{ "episodeId": "SLP475", "speakers": { "stephan": { "name": "Stephan Livera", "role": "host", "tag": "STEPHAN" }, "rapha_zagury_cio": { "name": "Rapha Zagury CIO", "role": "guest", "tag": "RAPHA" } }, "segments": [ { "speaker": "stephan", "time": "00:06", "start": 5.72, "text": "Hi and welcome to Stephan Livera podcast, a show about Bitcoin and Austrian economics brought to you by Swan Bitcoin. You can use swan dot com or the Swan app available for iPhone or Android for safe and easy Bitcoin buys. Swan offers recurring purchase plans and you can also do one time buys, also known as smash buys. Swan offers free custody in your own wallet. legally owned trust account, and of course, not your keys, not your coins. Swan also offers free automated withdrawals to self-custody, which Swan encourages you to do. With Swan, you can easily start stacking Sats while also learning about Bitcoin. Swan makes all kinds of resources available to help you decipher this crazy world and understand what Bitcoin is and what the mission is and what the goal is of this. With Swan, you can make it really easy to automate your sat stacking process, and that can help you deal with the volatility over time. The long term also, so go to swan dot com slash livera to sign up and get ten dollars of Bitcoin dropped in your account when you start stacking with Swan. Next is CoinKite. As you all know, not your keys, not your coins. It's important to think about self-custody, and CoinKite are making hardware products and tools that you can use to easily self-custody. The Coldcard is my favorite Bitcoin hardware device. It's really reliable and very practical, and it just makes it so easy to self-custody your coins. You can use it in air NFC or with a micro SD card, or you can directly plug it into a computer if you are a beginner, and you can use it in all kinds of configurations, whether it's single signature or with a passphrase or as part of a multi-signature setup or with BIP eighty-five. There's so many options, and you actually learn more about Bitcoin as you explore some of those. So if you wanna get your cold card with a discount, go to coinkite dot com and use the code Laverara for a discount on your cold cards. Mempool dot space is the leading Bitcoin and blockchain explorer Is a multi-layer ecosystem and mempool dot space is comprehensive, it lets you view that entire ecosystem. You can see the mempool, you can see the blockchain, you can see second layer networks like the lightning network, and you can see all kinds of interesting details about the transactions that you are using, like whether it was a multi-signature transaction or what kind of fee rate was attached or details about the lightning nodes on the lightning network. With mempool dot space, you don't even have to trust a third party, you can host it yourself, it's free and open source software. Now, if you This custom mempool instances with your company's branding, you can get increased API limits, you can have increased access to the team for feature requests and more. So go learn more over at mempool dot space slash enterprise. So for today's episode, Rapha from Swan, he is the CIO, joins me to talk about the Nakamoto portfolio and why it's essential that people should be holding Bitcoin as part of their portfolio. I think he has a lot of really interesting perspectives about how research should be done and some of the problems with research. research in the financial services and fiat world today and what can be done to improve that, as well as talking about various concepts around the Nakamoto portfolio, portfolio optimization, DCA or lump sum, the Schrodinger model, and more. Rapha, welcome to the show." }, { "speaker": "rapha_zagury_cio", "time": "03:16", "start": 196.33, "text": "Thank you, Stefan. Great to be here." }, { "speaker": "stephan", "time": "03:19", "start": 198.79, "text": "Yeah, and, I, I found it really interesting, obviously now you've, recently joined with, the team at Swan, and I found it funny that we actually knew each other even before you joined, and, I was looking back through our DMs, and I remember we were chatting back in, I think twenty nineteen, or maybe early twenty twenty, back in those days about the risks of things like BlockFi and, rehypothecation. So quite, a funny story to see that you sort of come around and, now here" }, { "speaker": "rapha_zagury_cio", "time": "03:49", "start": 229.25, "text": "Thank you, thank you. It's great to be at Swan, you know, that this is actually a good way to start because I've been, first active on Bitcoin Twitter for, for a while, right? But also been following Swan for a while, and of course, you, right? So it's, it's an honor to be here. I've listened to, I don't know how many hours of your podcast through the, through the years, you know, I love running, and I always take, one of your podcasts with me when I'm, Great to be here. It's a pleasure to be here, and I can tell you a little bit about my story of how I ended up at Swan, but it has a lot to do with the story that you mentioned, a lot of block, about BlockFi and the scams in, in the Bitcoin world, and, you know, Corey and I have been kind of the same way that we've been exchanging DMs, we've been exchanging DMs, so it, it ended up, working really, really well. So" }, { "speaker": "stephan", "time": "04:40", "start": 280.27, "text": "Yeah. And let's, while we're here, let's How research is being done in the, let's call it, normie or normal, fiat financial world versus how you think it should be done in, let's say, the Bitcoin open source ethos. So, do you wanna expand a bit on that?" }, { "speaker": "rapha_zagury_cio", "time": "05:00", "start": 299.51, "text": "Yeah, a- absolutely. So I spent all my career in Wall Street, pretty much, right? So I, I was, fourteen years working Wall Street in New York, worked at Merrill, worked at Goldman, worked at Deutsche Bank, so saw a little bit about, of everything, mostly on the trading side. So I did some fixed income trading, did some derivatives trading, but through those years, of course, and then when I moved back to Brazil, I decided to start my own company, started two companies. One was an investment banking company, and the other one was- Lending FinTech, which become, became one of the largest FinTechs in, in Brazil. but through the time in Wall Street, I saw a lot of things that, you know, as you imagine, I didn't like seeing. and one of them was exactly on research, you know, how conflicted research was, how closed doors everything was, and, that always bothered me, right? You know, you would see a price target for a stock, but, even though the company, the, usually the bank would provide some rationale how you got to those it doesn't really provide you the model, so you can't check the calculations, you can't check all their assumptions, right? so it's very, very hard to critique and to really analyze anything that they are doing. the reality is that the vast majority of people, they would take for granted whatever they see. So, Wall Street will send out a research to have a price target on a stock, and the general population would just read that and say, \"Okay, you know, so, Goldman thinks that stock X, Y, Z is going to the moon, And, that, that, that also really bothered me because it depends. First of all, it's out of context. It's not that stock may or may not be for, for everybody, right? Or that asset or whatever it is, but also just pinpointing a price for a specific stock, it's just like throwing darts, right? And in fact, there, there's actually, there's actually an experiment that, the, the Wall Street Journal conducted, you know, and you, you can Google this, you'll see like many, many years ago They got stock analysts, and they also got an ape, and the ape would, would spick out of a box, you know, different stocks, for a certain period of time, and guess what? The ape did, it was beating the analysts, right? shocker. So, and there are different experiments like that. There's like the dart experiment that the New York Times, I think, did, where you just threw darts and, into like a, a panel of stocks as a way to-- So there's a random component to it that it's massive You, if, if you've been like me, that you've been seeing these analysts come and go, you would see that some of them will have two, three, four years of very good, and then they, you know, they start not being so predictable and they start having, you know, bad predictions for, for a while, which is, it's expected. The other thing I've seen, you know, kind of like in parallel to that is traders. You see traders are very good traders for a year, for two years, for three years, but, I think I can count" }, { "speaker": "rapha_zagury_cio", "time": "07:59", "start": 479.21, "text": "Traders that I think that, that I've seen that were consistent across a very long period of time, right? So then if you see that, you start to think, \"Well, maybe these are just the guys that, you know, threw the dice and got six in a row, twelve times in a row,\" which will happen, like, you know, they're like, \"Were they" }, { "speaker": "stephan", "time": "08:15", "start": 494.62, "text": "lucky or were they skilled?