Plan B (@100trillionUSD), operator of a well known pseudonymous twitter account joins me for discussion on modelling the incredible value of Bitcoin. Don’t miss this discussion on data modelling, finance and investing in Bitcoin!
- Influences in terms of Bitcoin
- Modelling Bitcoin’s digital scarcity
- Impact of the halving
- Challenges and problems with modelling Bitcoin
- Finance and Investing theory and practice applied to Bitcoin
Plan B / @100trillionUSD Links:
- Twitter: https://twitter.com/100trillionUSD
- Modeling Bitcoin’s Value with Scarcity – https://medium.com/@100trillionUSD/modeling-bitcoins-value-with-scarcity-91fa0fc03e25
Podcast Transcript (Sponsored by GiveBitcoin.io):
Stephan Livera: Hi and welcome to the Stephan Livera Podcast focused on Bitcoin and Austrian economics. Learn the technology and economics of Bitcoin by listening to interviews with Bitcoin’s best and brightest.
Stephan Livera: My guest today is a pseudonymous account known on Twitter as PlanB or 100trillion. Now, he has been doing some really interesting graphing work and charting work, so I gave him the message and he was keen to come on. This is actually his first podcast episode, so a very special one here for you, guys. Here is the interview.
Stephan Livera: PlanB, I’m a fan of some of your graphing work that you’ve been doing on Twitter. You’ve been really setting it alight lately. First of all, welcome to the show.
PlanB: Thank you, Stephan. I’m glad to be on the show.
Stephan Livera: Obviously, I know you’re a pseudonymous account, but let’s just start with a little bit of background on you, and I think maybe we’ll start with: what’s in a name? Why the Twitter handle, @100trillionUSD? Is this your theory for the longer-term value of Bitcoin?
PlanB: That’s a good question. PlanB actually refers to an alternative plan for quantitative easing and negative interest rates. Quantitative easing is the essential bank strategy for printing money and saving banks and economy; but we don’t know how it ends, it’s really uncharted waters, and it might be handy to have a PlanB, so that’s what the “PlanB” stands for. The 100trillionUSD is a reference to the Zimbabwe $100 trillion note during the 2008 hyperinflation there. Since quantitative easing, printing of money, could lead to hyperinflation, I thought that would be a good mark to put up there as a reminder why Bitcoin is here.
Stephan Livera: Nice. Very fitting. Very fitting. Obviously, I know you’re a pseudonymous account so I don’t want you to dox yourself, but maybe just a little bit of background, whatever you’re comfortable to share, perhaps just that you work in finance.
PlanB: Sure. No problem. I have a background in legal and economics, and I worked all my life in traditional finance, and mainly with a focus on quantitative investing, so analyzing models and investments; and also in structured finance, so asset backed securities, residential mortgage backed securities, and collateralised debt obligations; in short, the financial engineering part of an institution. Currently, I work for an institutional investor as an investment manager where we have a big balance sheet, a multi-billion dollar balance sheet, and I analyze, model and source assets for them.
PlanB: The reason to be anonymous, apart from opsec reasons, maybe also that I would like to focus on data and facts and logic, and it shouldn’t matter who I am for that discussion. I think Satoshi gave a perfect example here.
Stephan Livera: Fantastic. Yeah, I totally agree with that. Thanks for that. You’ve shared that you’ve got basically a relevant background to what you’re doing in terms of charting and showing some of these different quantitative approaches on how we can think about what is the longer-term value on Bitcoin, and so on. Let’s talk a little bit with your general philosophy around how do you think? What’s your guiding Bitcoin investment basis?
PlanB: Actually, how I got into Bitcoin was 2013; five years into quantitative easing at zero interest rates, or at least low interest rates. I was searching on the internet for a QE hedge or arbitrage opportunities regarding to quantitative easing, and that led me to a website, ZeroHedge. You might know it.
Stephan Livera: Yes, classic.
PlanB: Yeah, it’s a classic. There was this article about Bitcoin with a reference, of course, to the whitepaper, so I read the whitepaper end of 2013 and I was hooked from the start. I think it’s a real piece of art. It’s deep, it’s fundamental, and yet simple. I read all Satoshi’s emails and posts after that from the Nakamoto Institute, and followed the references that he made in the whitepaper and in the mails to Adam Back, Hashcash, to Nick Szabo’s work. I think I read it all. It took a while for me to invest, though, in Bitcoins. Since 2013, when I started reading the whitepaper, Bitcoin was $100; and when I was finished reading, two months later, it was $1000. With the price going up 10x, I thought I might wait a little. I ended up waiting until 2015 to make the first investment.
