the way, I agree with you. I don't have any of the
• 1:15:15
  mathematical backgrounds and whatever, just I've been in
• 1:15:18
  Bitcoin for eight years. So you, you tend to, yeah, I
• 1:15:21
  mean. It will not make sense, right?
• 1:15:22
  If we say something stupid and it was completely out of it,
• 1:15:27
  real, you know, you, you will tell me Giovanni, you're full of
• 1:15:29
  shit. And I it we just confirm a lot
• 1:15:33
  of things that many people say anyway, but we do it more
• 1:15:36
  rigorously. We give a stats we you know, we
• 1:15:39
  have a little bit more add to this because you know, we we do
• 1:15:43
  we introduce science like scientific method, like if you
• 1:15:46
  were trying to publish. Absolutely.
• 1:15:48
  So the the idea is that yeah, let me finish, let me tell you
• 1:15:53
  an entire story and then ask a bunch of questions.
• 1:15:54
  OK, It takes me literally 2 minutes.
• 1:15:57
  So we are going to have a full bull starting in October,
• 1:16:02
  November of this year. Price will go crazy.
• 1:16:06
  We will go up here along this line.
• 1:16:10
  It is about one year. So it takes one year to reach
• 1:16:13
  the top. So the top will be around
• 1:16:16
  September, October of 2025. Now people want to know what is
• 1:16:21
  the height of that top. So this is where I distinguish
• 1:16:25
  the precision of a cycle because you can see the starts here.
• 1:16:28
  These are how how precisely stats are the the the graph
• 1:16:34
  below shows how likely is that these pattern is due to chance.
• 1:16:38
  And these are logs that is 10 to the -80 So I basically says it's
• 1:16:43
  impossible it is due to chance. Where is a real pattern there.
• 1:16:46
  Now is the pattern going to repeat?
• 1:16:48
  We will see. But if it repeats, get ready for
• 1:16:53
  November when we are going to reach the peak.
• 1:16:55
  That is very strongly based on the statistics of the previous
• 1:16:59
  cycles. Now, what is the value now?
• 1:17:02
  That is where, because differently from holders, I will
• 1:17:06
  always tell you where the stats supports me and where they don't
• 1:17:11
  support me and where I'm trying my best with what I have.
• 1:17:15
  But as a scientist, I need to warn you that is a little bit
• 1:17:19
  weak as a as a calculation. So I have an article on Medium
• 1:17:24
  because I'm writing. OK.
• 1:17:25
  So hold on. Let me stop you right there.
• 1:17:27
  So let me just to clarify, right, seems like your model
• 1:17:30
  holds up very, very well on the downside other than the Black
• 1:17:35
  Swan event that we had because of the pandemic.
• 1:17:38
  Not actually vet one. Vet one was also verification of
• 1:17:41
  my, of a theory because in fact, I use it all the time as an
• 1:17:44
  example. I can even show you because it's
• 1:17:46
  great that you mention it, say, Oh, beside that, no, actually
• 1:17:50
  that one was a verification that we were right.
• 1:17:53
  Because let me give me just a second because it's kind of
• 1:17:56
  cool. It's like a punch line.
• 1:18:00
  If I I need to find it, let me just give me a second, but go
• 1:18:04
  ahead. I I follow what you're saying,
• 1:18:06
  but no, this is so exciting. And I'm and I'm learning so much
• 1:18:10
  and I'm trying to trying to soak all of this in.
• 1:18:13
  This is this is out of my area of expertise.
• 1:18:16
  So, OK, so your model holds true.
• 1:18:19
  For the downside, it's very accurate, but for the upside?
• 1:18:24
  Yeah. So let me let me interrupt you
• 1:18:26
  see this event at around 4200 because this.
• 1:18:31
  Yeah. Could you zoom in a little bit?
• 1:18:32
  Do you mind zooming in so everyone?
• 1:18:34
  Could me let me go and try to zoom in?
• 1:18:37
  It's on the bottom, yeah. Yeah.
• 1:18:39
  So if I see this, think here, this deep here.
• 1:18:44
  Yeah, that's the Black Swan. That's the code.
• 1:18:46
  That's. The you see, actually what
• 1:18:48
  happened, it went a little bit below and then it said, oh,
• 1:18:52
  fuck, I should not be here. Sorry for the bad word.