\" And maybe the question is, if they weren't able to sustain it for a long period of time, maybe they were just lucky." }, { "speaker": "rapha_zagury_cio", "time": "08:20", "start": 499.84, "text": "And, and I don't think our lifesp" }, { "speaker": "rapha_zagury_cio", "time": "08:29", "start": 509.21, "text": "People that will have ten, maybe twenty years as analysts in, in Wall Street, you know, and in twenty years, you may have five and ten years that are good just because you were lucky, right? Don't get me wrong, there are people that are very, competent and they're, I think there are people that add a lot of value, but typically, unfortunately, what would happen is that the ones that were lucky, you know, were actually getting predictions three, four, five, ten years in a row, these are the ones that rise to, to the top, right? And We're lucky and also the ones that are competent, and my experience is that the ones that are lucky are actually the ones that, that start, rising to, to the top, right?" }, { "speaker": "stephan", "time": "09:09", "start": 548.57, "text": "Yeah, yeah. And the other point I wanted to, I wanted you to elaborate on is the models aspect, because it's very feasible for people to, based on the assumptions that you build in Create all kinds of valuations and numbers, right? So as, as an example, you may be an analyst, and I'm sure maybe you can elaborate on this, but as I understand, you could be an analyst who's looking at a stock, and there's all kinds of subjectivity involved, right? You might be looking at, okay, what's the discount cash flow analysis, right, known as DCF, you may be looking at that, and based on the assumptions, this is how I'm gonna build out a price estimate for what I think the future, you know, the future value or" }, { "speaker": "stephan", "time": "09:51", "start": 591.32, "text": "The numbers there to generate a desired outcome." }, { "speaker": "rapha_zagury_cio", "time": "09:55", "start": 595.25, "text": "absolutely. So, yeah, so as you mentioned, most of the analysts we would use something like, you know, either looking at multiples or lo- looking at discounted cash flow of stocks. What they'll do, you know, very, summarize that they will look at what their expected returns or the expected profits from their company or whatever is the multiple that they're using, right? And they'll discount that to today's value. So they're gonna look, okay, I expect this count company for the next ten years to generate this amount So you discount that to the present and then you come up with a number. Well, there are several problems with that. One of them is, you have to estimate the cash flow, so there's uncertainty around how mu-how that company is gonna perform in the future, right? That's already a huge un-uncertainty because as we've seen, their companies are doing really well this year, may do poorly three years down the road. A company on the opposite, the company may come up with a product that was completely unexpected, take over market share and just explode in value. rarely we Up discontinuities, right? As humans, we're terrible in predicting discontinuities. So anything, we always think that the next day, the next month, they're gonna be just like the last day and the last month that we experienced, right? that's kind of like the famous quote from, from Talab, right? The, the turkey never knows that there, it's Thanksgiving, right? So Thanksgiving comes and the turkey didn't expect that, that was a very unexpected, day. And we're exactly like that. So none of these models, first of all, they thing you mentioned, which is really, really important, and most people when they see the price and they don't think about that, is the, that price that estimate, it's dependent on like a lot of variables, and small changes in some of these variables lead to massive changes in what the price is, right? So one of them is the discount rate. So you're discounting all these future cash flows by certain discount rate. So if you have higher interest rates, for example, that is a problem because, you know, prices are gonna go down on, on the present value basis. the other one is also, as I just mentioned, you have to predict how those companies are gonna be performing, right? And when you have several variables together that each of them could impact the numbers, right? You have a lot of room to, to maneuver. And, we've seen there are stories about this, you know, you can Google, I'm not making this up, you know, instances where investment banking, part of the, the company of the bank, right, was putting pressure on research because that company that they were doing research on was actually a client, right? Enron is great case about this, right? And they couldn't lose the business, so the analyst shouldn't be coming out with an estimate that was bad, and the analyst could just play around with two or three variables and get to, to the number that, was, you know, what the number they were looking at. And, that happened in Enron, right? There were like massive lawsuits against, Goldman against Miro in terms of exactly the, the conflicts between, and you're A Chinese wall, right? But, yeah, that, the, the, the walls are made in China for sure because they're, they break all the time and they, you know, okay, the people jump from one side to the other and, and that still happens today, because the investment bank, at the end of the day, you know, you have a CEO in the bank, right? And the CEO oversees both sides of the bank and, you know, whether they like it or not, they may see, you know, an analyst may see, oh, that this company" }, { "speaker": "rapha_zagury_cio", "time": "13:21", "start": 801.28, "text": "Don't want to, right? And they aren't notified, they're still influenced by that because they know that, you know, if the comp- if the bank loses that company, at the end of the day, that's gonna impact his bonus, in a way or another, right? So it's very hard unless you are completely se- which they are, right? Completely separate research, independent research house, inside banks, they are gonna be conflicted, right? And these just became machines also to go out and put out reports and, you know, you, you can Reports a day with different analysts and, you know, expect that you are gonna have quality all around. Pick any bank that you want, and, you know, pick Bitcoin's a great example. You're gonna have, you know, inside Goldman, you have good research talking about, Bitcoin, and then you have somebody like Charmin, which is the, she's the CIO of, the wealth management side that hates Bitcoin, and, you know, and you read it, and it's everything is very superficial. It's still, they're still at the, bit Right? So these guys stopped like ten, fifteen years ago and aren't interested in looking at it, just using this as an example to show that, you know, research can be very wide and, and, and very diverse even within one company, right?" }, { "speaker": "stephan", "time": "14:36", "start": 875.99, "text": "Right? Yeah. And I think that's also, an often missed point, which is people will come out and say, \"Oh, Goldman said this,\" but actually it's like one particular team, and it's a massive organization, and these different teams all have different views on things, and the individual analysts writing those Reports and doing models and mo- financial modeling will have totally different views. One other point I wanted to touch on, as you mentioned, the discount rate. So as, as we mentioned, often these models will be de-highly dependent on specific variables, and in one, one notable case, the discount rate. So for people who aren't familiar, the finan-- you know, the finance behind this, the general idea is this concept of the time value of money. So the idea is you may be estimating future cash flows, and then we are- Discounting each of those years back to the present year to kind of come up with the NPV, net present value. And the interesting thing here is the discount rate is really influential, and it can cause funny behaviors when that discount rate is either, you know, is really high or really low. And so in the recent environment where, up until recently, before we had the rates come up a lot in the US, when the rates were really, really low, I think it's fair to say people could justify All kinds of crazy projects because the discount rate was so low. I'm curious if you have any thoughts or you wanna elaborate on the discount rate being low and how that can exaggerate or cause really crazy things to happen in a valuation context." }, { "speaker": "rapha_zagury_cio", "time": "16:08", "start": 967.73, "text": "Absolutely, and, I think one of the results of that that we've seen is the massive financialization of different assets, right? Because capital has to go somewhere if the interest rates that you're receiving, you know, as, as a return are low. The capital is gonna go somewhere else, right? It may go to real estate, it may go to different assets, and I'll come back to that, you know, that has a lot to do with one of the models that I wrote. But you're absolutely right, I think in an environment where you have very low interest rate, right? and we know that intuitively, projects that, historically wouldn't be considered reliable and viable, right? They become viable because first of all, the, there's capital available for them because the capital wouldn't go anywhere else, right? Manipulation of lower interest rates that we've seen, you know, actually created a lot of the problems that we're seeing right now, right? So we see manipulation, we talk a lot about money printing, money printing, money printing, which is of course huge problem, but the manipulation of interest rates is also a massive pro-problem, right? Because your governments are actually making, financing of some of these projects that shouldn't be around just being viable, so it's an indirect subsidy to, you know, bad projects, crazy ideas, right? Exactly. And people very rarely talk about that, you know, Stephan, if I told you, like, you know, I tell everybody the story, like I lived in Brazil, so I grew up in Brazil, in my early age, and I talk a lot about, you know, price controls and crazy things that I saw. And anytime that I talk about price controls, people say, \"Well, that wouldn't never happen in the US, right?\" Well, that happens with interest rates. Interest rates are price control, right? The, the interest rate is the price of the money, and That meeting, and we, we actually applaud that, and that's transmitted on CNBC and everywhere else, right? And it is a price control. They're controlling the price, it has massive implications in all the assets. You're directing money to one way or the other, and, you know, it's impossible also for a group of people to know exactly where the capital should be going. They should let the market do that, right? And the money would have interest rates would be very different in one place than the other, as it should be, and it should be Actually different for individuals and for companies, right? And significantly different than, than it is today. as I said, one of the things we, you know, I built was a credit fintech And we actually did like massive underwriting, on the clients. We used like forty thousand data points to try to get what, what is the right interest rate for that individual, because what we see is that, you know, individuals usually, particularly in, in, in developing countries, they'll go to their bank account, they'll ask for, they'll ask for, for, for some kind of loan, and the interest rate that you're gonna get, the interest rate that I'm gonna get, the interest rate that pretty much anybody's gonna get is similar, it's the People that, you know, shouldn't be getting that loan anyway, they're gonna be getting a cheaper loan than they did. But also on the other side, you have people that are, you know, very good quality that you, I would be willing to lend them at very low interest rates, but I actually can't, right? Because you have regulations, you have things in place that, that don't allow you to, to do that. So that, that's a massive, disalignment of interest that, that, again, we, we have in, in our system that need to be broken up in some sort of way, right?" }, { "speaker": "stephan", "time": "19:32", "start": 1172.39, "text": "Yeah. I think one point just to explain that for listeners who are newer to the