Stephan Livera: Wow, yeah. That’s an interesting point because what normally happens… and I suppose this is probably because you have a bit more of a professional finance background… but many retail individuals who find out something is going up, they might think, “Oh, quick. I’ve got to buy some now,” but it sounds like you actually had a bit more of the patience to wait for a good buying opportunity.
PlanB: Yeah, exactly. Fear of missing out, the FOMO. I’m not immune to that feeling, by the way, but I learned to protect myself; that’s true. Now, that we’re at it, the feeling of the end of 2015, it feels very much like today after an all-time high and after a big bear market, so I’m very excited about today.
Stephan Livera: Fantastic. Who are some of your influences in the Bitcoin world? I mean you mentioned obviously Satoshi, Nick Szabo, Adam Back. Any others?
PlanB: Yeah, absolutely. Maybe my general view that I got from Adam Back and Nick Szabo, and Satoshi also, was that it’s all about the digital scarcity thing. I see Bitcoin as the next logical evolution in money; it’s just better money, and money is important not because of the financial part of it, but also because like language money is key for human cooperation, so better money leads to better cooperation… more trades, more specialization, better capital allocation, etc… and in that sense, I think Bitcoin will bring the next renaissance, if you will.
PlanB: I came to Bitcoin from the financial investment angle, but what drives me is this better money thing, and I want to see Bitcoin succeed. There’s one quote that I used in the article, of Satoshi, that I really like, and it’s, “Imagine there was a base metal as scarce as gold, but can be transported over a communications channel,” so that’s where he directly refers to this digital scarcity as being very important. The thing is, I see a lot of technical analysis at the moment in Bitcoin that’s really fun, but what I am also very interested in is more fundamental econometric models; that’s also where my expertise can be of value, maybe.
PlanB: A lot of my thinking is also shaped by people like John Nash, the Nobel Prize winner, with his game theory. He has a very clear vision of what money should be. We should look at money like a technology so it can be improved upon, and sadly that didn’t happen very much over the last couple of decades; and also Hayek, of course, with the nationalization of money is something that, from an economist investor perspective, maybe it’s still a bit weird that every country in the world has its own money printed on paper and coins. Yeah, those classics. Maybe I shouldn’t forget Milton Friedman who basically predicted the rise of Bitcoin in 1999 already. Those are big influencers, the classics. Of course, Saifedean Ammous, his book is a real classic; if you’re serious about Bitcoin, you should have read that book. I’m sure you did.
Stephan Livera: Yeah. I think for me a big influence is the Austrian School, and I think one concept that Saifedean has really popularized within the Bitcoin world is this whole idea of looking at things through the concept or through a prism of stock-to-flow ratio; and I notice that from your charting and your analysis, that you have actually incorporated some of that into your own work. Can you tell us a little bit about how you’ve done that and why you’ve done that?
PlanB: Absolutely. Going from digital scarcity to stock-to-flow, maybe that’s one step in between, and that’s the unforgeable costliness, which is the definition that Nick Szabo gave for scarcity. He refers also to the costliness of production. Like gold, it’s very costly to produce gold, and that is a very useful definition because it feeds directly into the importance of a fixed supply, or at least a cap on the money supply, which of course Bitcoin has; but also things like proof-of-work and hashrate which make Bitcoin production costly, and also things like decentralization; because if you can influence the money supply or change it, then you can’t ask yourself if it’s scarce. What Saifedean did, and it was actually the first time I read it, was to make scarcity quantifiable. Since I like to model things, I had to quantify scarcity, and he really explained this stock-to-flow ratio very good, and maybe I’ll explain it a little bit.
Stephan Livera: Sure. Definitely.