• 1:18:55
  Let me bounce back. You know, So actually that is
• 1:18:58
  what as in fact, I will use it in my paper and say, look at
• 1:19:01
  this. You know, for some reason the
• 1:19:03
  price knew that that was something that they cannot
• 1:19:07
  violate. And he went back, right.
• 1:19:09
  So it looks like even during the pandemic was almost like a
• 1:19:13
  stress test of a theory. The theory helped that there is
• 1:19:17
  some kind of crazy power law, unviable lying there.
• 1:19:22
  And even during the pandemic, we respected it.
• 1:19:25
  In fact, we were a little bit too bullish relatively to that
• 1:19:28
  trend. And then there was this
• 1:19:31
  correction. And the correction brought
• 1:19:33
  everything back to normal, you know.
• 1:19:35
  So let's go back with your question.
• 1:19:37
  Yeah. Let's go back to what we're
• 1:19:39
  initially just because and I'm I'm really glad that you brought
• 1:19:42
  that up. So the the upward, the upward
• 1:19:46
  trend, right. So it's November of 2025.
• 1:19:52
  Again, I don't have this type of background and whatever, but and
• 1:19:56
  I usually don't talk about speculation and any of this
• 1:19:59
  stuff but instinctively. I feel historically Bitcoin
• 1:20:04
  tends to peak 12 to 12 to 16 to 18 months after the halving.
• 1:20:08
  That's what I've, what I've noticed, that's what I've seen
• 1:20:11
  this cycle. There was a lot, there was this
• 1:20:13
  big theory of the left translated cycle, but it seems
• 1:20:16
  like it's not playing out because we're crabbing sideways
• 1:20:19
  like always happens, right? So, OK, so November of next year
• 1:20:25
  we start. And by the way, we are, we are
• 1:20:26
  moving along the power law, your graph where the power law is
• 1:20:30
  becoming like a resistance right now for the price.
• 1:20:33
  So OK, So what? What is?
• 1:20:35
  What is the cycle peak? And I and I know.
• 1:20:38
  That yeah. So, yeah, yeah.
• 1:20:40
  This is where as a scientist I have to make all these
• 1:20:44
  disclaimers and say, because, you know, this is what science
• 1:20:47
  teaches us, that we need to be honest and open with our data.
• 1:20:50
  So I wrote this article that people can read on Medium.
• 1:20:54
  You can also find it in my website.
• 1:20:56
  I'm going to use my website. It's called Bid poseidon.com.
• 1:21:00
  So everybody should go to my website to learn more because
• 1:21:05
  I'm putting there all the information.
• 1:21:06
  It's going to be kind of a hub for everything related to power
• 1:21:10
  law, and they can give you the link if you want to put it in.
• 1:21:12
  Your no, I put we've been putting it in the live chat for
• 1:21:15
  everybody. Yeah, so.
• 1:21:17
  That that in I've wrote this up because there was some time,
• 1:21:21
  some debate and some there is this guy, I think he's called
• 1:21:24
  Crypto University something. Bitcoin University.
• 1:21:28
  Yeah, no, I think this was a crypto university now different
• 1:21:33
  from Bitcoin universe, but yeah, that we call it calls it the 5.3
• 1:21:38
  theory. And then Peter Brand also was
• 1:21:42
  discussing basically the same idea.
• 1:21:43
  So they their claim was, oh, we are already reach a peak of
• 1:21:48
  70,000 said it's stupid, you know, and I explained why it's
• 1:21:52
  stupid. But if you follow the logic
• 1:21:56
  right, I've wrote this, these are medium articles called a
• 1:21:59
  scientific method to evaluate the size of a Bitcoin bubbles.
• 1:22:05
  OK, and explain my logic. It's all based on measuring the
• 1:22:09
  difference between all the different peaks from from the
• 1:22:13
  trend. And then we notice if we take
• 1:22:17
  all the bubbles and we plot them in terms of deviation from the
• 1:22:20
  trend, they also follow a pattern.
• 1:22:23
  Now want us to understand that is only three data points.
• 1:22:28
  If I try to publish a paper, a scientific paper with three data
• 1:22:33
  points, they will laugh at me. Now if information I.