concepts behind Austrian economics, a famous concept in the Austrian school of economic thought is the Austrian business cycle theory, and that's exactly what we've been speaking about as Central banks and governments artificially push interest rates lower than what they otherwise would have been. What happens there is that projects artificially look like they are viable when really they aren't because of this problem with the discount rate, as we've spoken about. So because entrepreneurs have been fooled in a sense, and one way I've heard, it's kind of a pithy way to say it, it's not that, entrepreneurs all of a sudden become idiots and they're doing all this malinvestment, it could also be that idiots become entrepreneurs, right? It's that, unfortunately, people have, because we've lost all tether with the real world, there's not that accountability that a real free market sound money would, enforce. There's no discipline being enforced by a free market sound money, so instead it's being fiat created, there's artificial cheap credit. It just looks, it makes projects look really viable, and that's why we see all these people running to do things like, you know, flipping houses or the dot com bubble or, in the two thousand and eight case, there was this idea of the ninja Loans, right? No income, no job, no assets. So all these loans were being issued for people who were simply not creditworthy. And so that was a problem in two thousand and eight. Of course, you know, there are different issues that come up over time, but essentially the Austrian cycle, business cycle theory is showing us and explaining for us that we're going to see all this malinvestment. So I think bringing it back to sort of the Bitcoin ethos of verifiability, I think that's something that you're trying to change with, how you- Your approaching modeling and being able to show people, okay, these are the assumptions we have made. If you have different assumptions, you can plug those in and you can see what numbers you come up with. And it's, I think that's actually interesting because it's more reproducible, it's more verifiable, and that's really much more aligned with the Bitcoiner ethos and a little bit about how financial modeling and financial estimation could be done. So do you wanna just, elaborate a little bit about how you're viewing modeling?" }, { "speaker": "rapha_zagury_cio", "time": "21:47", "start": 1306.9, "text": "A- Absolutely. So a little bit of background first. So as I said, you know, when, when I was growing up, I, I always loved technology. So I've been involved in, even though I went, went to work in financial sector, I always loved technology. I actually ran, you know, your listeners are probably not gonna know what this is, but a, a BBS, bulletin board system like back in the, in the nineties. So these were, this was the infancy of communication of the internet, as we saw. We used dial-ups, we, you know, Access with their modem so, you know, chat and download games and different things like that, right? so I, I've always been involved in technology in some sort of way. So even when I was working at Wall Street, I, as a hobby, I would do other projects, right? And I always loved to be involved in, in the open source community. So I've contributed to, to some projects, along the way, I've created my own projects, right? And there are challenges with open source, code and the o-open, open source, system, but I think the benefits for the community far outweighs all, all of these challenges, right? so I've always been a huge proponent of open source, and, so when I joined Swan, you know, was talking to Core and Core is like, \"Oh, we need to start thinking about different things in research, what we're gonna be putting out, right? \" And kind of like with that ethos in mind of, having transparency and with everything that I just mentioned, that, you know, I wasn't gonna definitely, I told him like, \"I I don't have any price predictions for Bitcoin, you know, predicting price is a losing proposition, right? At least in the short term, I can tell you the direction the price is going, you know, in five, ten years, which I think it's up, if it's gonna be up ten percent, twenty percent, you know, a thousand percent, I have no idea, no one has any ideas as well, right? So if anybody tells you that they know where price is going, I can tell you, they're wrong, right? And this is one of the reasons why I" }, { "speaker": "rapha_zagury_cio", "time": "23:48", "start": 1427.76, "text": "Places, right? There are other issues with that, but any model that I see that is trying to predict price along the time, I already kind of like don't like that because again, you have to be very right and you have to have so many variables that are right in order to, to get to that price. So this was the first thing we had in mind is that, you know, it was gonna be open source, and the other thing is that we're gonna make it available so that anybody can run the numbers, so not only on the open source side so they can replicate the code and can Right? We're gonna have, I can guarantee you that, you know, in, on our website, there's something there that it's wrong. So this, this gives an option to whoever is looking to the numbers to redo the calculation and get to their own numbers, which may be in line with, not with others. The second thing is, for people that don't code, like we, we know the vast majority of people don't code, right? So we couldn't expect to just put the code out there and expect people to read the code and understand what's happening, you know, So we actually provided web apps where users can go there and then just change the assumptions. So the model is baked in, but the assumptions aren't, and they can plug in their own assumptions, right? So for example, we have a model that at the end of the day, it's looking at the probability of the monetization of different assets. we have a base case, you know, we have a bear case, we have a bull case, but don't take those from granted. Get in there, run the model, and then you can change all the assumptions, right? So the same That we created to get to these levels, you can do the, the same thing. The other thing is that, you know, we talk about models, models, models, but a lot of the thinking isn't creating models, it's actually on creating frameworks. So when we build this model, the, the, the end goal isn't to have a price prediction, the end goal is try to explain why different things happen, right? So in this model that I just mentioned, for example, it's very easy to see why Bitcoin has massive volatility, because- Small changes in some of these variables would lead to significantly different prices in Bitcoin, right? And as we, as a collective group, right, of investors, of people looking at Bitcoin, are making our own assumptions, you're gonna have the ultra bear that thinks Bitcoin is gonna go to zero, and you have the ultra bull that think Bitcoin is gonna go to a hundred million dollars, right? And everything in between. so this gives you a, a, an idea of like, okay, if the guide says goes to zero, this is an easy one, but there's Bitcoin gold, right? But So the guy that is talking about, you know, a hundred million or whatever the number is, what his assumptions need to be to get in that place, right? And then try to do the opposite and say, okay, given these and given what we know about the model, how's the current price pricing these probabilities, right? Is this a high probable event? Are we early, in adoption or relaying adoption? And I think with these things, it's very easy to see, you know, first that, as I said, price can be very volatile, and second, we're very Are extremely early in, in a lot of senses, right?" }, { "speaker": "stephan", "time": "26:51", "start": 1611.46, "text": "Yeah. And let's chat a little bit about some of the modeling that you've started and this idea of Nakamoto portfolio theory. So what, what is that?" }, { "speaker": "rapha_zagury_cio", "time": "27:01", "start": 1620.58, "text": "Yeah. So this is the first big piece of research that we're putting out, right? So based on everything that I said, on how we're gonna do, be doing research, the first area of focus for us is portfolio allocation and how Bitcoin should be part of any portfolio. At the end of the day, right? So what I did is I went back to all the models, all the theories that, you know, I've seen through, you know, all this time, and in-- I either adapted them to work with Bitcoin or just, in most of the cases, I just ran them as they are so that we can see if Bitcoin could, could fit or not in this portfolio. So another way to think about this is a challenge I always had is when I went to my colleagues and talked about Bitcoin, right? It's too foreign for them. There's too many things that they need to know in order to really grasp b-bitcoin, right? They need to know about, you know, a little bit about Austrian economics, they need to know a little bit about technology, they need to know a lot about game theory, and it's hard for them to break out of some of the silos that they've had in the past. So what I've tried to do, and this is again, a lot of the work that I have on the NAKMO portfolio is part of this framework that I've been doing, is actually go back to their models" }, { "speaker": "rapha_zagury_cio", "time": "28:18", "start": 1697.72, "text": "Portfolio theory, which is not very modern, is a theory that was written in the fifties, right, by Markowitz, that basically looks at the assets, look at historical returns, and then take the, the try to see how do you optimize risk for the amount of return that you wanna take or the opposite, right? You tell how much risk you wanna take, and then you find the amount of return or the best weighting that you, you can do, with these assets, right? So I got this, and I included Bitcoin, and the, the result, which again we Should be part of pretty much any allocation that we, we look at. It's an asset that has low correlation, right? that has, of course, good returns, has very good, returns by the amount of volatility that, that we see, right? So everybody says, \"Oh, it's volatile, it's volatile, it's volatile,\" yeah, it's volatile, but it also has, you know, good returns in, in the long term. So, that's the nature of, of the beast. So in a sense, I'm trying to," }, { "speaker": "rapha_zagury_cio", "time": "29:18", "start": 1757.78, "text": "A story, a very quick story. So there's a, a colleague of mine who's a bit-- became a Bitcoiner today, but, he was very skeptical of Bitcoin for a long period of time. And this is a major investor in hedge funds. This is one of the guys that started investing in hedge funds like really, really early, and of course, made, you know, good amount of money with hedge funds, right? so, you know, I, I told him about Bitcoin a while back, and he couldn't break it out, so he kept asking these questions about It works, I can't verify the code, I can't see anything, right? how transparent it is, like the typical, the government's gonna ban it, right? Like the typical, questions, and he couldn't ever get, get across it. So, and but, but this is a good friend, so like, I need this guy to see that this is more than actually he's, he, he's seeing, right? So I did something a little tricky. So I called him up, I got the Bitcoin historical returns, right? This was early" }, { "speaker": "rapha_zagury_cio", "time": "30:18", "start": 1817.96, "text": "I printed in a sheet that looked exactly like a hedge fund manager to him. So it had the monthly returns, had the historical distribution, right? Again, a lot of this work that I have on Echomodo, portfolio was born from, from that story, right? and I sent it to him and I said, listen, I'm investing and, you know, just like he knows, he knows I also invest in, in hedge funds. By the way, this guy invested in Madoff, right? Which is a completely different discussion, but keep that aside because I w-w-with this fund, and I don't know, this f- this manager looks very good in the long term, but he has some very bad ears. So, what do you think about that? Should I invest with that? And takes like ten minutes, the guy calls me up, right? And it's like, \"Who's that manager? I wanna invest with him. You know, this is very good returns. I, I will take the bad ears, right? You know, this isn't a problem because look at his historical returns, right?