PlanB: Stock is the current stockpiles of something… gold, it could be Bitcoin, it could be anything, the current above-ground stockpiles… and flow is the yearly production. Now, if you divide stock by flow, you get the stock-to-flow ratio. You could also do it the other way around, so you could divide the yearly production, the flow, by the stock, and then you get the money supply rate, or in Bitcoin they sometimes call it the inflation rate. So, stock-to-flow ratio is nothing less than, or nothing more than, 1 divided by the inflation rate. If we look at some numbers: gold, for example, has a stock of 185,000 tons, and a yearly flow of 3000 tons per year, so the stock-to-flow is 62, which is really high. Silver has a stock of 550,000 tons and a flow of 25,000 tons, so it has a stock-to-flow ratio of 22.
PlanB: What Saifedean also makes very clear is that other commodities, like copper or zinc, or I’ll use the examples of palladium and platinum: they all have stock-to-flow values of around 1 [corrected], less than 1 [corrected], or slightly above 1 [corrected], but it’s actually very rare that an asset or commodity can go beyond the stock-to-flow ratio of 1, and if it does it gets this monetary aspect; in fact, only gold and silver have stock-to-flow ratios above 1, 22 and 62, and they are really monetary assets so they have value. Because of their high stock-to-flow ratio, their scarcity, whereas all the other commodities also can add value; for example, platinum and palladium are used in catalyzers for exhaust gases in cars, but that’s a value derived from utility.
PlanB: I think that’s the part that Saifedean really made clear to me: that there is a split between monetary assets with a high stock-to-flow ratio; and commodities which have a utility value, but a stock-to-flow ratio of 1 or less. Then, if you look at Bitcoin where it fits into those two categories, it has a stock of 17.5 million Bitcoins at the moment, and a flow of around 0.7 million Bitcoins per year, so it has a stock-to-flow value of 25; that puts it right into the monetary category, and that’s very interesting. That’s also when it struck me that during the all-time high in November-December 2017, the total value of the Bitcoin market was around or similar or even slightly above the total silver market, and that was too much of a coincidence for me: that the stock-to-flow ratio of Bitcoin and silver is almost identical and the market value, so that’s where I got the idea to use stock-to-flow as an input for a model to model Bitcoin’s value.
Stephan Livera: Fantastic. Yeah, I think it’s a really great insight. I think it’s a novel way of trying to model-out the actual impact of this stock-to-flow ratio; and as you were saying, these goods that have a high stock-to-flow ratio above 1, they tend to have some level of monetary premium. Talk us through a little bit around what sort of numbers that the chart is showing… I’m sorry, one other thing; take one step back. Before we get to that, we should just talk a little bit how Bitcoin right now, as you mentioned, has that stock-to-flow ratio around 22, similar to silver. What will be the future stock-to-flow ratio say 10, 20, 30 years out?
PlanB: That’s a good point. What you notice is halvings become very important. So, stock-to-flow ratio increases every day a little bit; but then once every 210,000 blocks, there is a halving of the number of Bitcoins that is created in a block every 10 minutes, so that will double the stock-to-flow ration. The halvings are around every four years. Next halving is May 2020. So, that will double to stock-to-flow ratio to 50… very close to the stock-to-flow ration of gold, 62… and four years later in 2024, it will double again to a little about 100, and then in ’28 it goes to 200, and so on. That really puts us into uncharted waters after the next 2020 halving, which is very exciting, I think.
Stephan Livera: Fantastic. Obviously, this is an audio-only podcast. I’ll advise the listeners, I’ll put the link in the show notes, to PlanB, to your article and to your graphs, but maybe just talk to some of the key points on the graph just to try to help articulate that for the listeners?
PlanB: Should I do the stock-to-flow chart first?
Stephan Livera: Yeah, sure. Let’s do stock-to-flow.
PlanB: The stock-to-flow chart is the chart that shows you stock-to-flow on the x-axis, and market value on the y-axis. It’s a scatterplot, and it has 111 data points in there of all the monthly market values and stock-to-flow values of Bitcoin for the last nine years. When I first made that plot, I saw nothing because I didn’t have log scales on… and you really should look at these charts in log scale or use logarithmic values… because if you don’t, you don’t see the long-term trends. So, if you look at lock scale to stock-to-flow and market value, you see this perfect straight line; when I saw it first it was really like, “Whoa.” Perfect straight line from the bottom left to the top right, from low stock-to-flow and low market value, creeping up to high stock-to-flow, current stock-to-flow of 25, and a current market value of around now $80 billion to $90 billion.