• 1:22:36
  Understand they they will think that is stupid because there is
• 1:22:38
  nothing to support your case. But again, is part of what S2F
• 1:22:43
  does because of his entire model is based only on the bubble
• 1:22:47
  without only three. So it's ridiculous.
• 1:22:49
  But you don't do that. But given that it's a minor
• 1:22:54
  thing, you know, it's not that our entire model is based on
• 1:22:58
  these three data points. We only try to make a rough
• 1:23:01
  estimate of the size because it's not really important If we
• 1:23:04
  get the timing correct, it doesn't matter if it goes to 203
• 1:23:08
  hundred 500 all what we care is that during the time we are on
• 1:23:14
  alert to know that the price is going down and then we can do
• 1:23:18
  whatever we need to do. We stop buying if we are doing
• 1:23:20
  the CA or we sell a little bit to with the intention to buy
• 1:23:25
  back at the bottom. All these things.
• 1:23:27
  The timing is so much more important than the correct size
• 1:23:32
  of a bubble. OK, but if you follow the
• 1:23:35
  reasoning and say look, I know you is not scientific as I know
• 1:23:39
  it's not the best, but it sometimes is all what you do,
• 1:23:43
  right? We only have three data point
• 1:23:45
  can based on this three data point make a rough estimate of
• 1:23:49
  water sizes. Then what you do, you project
• 1:23:52
  that decay. So it looks like it's
• 1:23:55
  exponential that is exponential instead of being a power law,
• 1:23:59
  they they decrease of a bubble size.
• 1:24:01
  So they go down very fast and they estimate if you follow the
• 1:24:05
  logic of my article is that what we are going to get, it's about
• 1:24:11
  80% deviation from the trend of the next bubble and the trend of
• 1:24:16
  the time of a bubble, the trend will be about 120,000.
• 1:24:20
  So we're talking about something on the order of 2000, sorry,
• 1:24:25
  210,000 dollars, $120,000. And I like this approach because
• 1:24:32
  it's all based on using the information which we have,
• 1:24:35
  making an extrapolation. And also it's a very
• 1:24:40
  conservative estimation. Instead of pushing formal and
• 1:24:44
  telling people we are reaching 1,500,000, we are saying, look,
• 1:24:48
  if it looks like the bubbles are becoming smaller and smaller
• 1:24:52
  with time, if this continues, then this is what to expect.
• 1:24:57
  And if we go higher than that, I'm fine.
• 1:24:59
  I'm perfectly fine because it means that maybe this decay was
• 1:25:03
  not true. You know, maybe it's an illusion
• 1:25:05
  because it's only based on three points.
• 1:25:07
  You know this why you don't want to rely your statistics.
• 1:25:11
  And I just want to clarify for everyone.
• 1:25:13
  So the estimation is around 200 to 210,000, but there's no way
• 1:25:19
  to know the top. So that's just based on three
• 1:25:25
  data points, which is not enough data points.
• 1:25:27
  And you're basically coming to the conclusion that it's going
• 1:25:30
  to be around 200 to 210 to 220, but it could also go up to
• 1:25:36
  300,400 thousand. Yeah, etcetera because you know
• 1:25:41
  it's not really the core of theory, right.
• 1:25:43
  It's something it's like a nad's on that I'm doing saying OK,
• 1:25:47
  based on what we are observing. So there are these deviations.
• 1:25:50
  We seem to be regular. We don't know because to know,
• 1:25:54
  to claim regularity, we will need dozens of data points and
• 1:25:59
  we don't have dozens of cycles, you know, we have only three.
• 1:26:02
  So if you follow the logic and say look, let's look at the
• 1:26:06
  worst case scenario, right? I mean, it could be worse than
• 1:26:10
  that. It could be that it doesn't go
• 1:26:11
  anywhere, right? We don't know.
• 1:26:13
  But if it continues to do what it has done, if these cycles
• 1:26:18
  repeat like we were repeating if the deviations for whatever
• 1:26:22
  reason, I don't know because I need to understand why we get
• 1:26:26
  this deviation so regularly in terms of their decay.
• 1:26:30
  It's possible it is a function of how much money we have
• 1:26:34
  available because you know, one thing is to move, you know, an
• 1:26:37
  asset that has a market cap of few billion dollars and another
• 1:26:41
  one is moving a market cap with us.