\" And, and I told And Mr. Nakamoto in Japan, he's very secluded, right? I don't know if you're gonna be able to get in his fund, you know, it's not for everybody. See, there's a lot of volatility. And he's like, \"Well, try to get me a meeting with him, 'cause I really, really wanna get, get to meet this guy.\" So we hang up, I don't tell him anything. So he picks it up and he calls me like ten minutes later, he's like, \"These are Bitcoin returns," }, { "speaker": "rapha_zagury_cio", "time": "31:45", "start": 1904.75, "text": "right?\" I'm like, \"Yep Manager, where I have no transparency, I don't know what they're doing, right? I would probably invest and knowing that Bitcoin is transparent, I'm actually asking all these questions, right, that a manager would never answer to me. So I may be overthinking this, and he ended up, that's how he ended up investing a little bit in Bitcoin to start with, and, and then a little bit becomes a little bit more, and you start to learn, right, and it comes back. And he mentioned, he's like, \"Yeah, I invested in Madoff, right? Turns right, and I was happy for a long period of time until I wasn't. So again, I'm overthinking this, I shouldn't be. So I'm telling you this story because, as I said, the Nakamoto portfolio was born from these kind of conversations that I had in the past. It's a little bit of a Trojan horse, Stefan, you know, that I'm going out there and, putting it out there in a language that a lot of traditional financial advisors, that other people can read and can see that, you know, Bitcoin has a place I'm talking, I'm speaking their language, right? If I just go to them and say, \"Yeah, you know what? This is decentralized technology and, you know, you can verify the code,\" it doesn't resonate to a lot of these people, right? Resonates to us, right? 'Cause we know, again, technology and we love this, this stuff, right? But then we have a little bit of a, an Austrian school, mindset, right? A lot of these guys don't, and they don't have time also. Financial advisor is thinking about Right? He's looking at, you know, new funds that the client's investing, right? He's looking at, how they, how they're gonna do inheritance, so they don't have time to dig, to dive, do a deep dive into some of the assets. So what they will do usually is that they'll receive a fact sheet just like this, right? They'll look at the returns and like, yeah, this fits or doesn't fit my overall portfolio, right? and again, I, you know, I'm very happy with what we've done because, and this I've seen everything in these last few weeks. It's been a week and a half that we launched this thing, and it's like, you know, the website breaks all the time 'cause people are, are really running the numbers, and people are coming back and saying, \"Oh, I added in a portfolio of, corporate bonds, for example, right? And here are the results, and Bitcoin should be there, right? I shouldn't have fifty percent Bitcoin, but I should have maybe one percent Bitcoin in that portfolio, right? \" And I ran this on a portfolio of commodities, and I'd like everybody to just go to a nakamotoportfolio dot com and then they can, they can run the numbers, right? They, they can see, how their own portfolio or a fictional portfolio would actually perform compared to, to Bitcoin. And there we have several, you know, I got all this, analytics that we've had in terms of statistics. You can be as basic and/or as advanced as you want, and we're gonna be adding more things to that with, with time as well." }, { "speaker": "stephan", "time": "34:45", "start": 2084.99, "text": "That's fantastic. And I think one interesting point that Came to me from your story, which is a great story, it's that when people are new to something, they often impose an even higher bar for that new thing than what they're currently using and comfortable with. So it's, it's kind of funny that, y-you know, your friend was imposing this incredibly high standard for Bitcoin, but that standard was much higher than the standard he was already applying for things that he would already put money and did already put money into. And so I think it's a funny parallel, and it just shows- Because to some extent, it's about people who are open-minded, and to some extent, it's people who are willing to think for themselves and being willing to challenge the herd, right? Because there are some people out there who would rather be wrong, but with the tribe, let's say, than be correct and on their own. And I think absolutely that sort of, yeah, and that sort of shows, you know, people who get into Bitcoin early, not all of them, of course, some of them were, you know, maybe some of them were lucky, not skilled, Familiar, but the ones who were skilled, they were getting into it because they were open-minded, but they also were able to have some kind of thesis about why they held for such a long period of time. Because as many people have mentioned, right? You, you know, people might have bought Bitcoin at two dollars or whatever, but did they hold it? That's the important question, because many of them didn't, or they would have sold for a ten x, because if you don't have a thesis about where you think it's going in the long run, you're not gonna be able to Idea." }, { "speaker": "rapha_zagury_cio", "time": "36:19", "start": 2178.66, "text": "Just one point on that, Stefan, it's, it goes back to one of the reasons why we're trying to do research differently, because if you actually, I was looking at this this week, get, I, I think I actually put this on Twitter, Look at the analysts and the predictions that they had for Silicon Valley Bank up until a few, a month ago, right? And what you'll see is that there's, there's a chart you can see, like the where, where the expectations, the price expect-expectations are from the most bullish analyst to the most bearish analyst, and the difference is like none, right? So there are no outliers on this, right? Everybody, why exactly for what you just said, right? A guy that goes out there and has a price prediction that is much different than his peers He's gonna have a target on his back, right? It could be good, it could be bad. Most of times it's bad because, you know, he took a chance. If they're all wrong, it doesn't matter, everybody was wrong, you were with the pack, right? Which they were. And you see that, you know, as, as things start to collapse, all the analyst expectations are going down together, right? So everybody's with the herd, and, for us as investors, that has no value, right? I mean, I'm not gonna be reading that It's easier and it has probably more signal than looking at the analyst expectations, right? because the guy that made, you know, the wild prediction, and he was making wild predictions for many years, he got fired, he's not there anymore. So there's negative selection also, right?" }, { "speaker": "stephan", "time": "37:46", "start": 2265.86, "text": "Yeah, it's like a survivor bias, maybe a recency bias, as well as that kind of tribal aspect that, you know, maybe there's still a bit of a- Biological or cultural element that, may be programmed into us, right? Because maybe historically, if you were, let's say, not in line with the tribe, that might have been a death sentence, right? Like you might be literally not eating if you weren't in line with the tribe. So maybe you can sort of understand, maybe there's some psychological or biological reason for that, but in today's world, maybe it's maladaptive in a sense, or we're maladapted for, you know, the modern world and maladapted to understand why. Bitcoin is a better money, and it's, it's gonna take time, right? That's, that's kind of my thesis as well, is that I, I believe it'll take, you know, it may, it may, you know, hyperbitcoinization, as much as, you know, people pumping it on Twitter or whatever, saying, \"Yeah, it's gonna happen next year or whatever,\" no, I think it's, it's, it's a long process of people slowly shifting and understanding, and it's only that small percentage, let's say fifteen or twenty percent of Streaming into understanding and using Bitcoin, and maybe they won't consciously, be thinking about why it works or why it makes sense, they'll just be using it because, okay, the tribe uses it, you know? So maybe there's a little bit of that, but I, I'd love for you to touch a little bit on, we were talking about modern portfolio theory and, you know, portfolio optimization, could you just explain a little bit about that for, you know, for, for the neophytes and people who are new, what that is and why" }, { "speaker": "rapha_zagury_cio", "time": "39:24", "start": 2364.21, "text": "Yep, a- absolutely. So, you know, think about it this way. You start with a basket of assets, right? Let's say we pick S&P, we pick bonds, we pick commodities, we pick different-- let's say we pick ETFs, right? Exchange-traded funds, which are easy to track, their price daily, and, you know, there's a market on them daily. So we pick a basket of different ETFs and stocks. Let's say we pick Apple, we pick Google. We put all of this in a box, right? and we put Bitcoin And back to Bitcoin. So the first question that, you're gonna have is like, okay, I know I'm gonna buy all these assets, but how much should I buy of any of them, right? And the answer lies in different things, right? It lay, lies also, first of all, in your risk preference. So you might, might be somebody that is very risk averse, that don't wanna take too much risk, or maybe a corporation where this is cash for your corporation, you can't be risking it too much, so you can't take too much. So Investor one, and then investor two, maybe an investor that it's ver-- it's young, could take a lot of risk, right? And he's okay in having very large volatility in his portfolio because he's gonna hold on for, for the long term, right? So these are two kind of investors. So modern portfolio theory tries to do is optimize for a given variable. So in this case, it may be risk. So the first investor is gonna say, \"I'm very low risk. I'm trying to achieve, let's put a number to it, I'm trying to achieve a volatility percent in my portfolio because I'm very low, very risk-averse. So what you do is that you start with the probability that you know it's three per-- the, the volatility which you know is three percent, and then you look at the volatility of all of these assets, you combine them together, and you try to get what would be the optimal, allocation to all of these assets so you get the maximum amount of return possible, right? And I'll come back to that. the other investor is the same thing, but the difference is that this is an investor that is There's more pro-risk, so he's gonna end up with assets that are much more hit-risky than the other one. One thing I didn't mention is that it's not only when you put all of these together, it's not only the individual assets, but it's also how they work with each other. So the, when we talk about correlation, correlation is important exactly because of that. Why? Let's say for example, you have two assets, both very volatile, right? Let's say you have both assets that, you know, they go, they could Go up or down, you know, they could go up fifty percent in one, one year, they could go down thirty percent in one year. So very volatile assets, right? But let's say that when asset A goes up, asset B goes down, and when asset B goes up, asset A goes down, right? So what happens there is that one asset actually behaves a little bit like an airbag to your portfolio, cushioning a lot of these volatilities. So two assets that are very volatile, you put, when you put them together, you may actually end up with very little Because your overall return is gonna, your overall volatility is gonna be much lower. So when I say, \"Wow, you know, I have a lot of, issues with Markovitz model, you know,\" and we can get into them, but one of the advantages that it has is that it easily, you can easily visualize, how these things work when they are together, right? And when you construct portfolio. So optimization is the process of finding what would be the, the, the- The ideal allocation of these assets that you already picked for to satisfy a given con-condition. In this case, is your risk tolerance, how much risk you wanna take. So just very quickly, I'll go back to, some of the, the, the issues that the Markowitz model has, which I think are important on, on this context. So the first one is that it's based a lot on historical returns, right? So it will look at the, the past of these assets, and with that, it's gonna try Try to get an understanding of what kind of return and what kind of risk each of the assets are. So when you look at historical returns, you of course have issues because, you know, the future, as we said, the future probably isn't gonna be like the past. So there's a model that is very bad in predicting discontinuities again. So if you have an asset that, you know, had very low volatility, but then all of a sudden start having more volatility, or an asset, which I'll get to it, that it doesn't have the distribution of returns, It doesn't work that well, right? So going to this point, so it also assumes that the returns are normally distributed. What does that mean? That means that they are, they have that, that bell curve shape that, we know, right? So you have most of the returns concentrated in the middle and you don't have a lot of tails, right? Guess what? Bitcoin is an asset that's, you know, exactly the opposite. We have fat tails, so we have very little, we have actually have a lot of returns in the middle, we have very little returns in In, in terms of, of returns in any period of time that you pick. The other thing that the model, assumes is that investors are rational, right? And that information is, a-across everybody in the, in the same way. Well, we've seen a lot of irrationality in the markets recently, right? Meme stocks, all of that, that, in a sense it is rationality because people are trying to optimize something, but it is irrational for the, this model, right? In the way that the model will see. And the other thing is that Is widespread, and I would say that probably, the, the Markovitz shouldn't have written that it's widespread, because it is widespread. There's a lot of information today. Anybody that wants could read about Bitcoin for, you know, hundreds of thousands of hours, today. There's, more than ample, information out there. The problem is that there's no willingness to, to actually access that information, right? So even though information is out there, it's not distributed equally yet. as I mentioned the example Right? my friend, he had all the information out there to learn about Bitcoin, right? I actually, so I could take the horse to the water, can make it drink, right? So I took him to the water, he didn't drink. I had to put a little bit of sugar in the water, then the horse drink the, drink the water, right? So information is widely distributed, it's just not accessed, I think, in, in the, in the right way yet, because it is, a novel concept, it is something different as to your point, at" }, { "speaker": "rapha_zagury_cio", "time": "45:54", "start": 2754.07, "text": "Bitcoin in to actually show how these things work within the context of, of portfolio allocation. The other thing that we see, and again, you know, anybody can run the numbers on Akamur portfolio and then they can see this, but, we have a tab there for optimization. So I optimize, you put in the assets that you have, and then it'll go to this optimization, and then it would spit out like with different variables. So let's say we optimize for risk return, right? So you're having the highest amount of return for any risk that you- Take, let's say you optimize to have equal risk contribution, so every asset i kind of like adds the same amount of, risk to the portfolio, and we run all of these and we get to, to certain levels. And what we've seen is that a Bitcoin allocation is present pretty much everywhere in pr- in every different model, right? And it is also present in every level of risk, from the le- less adverse investor to the extreme, risk tolerant investor, all of them should have some kind of Bitcoin allocation to their- To their portfolio." }, { "speaker": "stephan", "time": "46:55", "start": 2815.29, "text": "Yeah. So basically, adding Bitcoin to your portfolio, even if it's only a small percentage, improves, in most portfolios in terms of, we would say risk-adjusted return. Yeah. Right? I think that's probably the, that's how we could summarize that. I guess, actually, would you mind explaining what is risk-adjusted return just for people to, who aren't familiar with that? Yeah," }, { "speaker": "rapha_zagury_cio", "time": "47:16", "start": 2835.78, "text": "absolutely. So the way typically risk-adjusted returns are measured is what we call the Sharpe ratio. So the Sharpe ratio does, very simple, it Return, right? It would take out the risk-free and then it would divide by some measure of volatility or risk, right? So what you're seeing is how much you're getting of return in terms of the risk that, that you're taking. So you wanna optimize that, you wanna have as much return as you can for the same amount of risk, right? So let's say we have two baskets, right? And they all have twenty percent volatility, but one has a historical return of forty and the other has a historical return of twenty, right? One is gonna have a Sharpe I have a Sharpe ratio of one. Forget about risk-free for now, right? but risk-free is also important because it goes back to what we were discussing before, right? which is if you have a risk-free rate that is manipulated in some sort of way, you are gonna end up with Sharpe ratios that are also indirectly manipulated, right? The results aren't exactly what you see. And we see a lot of this in, like for example, this, this investor that was running short-term bonds, he saw that the Sharpe ratio, you know, depending That's because here you're talking about very low returns, right? So if you increase your shar-- your, your risk-free rate a little bit or, or reduce a little bit, you end up either having very good Sharpe ratio or negative Sharpe ratio in some cases, right? So manipulation also has an effect here, but the point is exactly that, that you're, you're trying to adjust the level of re-- the, the, the return that you could take by the level of risk that you do. So, one of the things that will come out of this is what we call So what the efficient frontier is, is you're gonna have on the x-axis different risk tolerances. So on the zero, you're gonna have somebody that doesn't wanna take any risk whatsoever, and of course, you know, you shouldn't be investing in anything. And then on the other spectrum, on the end of the, the x-axis, you're gonna have somebody that may be willing to take, you know, a volatility of fifty or a hundred percent or whatever it is. And then you draw a, a curve that would actually find for every given level of return Of risk that you want, the, at the level, the optimal level of return that you can achieve by mixing these different assets, right? So let's pick Bitcoin and bonds as extreme examples, right? So the cl-- the investor that doesn't wanna take any risk, he's gonna have ninety-nine point ninety-nine percent of his portfolio of bonds and point zero one percent of Bitcoin, right? On the other spectrum, the investor that, you know, is young, as I said, wants to take a lot of risk, right? Has a long time horizon, he may say, \"Screw bonds, I wanna buy Bitcoin, it has a hundred percent Bitcoin, so these are two easy extremes. But what about the guy that is in the middle, right? That says, \"Okay, I wanna take ten percent annualized volatility. So what the efficient frontier does is that it spits out what the right combination between Bitcoin and bonds would be so that he can optimize and have the maximum amount of return as possible for that risk