• 1:26:44
  And you know, three, you know, almost $3 trillion by the time
• 1:26:48
  we arrive to this peak or $2 trillion with whatever it is.
• 1:26:53
  So it's much more difficult to move it.
• 1:26:55
  So is why we see the smaller bubble.
• 1:26:58
  Now. Maybe there is a very precise
• 1:26:59
  explanation of why this happens, right?
• 1:27:02
  And if that is true, then the conclusion is 200,000, you know,
• 1:27:07
  close to 200,000, it is still great, right?
• 1:27:09
  It's still amazing that we can go to that, but I don't exclude
• 1:27:13
  that we can go to 250 now. Larger and larger deviation from
• 1:27:17
  these values are going to be less and less likely, right?
• 1:27:20
  So 500,000 is much more difficult than 300,000.
• 1:27:25
  Based on the three data points that.
• 1:27:28
  Based on the three data points. Yeah, based on the three data
• 1:27:30
  points, OK, I'm understanding and I'm and I'm and I'm learning
• 1:27:32
  and I'm and I'm understanding your, the, the, the logic and,
• 1:27:35
  and where you're coming from. OK, this is fascinating.
• 1:27:38
  Now I think the question on everyone's mind and I'm going to
• 1:27:42
  use this calculator and just want to emphasize that Giovanni
• 1:27:44
  has not you know completely authenticated it.
• 1:27:50
  But I did run some of the numbers and on on the 15 year
• 1:27:53
  aspect and it seems like they were somewhat accurate.
• 1:27:57
  So 2040 roughly $4 million. So let's just extrapolate and
• 1:28:04
  move it to 2030. And according to this, the 2030
• 1:28:10
  price is going to be roughly half $1,000,000.
• 1:28:13
  Does that correlate with your data?
• 1:28:17
  Yeah, it looks right. It looks right.
• 1:28:19
  You know that could Betty and and remind everybody what that
• 1:28:23
  represents, right. Remember this is the trend,
• 1:28:26
  right. So it depends where we are and
• 1:28:28
  which day to be used in December.
• 1:28:30
  So right. So it's it's possible that is 38
• 1:28:38
  What what what is the date that's very small for?
• 1:28:41
  Me 12312030. 30 so right now 25 S if 29, so this will be
• 1:28:53
  actually cause the next So if we go for yes, right.
• 1:28:57
  So we have a top is going to be on the end of 25 S.
• 1:29:01
  The next one is going to be the next top is going to be after
• 1:29:06
  this one is going to be 29, right?
• 1:29:08
  So four years later. So 29th will be the next stop.
• 1:29:12
  So 30 it's basically one year later and this is about
• 1:29:16
  December. This will be the bottom, right?
• 1:29:17
  So this will be the bottom value kind of because I usually
• 1:29:22
  actually not even lower than that because usually the trend
• 1:29:26
  it's about two times like 60%. So whatever 60% is, we can even
• 1:29:31
  calculate what is the 60% of 500,000 close close to 250.
• 1:29:39
  Right, something. And that would be the bottom,
• 1:29:41
  you said. Yeah.
• 1:29:43
  So that is, yeah. So it's about actually 60%
• 1:29:51
  deviation that is so 200,200 thousand.
• 1:29:55
  So 200,000 is B is basically where and your view and this is
• 1:30:01
  telling you 410. No, no.
• 1:30:04
  And it says it. It says it right there.
• 1:30:05
  Look, it's, it's exactly, it's very close to your math, right
• 1:30:09
  the bottom. Price.
• 1:30:10
  Bottom price. That's a hundred 172.
• 1:30:12
  So it's very, very close. And then what would be the
• 1:30:15
  deviation up to 2029? Because I Giovanni, I, I know I
• 1:30:20
  understand my audience right and.
• 1:30:23
  This is this is 29. Of course is going to be less
• 1:30:26
  than 80. I didn't calculate it.
• 1:30:27
  We can calculate it, but that roughly maybe it's a deviation
• 1:30:31
  that is, I don't know 40%, but we can calculate it.
• 1:30:35
  I don't I don't remember by half what it is, but we can calculate
• 1:30:39
  what it is. I mean, in my in my model, I
• 1:30:41
  have it calculated all automatically.