that, that he's taking." }, { "speaker": "stephan", "time": "50:15", "start": 3015.0, "text": "\" Excellent. And the risk tolerance conversation also comes up when people are thinking about DCA versus lump sum, right? And as I- I mean, the way I sort of explain it for people is I'll say, typically, you might think about taking an initial lump sum and then set up an automated purchase after that, or just regularly accumulate. And I think that's probably-- that's what makes sense for a lot of people. But you have to think about your own risk tolerance and deeply think about that, because a lot of people can be very gung ho. They can say, \"Oh, yeah, I'm willing to take eighty percent drops,\" but actually, once an eighty percent drop happens, if you end up selling, that could" }, { "speaker": "stephan", "time": "50:54", "start": 3054.07, "text": "Bit on your thoughts around lump sum versus regular accumulation." }, { "speaker": "rapha_zagury_cio", "time": "50:58", "start": 3058.03, "text": "Absolutely, this is, you know, Sam and I, when I, when Sam Callahan, when I, when I joined, the first long conversation that we had was around this, like, you know, 'cause this is a question, as you can imagine, we get a lot from our clients because Swan is, has a product that, you know, incentivizes clients to buy Bitcoin as they go, they can DCA monthly, daily, however they want, right? So it is a question that we get a lot, at Right? So when I'm thinking about DCA versus lump sum, I'm thinking about the following scenario. You, you have capital, capital is available. So you have cash in your fiat account, you have, you know, ten thousand dollars in your fiat account. At that point, you need to make a decision. Are you gonna buy the ten thousand in Bitcoin or are you gonna lag in, you know, the ten thousand along a week, a month, a year, whatever it is? So when we're talking about DCA and lump sum, that's the difference. It's different than the, Every month he's gonna have, or every two weeks, gonna hit his paycheck right into his account, and then he buys some Bitcoin. So this guy is just doing a series of lump sums. He's not exactly, at least in our definition, he's not exactly dollar cost averaging, right? So when you talk about, oh, if dollar cost averaging, because I'm actually buying every week, what you have to first define is that, okay, is your amount at risk? is the amount that you had available, the amount that you are allocating, or you had more available and you decided not Investors need to have is the one that you mentioned, is like from the amount that I have available and that I'm gonna have available, how much I'm gonna be putting Bitcoin in. And this answer is critical so that you can withstand the drawdowns. After you make that decision of what is the right amount of capital that I'm gonna be deploying, then in, in the given the time, right? Then you need to make a decision of should I allocate that right away or should I do that through time, right? the answer is, and I think it's obvious, is during bull Or as you need to allocate as quickly as possible during bear market, it's probably better to, to DCA along different time. But then, I told you I don't predict price, so I don't know if we are in a bear market, in a bull market, I don't know if we're gonna turn right, and I don't think anybody can, because, you know, we may have another FTX tomorrow, we may have, you know, a large sovereign wealth fund that just comes out and declares that they have Bitcoin and then now as their exposure, right? And two things will have" }, { "speaker": "rapha_zagury_cio", "time": "53:24", "start": 3204.25, "text": "So on very long period of time, lump sum beats DCA. There, and that was in the beginning for many people when we came out with that conclusion was a little, you know, surprising. Like, you know, DCA is why averaging in is probably better because Bitcoin has these wild drawdowns, this wild volatility, right? So why is that happening? And, you know, and so we dig into the numbers. And another thing that it's again, it's a, almost a little intuitive, but it doesn't come out when you have the- Discussions this year, because it's different, is Bitcoin does, you know, pretty much two things. It's either sideways or going down, right, which is eighty percent of the time, or it's going up very quickly and very explosively. So if you actually look at the returns of Bitcoin, remember we talked about the bell curve, it's not a bell curve, right? You have these wild fluc-- mainly on the upside, which is, you know, surprising. Like so we have these explosive up moves. We did some analysis like looking at very small blocks of time. So if you Like, excluding a period of five years, right? You take out the top ten three days move, instead of having a positive return, you actually have negative return Bitcoin, right? Because these moves were really large, very quickly, which is something that we also tell clients, they're like, you know, we've had, you know, particularly I think earlier this year, a lot of people are, \"Oh, I shouldn't be sitting on the sidelines, I should wait. Bitcoin's gonna go to X, Y, Z price, right? It's gonna drop a lot, and" }, { "speaker": "rapha_zagury_cio", "time": "54:54", "start": 3294.11, "text": "Your face, and if it does, you're not gonna get in, into that, there, you're actually gonna wait again for it to drop, right? So there's a lot, and going back to your point, there's a lot, I think, of human behavior that needs to be managed on this. So, going back to the safe versus lump sum, the first thing is determine what is the amount that you can put at risk, that you can live with it, that, you know, you're not gonna be needing it in six months, that you're not Right? And then if you have more capital available in, in a week, in three weeks, in a year, whatever it is, because you sold the business, because you, you know, you're receiving your paycheck, whatever it is, then you make that decision again of how much you're gonna allocate it at that point. But historically, going back to the conclusions, if you actually, look in a very long period of time, lump sum tends to be much better than, than DCA, and it is significant. It's not, it's not even close, right? but Verify, that's another thing that, you know, we've built on the Nekomodo portfolio website, people can go in and simulate different time frames, different DCA strategies. They can say, \"Oh, I'm gonna buy weekly, or I'm gonna buy monthly, I'm gonna buy during three weeks, I'm gonna buy during, you know, I don't know, twenty-four months, whatever it is,\" and then they can compare what would have happened, and then they can start, they can start there, they can say, \"Oh, let's say I did that one year ago Risk. there's the flip side of that, as I said, DCA tends to perform better in bear markets, and a very good illustration of this is if you look, somebody that actually bought bi-bitcoin, you know, on a daily basis from the all-time high until today, they're actually making money, they're up something like fifteen percent, right? So think about that, the guy bought at sixty-six thousand, kept buying every day, right? He's actually making money now, while somebody that lump sum at the all-time high is down, you know, more than Fifty percent. So, you know, the, the, the answer is, you know, there is no magic formula here. You have to analyze the numbers and come to your own conclusion of what kind of risk you are gonna be taking in terms of, you know, either, 'cause there is a risk, right? Either Loomsami or, or DCA at the end of the day." }, { "speaker": "stephan", "time": "57:12", "start": 3431.74, "text": "Yeah, and I think the other way to motivate it is Because some of Bitcoin's returns are so dependent on their top ten days in the year, it's important to be allocated, to have an allocation, because if you're not in at that point, you miss the upside. So I think that's probably the other easy way to motivate that point, but I think the main thing is if you're gonna be in here, you need to have a stomach for the long haul. You need to have a stomach to kind of take some draw-downs, as many of us who've been around for a while have just had to, you've had to withstand. And but I think you build that over time. Hardly, but I think" }, { "speaker": "rapha_zagury_cio", "time": "57:44", "start": 3463.5, "text": "very hard, Stefan, because, hardly you're gonna have, you know, days of glory, and you're gonna have months and years of pain, right? That's the nature of, of hardline. You're Moments of glory, right? It felt good. You read Bitcoin Twitter, go back, read Bitcoin Twitter, the, the messages at that time, right? Everybody's super euphoric, hyperbitcoinization is happening, right? And, and then we have this whole period where people capitulate, get out of Bitcoin, you know, aren't very happy. It's the nature of the asset, you have to live with it, right? And you have to have the stomach to live with that." }, { "speaker": "stephan", "time": "58:22", "start": 3501.94, "text": "I, I think, I think that's right. You just have to build your" }, { "speaker": "stephan", "time": "58:29", "start": 3508.95, "text": "The Schrodinger model, because part of that is having a thesis about what you think Bitcoin will someday be. So do you wanna explain what's the Schrodinger model that you, have, come up with? Yeah. And, just explain a bit about that." }, { "speaker": "rapha_zagury_cio", "time": "58:43", "start": 3522.85, "text": "So one of the things that bother me a lot when I created, like, because in terms of tools that I created, first I created the, the, what we just discussed, the portfolio optimization, those tools were done, you know, from the past, from other things that I've done, right? But one of the things that always bother me is that it's backward-looking. So we're always looking at the back, what happened in Bitcoin price return, what happened, you know, with these assets return, and when you're trying to optimize for the past, again, we, we discussed, there What can I look that it's a little bit, it's not ideal, but it's a little bit more forward-looking, right? And then I was listening to, to Michael Saylor on one of the podcasts that he did, I think was late last year, Bitcoin as property, right, where he compares Bitcoin to, to real estate and, sees what could, you know, and he kind of like- Tries to explain what could happen if we capture part of the monetary premium that it's now sitting in real estate, right? And then he also goes through the fundamental arguments of why Bitcoin is better than real estate, and again, why this de-monetization of real estate should happen, right? So I kind of sat with that and I was like, \"Yeah, but this isn't only true in real estate, we see that in other assets, right? we see that in stocks, we see that in bonds, we see that in cryptocurrencies, right? We see that ac-across the board Then I gave one step more and I said, okay, so what happens if Bitcoin demonetizes all of these assets or some of these assets, and let's say it also doesn't happen today, but it happens at some time in the future, right? How can I think about that? so that was the first inspiration that I got. The second one was, as I said, you know, I traded a lot of derivatives. There is a model in derivatives that is very well known, the Black Scholes model, where basically what you're doing, so it's a model to price call options and, and put options on different assets, right? So you have an option to buy the S&P in one month or in two months, how do you know if that option should be worth a dollar, two dollars, ten dollars? So what the Black Scholes model is, that For that, option today. And what it does, very simplified, is that it will look at the probability of that option being in the money, being, being exercised, and also discounts it by time. So I got that same concept and brought, brought into a val-valuation methodology for, for Bitcoin, right? but before that, let's talk about, you know, the, the, the monetization of assets and why, that's a very important component. So we talked about rates being low for a very low period of time, and that created all kinds of wrong incentives and all, all kinds of, I think, wrong price signals in the market. Let's stick with real estate. We can talk about other assets, but let's stick with real estate, 'cause there's ample evidence that this happened, in real estate, right? So the amount of homes that are out there that are second homes or investment homes, or people are just buying not for the, their, their social utility of homes, of being in a home, right? But they're Or storing their value or thinking about, you know, a way to store value in the long term, it has increased through the last decades and continues to increase, which, you know, I don't know if ten percent of the real estate market is, i-i-is, you know, attributed to kind of like monetary premium, I don't know if it's ninety percent, it's somewhere in between, right? But for now, let's keep that as a concept and, and tomorrow we can change the assumptions later. I'll give some numbers, like, you know, we know that, forty percent only of the homes in the US are owner occupied, right? So that gives an idea that there's large amount of properties that are not. Also, the volumes that we see in real estate investment trusts in the US keep going, going up, which again, it's evidence that people use these as a way to store value in the long term. There's a whole separate discussion around is, you know, is really, real estate a good store of value in the long term, which I don't" }, { "speaker": "rapha_zagury_cio", "time": "01:02:45", "start": 3765.27, "text": "For a sec, I think, you know, real estate is a shitcoin, right? You know, you, you don't own it, there's like several problems with that, maintenance is-- I was a real estate investor in the past, you know, I owned like, you know, more than a few properties, and some of them gave me headaches that I really don't wanna have anymore in, in my life, right? Bitcoin, the only thing I need to worry about is to see if, you know, I check my node from time to time, see if the blocks" }, { "speaker": "rapha_zagury_cio", "time": "01:03:15", "start": 3795.79, "text": "Much, the government isn't gonna be coming after it with more taxes, right? I mean, they may, but, you know, that's again a separate discussion. real estate, I think there's massive issues, and I think people are kind of blinded, because first of all, if you imagine, so when you head on your house, right? You get, you walk through your house every day, and then your front door, you have a ticker, a price ticker of how much your house is worth that day, versus the day before, right? And," }, { "speaker": "rapha_zagury_cio", "time": "01:03:45", "start": 3825.29, "text": "Of Bitcoin, of your property, they can sell a piece of your property, right? I guarantee you wouldn't be able to withstand that volatility, right? Because, the, the instance where I had like a water leak and, you know, the house was, full of mold, right? The price would have collapsed, right? People would only be willing to buy the house at like half of the price that actually the house next door was being sold, and I would see that in my door, I would panic, right? But people don't see it, like prices are actually not shown" }, { "speaker": "rapha_zagury_cio", "time": "01:04:15", "start": 3855.25, "text": "Masquerade a lot of the factors in terms of, of what you're seeing, but if they did, it's" }, { "speaker": "stephan", "time": "01:04:19", "start": 3859.51, "text": "illiquid," }, { "speaker": "rapha_zagury_cio", "time": "01:04:20", "start": 3860.34, "text": "it's very illiquid, right? And also that part of the illiquidity, of the promise of liquidity is exactly that but we know that there is, you know, it's a massive market, it's three hundred and twenty trillion dollars, globally, right? Estimated, and again, the number can, can change up and down a little bit depending on what you read, but it's a massive market. It's one of the, probably the one of the largest markets in, in the world, right, along with currencies. so I look at that as, okay, so what happens? It's a very large number. What happens even with a very small, small probability, right? Let's Maybe with a ten percent probability it captures ten percent of this market, right? and then you run that number, you'll see what it was, right? And then I did this across all different asset classes. I did it for, for stocks, for bonds, as I mentioned, for real estate, gold, silver, and you can add any asset you want, you know, if you think that oil, for example, is a mon-- is monetized, bad example, but any other commodity, you could put it in the model and can, you can run the A couple of things that are interesting when we run this, this, first of all, is that, you can put very low probabilities, it's also being a Trojan horse, for conversations with, with Norm, is because, you know, a lot of people will say, \"Oh, I don't think this is gonna work,\" and it's always people talking about absolutes, right? What bothered me a little bit about, you know, the talk that, even Saylor did, is that it's an absolute. He says, \"Oh, this is gonna happen. We" }, { "speaker": "rapha_zagury_cio", "time": "01:05:53", "start": 3953.83, "text": "On the other spectrum, somebody like Dan Pena that keeps yelling Bitcoin's going to zero, Bitcoin's going to zero, right? what this model does is like forget about the extremes, let's put a probability into it. So we put a probability, right? And what you find out is that even at very low probabilities, even at very low, very high time horizons, thinking, \"Yo, I, I think, real estate's gonna be demonetized, demonetized by Bitcoin with a ten percent probability in twenty years' time,\" that still results in very large Fine. our base case, with what we ran there, and again, our-- I can guarantee you our base case is wrong, right? But, anybody can look at that and then they can get to their own estimates of, what, what the probabilities are, what the time horizons are, and also what the discount rate is. But our base case puts Bitcoin at three hundred and eighty thousand dollars today, so a fair value would be today around three hundred and eighty thousand dollars, and as Bitcoin captures more of that demonization over time, price should be going up, Price in this base case is a little bit more than three million dollars, but anyway, people again can, the, the bullish case is, Bitcoin should be worth four hundred, two million dollars today, and it should be worth like eight million dollars in, in the future, which means it will demonetize vast majority of these assets, So I was saying it's, it's kind of like a Trojan horse, because I go to these, to, to the advisors, for example, and I say, okay, you don't think Bitcoin is gonna work out, but some scenario it will. What do you think is the probability? And it's amazing to see that these guys will come up with probabilities that are even more bullish than mine. They would say, oh, I think it's five, ten percent, and you plug that in the model and say, okay, if you think that Bitcoin should be worth today five hundred thousand dollars It's not ten percent, maybe it's a little bit less, but what that shows is that, you know, I think people are having very hard time in conceptualizing what the, you know, the good outcome, the extreme outcomes really are. So the outcome of hyperbitcoinization, if it happens, even with low probability, it represents that Bitcoin should be worth significantly more. I, w-we've heard a lot that Bitcoin is, you know, the, the most asymmetric bet that you have today. This proves it, like, you know, because it is very asymmetric. Like if you're wrong, you know, your downside, it's, it's gonna hurt. Your downside, you know, could go to zero, but there's so much upside on this asset, right? Through what could happen with the, the monetization of, of other assets, that it's not even close, right? And everybody, again, everybody shouldn't have a piece of Bitcoin in their portfolio just because of that, because it, it does have the, the, the, you know, the, the potential, potential to capture a lot of the premium, i-in other percent that two percent that you have in your portfolio is really gonna make a difference," }, { "speaker": "stephan", "time": "01:08:46", "start": 4126.97, "text": "long term. Right. And then as people start even piecing a small percent, typically what that does is as lots more people are coming into Bitcoin, as we see, it grows the network effect, and then it sort of increases even the likelihood that it does go to that level. So, you know, it's kind of a funny, reflexivity in there. And" }, { "speaker": "rapha_zagury_cio", "time": "01:09:05", "start": 4145.6, "text": "I, I just remember something like, we launched the site last week, right? So, wasn't as, as Twitter a lot of people, and then I mentioned it, and, you know, the thing just blew up. But, Greg Foss was on the audience, so Foss gets, of course, this is pure math, right? So he gets really excited about it, and he, he comes into space and it's like, \"Man, I'm running the num-\"\" And then I ran the numbers and said, \"Oh, listen, if you add Bitcoin to this portfolio, it actually reduces your risk, reduces your drawdown, right? \" And, and then" }, { "speaker": "rapha_zagury_cio", "time": "01:09:42", "start": 4182.28, "text": "Reconcile my numbers and he said, \"Okay, let's, after the call, we'll talk about that, we'll see what's happening, right?