• 1:30:43
  But if I have to use my memory, I don't remember, but let's say
• 1:30:47
  maybe it's close to 30%, right? So calculate what is on December
• 1:30:52
  29, the trend price. Let's get.
• 1:30:55
  Yeah. So 410 * .3 is, so it's roughly
• 1:31:00
  half $1,000,000 roughly. Yeah.
• 1:31:04
  So like half, half five point. Right.
• 1:31:07
  So do 30% of that. So basically the next stop is
• 1:31:10
  going to be close to 500,000. In 2029.
• 1:31:14
  Yes, awesome. Yeah.
• 1:31:16
  And then we go we crash all the way to 180 and so you can see
• 1:31:20
  right if you time it correctly and even if you just sell 20% of
• 1:31:25
  your Bitcoin and you buy back at the bottom, it's going to help
• 1:31:30
  you, you know it's going to help you a lot.
• 1:31:32
  And then you can use other things you could use.
• 1:31:34
  Maybe you can do some options with micro strategy.
• 1:31:38
  You know where maybe you short micro strategy again, nothing
• 1:31:42
  the Gen. but we want to give these tools to people.
• 1:31:46
  This is why I have an entire community on this quarter.
• 1:31:49
  We have this indicators, we have meetings on a regular basis on
• 1:31:54
  Discord every week. We want to create a group of
• 1:31:57
  people that is very dedicated, wants to understand Bitcoin
• 1:32:00
  deeply. And then without doing the chain
• 1:32:03
  things, but with all the knowledge and with all the
• 1:32:06
  awareness and being careful, we want to leverage some of this
• 1:32:10
  knowledge, right? Because if we can multiply your
• 1:32:13
  Bitcoin and you get 200 times instead of getting 64, why not?
• 1:32:17
  You know, the entire key is here because some people say, oh, a
• 1:32:22
  lot of people are going to get wrecked.
• 1:32:23
  No, I want to do the opposite of what Plan B does.
• 1:32:27
  And instead of pushing formal, I want to tell people, be careful,
• 1:32:31
  you know, be careful. But at the same time, because of
• 1:32:34
  this very predictability, very strong predictability of
• 1:32:37
  Bitcoin, then we can leverage and try to multiply our Bitcoin
• 1:32:43
  because that is our goal, right? We would like to have more.
• 1:32:46
  Bitcoin More Bitcoin 100%. It's always good.
• 1:32:48
  I also want to say too that like this, you know the you talk
• 1:32:54
  about science, right? And you talk about, you know,
• 1:32:58
  the these things and data points you're as time progresses, you
• 1:33:04
  know the science isn't going to lie, right?
• 1:33:06
  You know, the power law theory is, is either going to be proven
• 1:33:10
  right or it's going to be proven wrong or, you know, there's
• 1:33:15
  going to be more to the upside. And then we're going to have
• 1:33:17
  more data points on the upside. Like for example, last cycle,
• 1:33:21
  and I tweeted this out earlier today, I believe was cut short
• 1:33:25
  artificially because of the China mining ban.
• 1:33:28
  So I think we actually should. I don't think I don't think that
• 1:33:30
  is interpretation. What happened is that we did
• 1:33:33
  have two tops. Say the right interpretation is
• 1:33:38
  that we add 2 tops because that is that is plan BS QS.
• 1:33:44
  So I'll show you this chart. So we actually add 2 tops.
• 1:33:49
  We add 1 early on. That can happen.
• 1:33:51
  You know, it depends on, you know, maybe there are certain
• 1:33:54
  things like most of this stuff is driven by long term holders.
• 1:33:58
  So so. It may leave.
• 1:34:00
  I say don't, Don't trade these. Don't trade that, you know, who
• 1:34:03
  are the people? Giovanni so.
• 1:34:05
  So Giovanni, my, my, I, I didn't come to that conclusion based on
• 1:34:08
  Plan BI came to that conclusion just based on the Bitcoin hash
• 1:34:13
  rate, right? There's a direct correlation
• 1:34:16
  between. Now, but the hash rate, the hash
• 1:34:19
  rate you need to go deeper. The hash rate is very
• 1:34:21
  disconnected with the price during the bubbles.
• 1:34:25
  It doesn't have anything to do with.