\" So, finish up the call, I run the numbers, and what happened was the following. He actually, he created a simulation where he included a one percent allocation to Bitcoin in twenty fourteen, but never rebalanced that. So that one percent actually became the portfolio after a while. And of course, now that the, you know, that one percent became close to a hundred percent, you are gonna face the large drawdowns of" }, { "speaker": "rapha_zagury_cio", "time": "01:10:12", "start": 4212.22, "text": "And you're gonna have a ninety percent drop down, and you're gonna be happy that you had it, because it just means that your portfolio is doing much better. so just," }, { "speaker": "stephan", "time": "01:10:21", "start": 4221.65, "text": "Yeah, I mean, it's, it's right. I think anyone who was around in the early days and didn't rebalance Bitcoin became a large percent of their liquid net worth, let's say. and I, one other area to touch on is, altcoins or as I prefer to call them, shitcoins. what's the problem of diversifying into altcoins? 'Cause I know this is another area that you actually ran some of the numbers, right? Because a lot of people come into this, maybe they're not thinking about the tax consequences, they're not thinking about fees, they're not, they're just looking at kind of, very specific outliers, and then- Hanging their hopes on that. So what's, what does your research say about, quote unquote, diversifying into altcoins?" }, { "speaker": "rapha_zagury_cio", "time": "01:11:02", "start": 4262.25, "text": "Yeah. You're not really diversifying, right? So I'll, I'll get that." }, { "speaker": "stephan", "time": "01:11:06", "start": 4266.5, "text": "Diversifying. You're diversifying." }, { "speaker": "rapha_zagury_cio", "time": "01:11:08", "start": 4268.3, "text": "That's the TL-D, TLDR, right? But, so you tell me what we ran, because that's also a question that I get a lot, right? And it, it really hurts like every second guarantee we're gonna see, we'll see this, this cycle again, right? Is people go To thinking they are experts in, in cryptocurrencies or shitcoins, right? And buying like the most obscure things that you, you could see, and that happened like in a matter of months, depending on some, some of these guys, right? And that always bothered me. So what I did is I went back to twenty sixteen and downloaded the historical data from all of these different shitcoins, right? imagine like from the most obscure ones to some that we know, right? Like Dogecoin, all, all of that, and ran the numbers. So okay Let's compare them with Bitcoin and let's see, you know, if you saw in twenty sixteen, look at the performance of Bitcoin. This is on Twitter, I have a Twitter thread on this, and there's a chart showing this. I think it's good to visualize on the chart. So the result, the end result is the following. So from twenty sixteen until now, if you bought, it's around eight thousand different, coins, right? Five thousand roughly don't have price anymore, so you can't find the price. Their price, their- So you got zeroed. They, they, yeah, they, they're either so illiquid that there isn't a price out there, or just, they just died, right? So they went nowhere, right? from that also, the let me tell you a little bit about the, about the top ones. So the top ones, there are forty ones that actually outperformed Bitcoin through, through that time period, right? And, these forty ones, if you bought them You got forty-six percent more, more Bitcoin. So for every one Bitcoin that you had, you had, now you have one point four six Bitcoin on average, right, from these portfolios. It's also crazy that, you know, I put this out there, first question that somebody asked, like, \"Oh, so what are the forty?\" Because I, I, and I'm not gonna tell you what the forties are, but some of these are really, again, obscure names that you never heard, and I guarantee you never invested on them. But the, the other two thousand something, right? Actually have a price now, right? Taking out the ones that went to zero. On average, for every Bitcoin that you had, you have point zero four Bitcoin, so you lost ninety-six percent of your Bitcoin. So people that are diversifying, I can guarantee you they're not gonna buy if they think, \"Oh, I'm gonna diversify into shitcoins,\" they're not gonna buy the forty that outperformed. They may buy eighty. From those eighty, they're gonna have the forty that maybe they're gonna have the forty that outperformed. Let's say they were very lucky, they Their Bitcoin. And I don't think, 'cause we've seen so many of these things, you know, have a cycle of coming out, you know, being the, the latest thing, saying that they have a re-something that is re-revolutionary, that is gonna take over the world, right? And they skyrocket and then they collapse. On the chart, you can actually see the ICO craze very easily. You see, you know, all these tokens like outperforming Bitcoin, you know, through two thousand, seventeen, two thousand eighteen, and then on the right Of these going to zero pretty much and die. And then one thing that gives me hope is that if we actually look at this last cycle, you see that the crazies actually, you see less of these shitcoins actually going much higher. You see a lot of them just being already like in the bottom, not even taking off at any period of time. but then the most interesting part of this chart is looking at the, the right side, the bottom. It's like all the shitcoins are dying there, like you have this dense amount of, that's a shitcoin cemetery. There, there, like they're all going to die at that corner there of that chart, right? so there is no diversification. the-- I also like to talk about the fundamentals here, because a lot of people forget that all of these, right? If they are gonna be in this market, they need to be open source. There's no-- there isn't a single coin that is gonna be out there that is not open source, because people aren't gonna buy it, right? Or maybe they will, but vast majority of them are open source, so the code is open to" }, { "speaker": "rapha_zagury_cio", "time": "01:15:16", "start": 4516.82, "text": "Right? That came up with something that is so revolutionary, so good. We have very good developers in Bitcoin, there's a lot of incentives in Bitcoin to adapt that technology, right? So eventually, that technology is gonna be adopted and it's gonna just plug in my laptop here, right? And it, it is gonna have, an impact, on Bitcoin, 'cause that, again, if it is a good technology that can be copied, and it makes sense to be copied, it will be copied, right? and unless something happens very quickly overnight, something that- It's absolutely out of the blue, revolutionary, which I guarantee it's not in any of these coins, right? there's no reason to buy them up until then, they're just testnets for, for Bitcoin at the end of the day, right? We've seen this happen, like, you know, there are some examples like SegWit when it happened in Litecoin, was great to see that it actually worked and then it could be implemented in Bitcoin later, right? So a lot of these, if you think you're, you're gonna be early enough to determine that, you know, Pop it into Bitcoin, I think people are just wrong. That's not gonna happen, right? we will need to change things to change significantly from where they are today, and who knows, maybe in the future, Bitcoin becomes so ossified that it's hard to implement changes and something comes up, but we're not there, at this point, we're not even close, right? so just keep that in mind as well, because the fundamentally there's no reason to invest in these coins. They are gonna have extremely high correlation to, to, and you see that to Bitcoin, You know, Bitcoin pric-price comes down, they all collapse and they go down significantly more, yeah, so they're not only leverage plays, it's worse because when they come down, they come down significantly more than when they go up, right? so there's no diversification in altcoins, you're actually, gonna end up with something that is worse than just buying Bitcoin." }, { "speaker": "stephan", "time": "01:17:06", "start": 4626.43, "text": "Yeah, unfortunately a lot of people fall for this, and I think what happens is it's, it's similar to when people are gamblers and they love to tell you about their big wins," }, { "speaker": "stephan", "time": "01:17:16", "start": 4636.66, "text": "Every single thing, and they're not telling you about all those losses. And rea-- in reality for most people, now, okay, maybe there's a few shitcoin insider, shitcoin elite people who maybe they're making money, they're making bank, but the most people just end up losing money on these things. And we also have to think about for some people there could be tax implications, there could be fees, there could be all these other implications that make it even worse. So the reality is for a lot of people, they end up de-verseifying and not diversifying." }, { "speaker": "stephan", "time": "01:17:47", "start": 4667.0, "text": "but, we should probably wrap up here. So, Raphael, where's the best place for people to find you and to find, your work?" }, { "speaker": "rapha_zagury_cio", "time": "01:17:53", "start": 4673.58, "text": "Yeah, so the most of the stuff I mentioned is on nakamotoportfolio dot com. on Twitter, I'm alpha zeta with two A, so alpha A zeta, so they can find me there as well. I'm always posting, you know, the way we do these, any of these research, that it usually goes first through Twitter. So, I'll make a Twitter thread, I'll post it And then make adjustments and then launch it on the website, launch a research report, and, and then launch the code as well. but again, people can find me on Twitter and, happy to, to answer any questions, DMs, hear any, any kind of input on the models. That's, that's what we want. This is, end of the day, this is all to the com-community, right? And, change these, modify, send a PR to, to the GitHub, whatever you want. That's what we wanna see." }, { "speaker": "stephan", "time": "01:18:42", "start": 4722.72, "text": "Fantastic" }, { "speaker": "stephan", "time": "01:18:46", "start": 4726.64, "text": "Been, posting about Bitcoin for years, a lot of great stuff, so make sure you follow him. And, Rapha, thank you for joining me." }, { "speaker": "rapha_zagury_cio", "time": "01:18:52", "start": 4732.46, "text": "It's my pleasure, thanks Stefan, great to be here." }, { "speaker": "stephan", "time": "01:18:55", "start": 4735.58, "text": "If you found this episode interesting or educational, make sure to share it with family and friends so they can also learn about the Nakamoto portfolio and go play around with the website. Also, get the show notes at stefanlivera dot com slash four seven five for this episode. Thanks for listening, and I'll see you in the Citadel." } ] }