• 1:34:27
  The no, no, but there there definitely is.
• 1:34:30
  You definitely can make a very strong argument as to why that
• 1:34:34
  caused downward cell pressure. So like that, that 50% of the
• 1:34:39
  flash rate, that's that's that's a lot of miners selling Bitcoin
• 1:34:43
  to relocate to more favourable. Jurisdictions, yeah, they don't
• 1:34:46
  have an impact on the market because the miners volume, it's
• 1:34:52
  like a drop in the ocean relatively to the normal volume.
• 1:34:56
  I can show you, you know, offline if you want, or I can
• 1:34:58
  make a pause that, you know, we can have a debate, you know,
• 1:35:01
  because we can have a debate offline.
• 1:35:03
  All right, maybe we can discuss it on X and open a thread and we
• 1:35:07
  can show you the evidence. But the evidence.
• 1:35:10
  So there are several things. The first thing I can show you
• 1:35:13
  from the data with Alvin, the ash rate, it's basically
• 1:35:18
  decoupled from price. During the bubble, it doesn't
• 1:35:22
  follow and even logically you can see why because it takes
• 1:35:26
  time for the mining to come online and during the formal
• 1:35:30
  everything happens we're very, I mean during the bubble
• 1:35:33
  everything happens very quickly. So everything that happens
• 1:35:36
  during the bubbles, it's formal, it's pure formal.
• 1:35:41
  So it's probably what happened is that the banning create panic
• 1:35:46
  in the people and the people salt.
• 1:35:48
  It's all what happened. It's all formal.
• 1:35:50
  It's all formal driven. It's there is no fundamentals.
• 1:35:53
  The miners have basically no impact during the bubbles.
• 1:35:58
  The only time when you have an impact, it's at the bottom when
• 1:36:02
  everybody sells, when you know so then is when the miners have
• 1:36:07
  an impact during the bubbles. They don't because there is a
• 1:36:10
  decoupling in the ash rate. So it was all driven by formal.
• 1:36:15
  So I agree that maybe the news created some kind of panic, but
• 1:36:19
  notice what happened and you can see it from this chart.
• 1:36:22
  The top, the real top happened exactly where he was supposed to
• 1:36:27
  be. So it was an initial top.
• 1:36:30
  There was no other high timing that could be driven by other
• 1:36:34
  that was bullish. Maybe it was too much excitement
• 1:36:37
  of you know, the FTX all these kind of things.
• 1:36:40
  You know, a lot of people coming in because there was a lot of
• 1:36:43
  advertising. You know, whatever FTXFTX maybe
• 1:36:47
  was creating formal, you know, because we were doing
• 1:36:49
  advertising and all these stars coming in.
• 1:36:52
  One can make always a story. One has to look at the data and
• 1:36:56
  then the real real top happened exactly where was supposed to
• 1:37:01
  happen with his research. So I and the size of a of a top,
• 1:37:09
  it's in line with the decay of the other tops.
• 1:37:14
  So it's true that is only three data points, but it didn't seem
• 1:37:18
  to be unusual. You know, it didn't seem to be
• 1:37:20
  like this very weird thing that it doesn't follow very precise
• 1:37:25
  path. Now we will have to see it's
• 1:37:27
  possible that the next bubble is not going to follow the path and
• 1:37:31
  then we can see, OK, you know, it was, it was an illusion.
• 1:37:35
  These are three dots that seem to be so well aligned.
• 1:37:39
  They were not aligned because the 4th one did something
• 1:37:41
  different, you know. So we will need to see it's only
• 1:37:44
  three data points, right? So this is where I say all the
• 1:37:46
  time, it's not really core part of the theory is just something
• 1:37:51
  that we are doing as another one just to give an estimate.
• 1:37:55
  But really we don't need to know how big that bubble is just all,
• 1:37:59
  all what we care is when. And I think when will happen
• 1:38:03
  exactly at the right time that the the regularity of the
• 1:38:08
  pattern is going to be respected.
• 1:38:11
  And so it's very important to understand the timing.
• 1:38:15
  And so that is the crucial thing.
• 1:38:17
  Interesting. Well, Giovanni, this has been,
• 1:38:21
  I'm very, very, very privileged to have you on the show.
• 1:38:27
  I've been in Bitcoin for a long time and I talked to a lot of
• 1:38:30
  people and this fascinates me and I've learned a lot.
• 1:38:35
  I don't say that very often. This is very interesting stuff,
• 1:38:40
  and I'll be honest with you, a lot of this goes over my head.
• 1:38:42
  This isn't my expertise, but I've been learning along the way
• 1:38:45
  as you've been describing this during the show.
• 1:38:50
  This is fascinating stuff. You know the power.
• 1:38:53
  I watched a video on YouTube describing power laws and how
• 1:38:56
  they happen in nature. And I think instinctively, you
• 1:39:00
  know, us Bitcoiners understand that, you know, that there is
• 1:39:05
  that Bitcoin is somehow connected with nature.
• 1:39:08
  And I would make the argument that is connected via proof of
• 1:39:11
  work. It's anchors it to the anchors
• 1:39:13
  it to reality. So this is fascinating stuff and
• 1:39:18
  I'm sure that a lot of people are fascinating in the chat as
• 1:39:20
  well. So we've put your website in in
• 1:39:23
  the chat multiple times. What I'm going to do as well as
• 1:39:25
  I'm going to put it in the podcast description so you guys
• 1:39:28
  could find out more about Giovanni's work and keep up
• 1:39:32
  with, you know, keep up with what he's doing.
• 1:39:35
  And I think the test of time is, is, is really going to show, you
• 1:39:40
  know, you know, if this theory pans out or not Personally, I
• 1:39:45
  find this fascinating. I want to learn more about it.
• 1:39:48
  And this is really, really, really cool stuff.
• 1:39:51
  And I'm, I'm just very, very happy that the Bitcoin community
• 1:39:55
  has so many, so many smart people, so many geniuses with
• 1:39:59
  all these different backgrounds that are contributing this type
• 1:40:01
  of work and this type of data. So this is really, really
• 1:40:04
  interesting stuff, Giovanni and I look forward to having you
• 1:40:08
  again back on the show to discuss, you know, the, the
• 1:40:12
  theory, planning out and seeing where where things are going.
• 1:40:16
  So this is this is fascinating. Perhaps we do an episode with
• 1:40:21
  with Fred Krueger and yourself. And we can just discuss the
• 1:40:25
  three of us more about this, you know, in a couple of months.
• 1:40:30
  But this is this is fascinating. I really, really enjoyed this.
• 1:40:33
  I learned a ton. And this is this is amazing
• 1:40:37
  stuff. So Giovanni also has a YouTube
• 1:40:40
  channel, guys, you can follow it at Quantonomy.
• 1:40:44
  And I believe that you guys drop some, some, some content in
• 1:40:49
  relation to this. Like I said, the website is in
• 1:40:53
  the in the YouTube chat and also in the YouTube video slash
• 1:40:57
  podcast description as well. Giovanni, usually I do these
• 1:41:01
  podcasts for about an hour. We did it for an hour 41.
• 1:41:05
  So no, no, no, no, no, no, this I'm, I'm, I'm saying that as a
• 1:41:10
  compliment because, you know, this is how this is how
• 1:41:13
  interesting this conversation has been.
• 1:41:16
  So Giovanni, I really wanna thank you for your time and I
• 1:41:19
  appreciate you coming on Simply Bitcoin today and just telling
• 1:41:24
  the audience about the law that you discovered.
• 1:41:27
  You saw that Bitcoin is connected to a power law and
• 1:41:32
  that is absolutely fascinating. So guys, go follow Giovanni.
• 1:41:36
  He's he's he's very vocal on Twitter.
• 1:41:39
  Go check out his YouTube channel.
• 1:41:40
  Go check out his discord. I just, I just joined his
• 1:41:43
  discord. I joined his Patreon because I'm
• 1:41:45
  really, really fascinated about this type of stuff.
• 1:41:47
  So guys, thank you so much for joining us.
• 1:41:50
  I'm your host, Nico, this is my host.
• 1:41:51
  This is my guest, Giovanni. This is simply Bitcoin IRL.
• 1:41:55
  And we'll see you tomorrow for the live show at 12:15 PM
• 1:41:58
  Eastern Standard Time. Peace out, everybody.
• 1:42:00
  Thank you so much. Episode was brought to you by
• 1:42:04
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