PlanB: What I also did was put a color overlay on the data points, and the color indicates the months until the next halving. Right now we’re about 13 months until the next halving in May 2020, and it has the color green; and the closer we get to the next halving, the color turns blue; and then at the halving, after the halving, it turns red a lot of months until the next halving. What that does is, in the chart, it groups all the data points into three distinct areas: the first area is before the first halving, so there was never a halving before, that’s the period until November 2012; and there’s a second period after the first halving, and a third period where we are in right now after the second halving. I think that’s basically what you see in that chart.
Stephan Livera: Perhaps talk to where the price would be at theoretically let’s say now, and then after the next halving.
PlanB: Right now the model indicates the value of a little above $6000 US dollars. I get that question a lot, “How much does the model indicate at last all-time high?” Now, in November-December 2017 at the all-time high, it had a model price of $3,700 US dollars, so the real market price was really too high with hindsight; and if we go into the future, next halving, May 2020, the model value jumps to $50,000 US dollars per Bitcoin, and of course the all-time high could be 3-10x higher than that, at least that’s what the price was last two halvings.
Stephan Livera: Right.
PlanB: So, it’s a rather conservative value. That number, by the way, is going to increase of course next halving, so the halving in 2024 when the stock-to-flow will be 100, Bitcoin will be priced at around $400,000 each. So, yeah, it goes up really fast.
Stephan Livera: I guess the other factor here to think about is that in practice what happens is markets can swing, or it can overshoot and then undershoot. Can you discuss that a little bit?
PlanB: Absolutely. Maybe when we talk later about the model itself, you’ll see it doesn’t have an accuracy of 100%, of course, because it’s a model; so all those FOMO actions and bull markets and bear fear, it’s all not in there, and you see that in the chart as well. So, the model price is very simple, based on stock-to-flow; but the actual market, of course, where fear and greed are playing out, so it overshoots and undershoots. Usually, what you see… “usually,” I mean the last two times… is that the market overshoots 3-10x the model value, but undershoots 50% maximum, so that’s one of the reasons why I thought, “Okay, if we’re at a model value today of a little above $6000, 50% of that $3000 should be the bottom of current bear market. But, yeah, that’s how I see it.
Stephan Livera: Essentially, what you’re saying then is using the model, we think the bottom would be around $3000. I’m not normally a bit TA price guy, but I am curious about all of this stock-to-flow and halving stuff. Then, I suppose what you’re suggesting is that if the model can overshoot on the next… assuming there’s a next bull run… it would go, so just looking at your chart here, it says Bitcoin and number of blocks per month.
Stephan Livera: You mentioned the $55,000 value. Essentially, if it does overshoot, it can go over $100,000 and then crash down to whatever half of $55,000, so like $27,000 or something like that. Theoretically, at this point that’s what your model is predicting?
PlanB: Yeah, exactly. To be clear, the prediction really is the $ 50,000 for next halving; but we know from the errors in the past that the scenario you described, that’s a very possible scenario, and that’s how I see it as well.
Stephan Livera: Yeah. I suppose the other big thing… obviously, I have to raise this and ask this question. Obviously, everyone discusses this concept of, “Oh, is the halving priced in?” and I think this does speak on where you stand on other debates; for example, the efficient market hypothesis. So, as an Austrian, and even Saifedean himself I think has made a similar comment on this saying, “Look, knowledge is not given to everyone equally, and so we should not anticipate that what might be called the strong form of the EMH, or even perhaps the weak form of the EMH, is not a good way to think about things,” but then there are others from the Chicago School and other schools of thought that may believe in that more. Where do you side on that?
PlanB: That’s a very interesting point. Actually, that’s one of my first charts, the halving chart with the color overlay; it shows the Bitcoin price with the months until the next halving; and you can clearly see from that chart that the halving is not priced in, or at least was not priced in the last two times. So, my best guess would be it is not priced in now, next halving May 2020, but the efficient market hypothesis. It’s kind of weird. It should be priced in, of course. In fact, I’m a big believer of the efficient market hypothesis, or at least it should be used as a first starting point for most people that don’t have inside information, or specialized knowledge, or a big trading room available. The efficient market price is the best price there is, they can rely on that, and that’s especially true if markets are really big and liquid and efficient, and I think that’s true for the Bitcoin, in a sense. It’s like an $80 billion market.
PlanB: It always surprises me how well the foreign exchange differences are arbitraged away immediately, so there’s really not much opportunity to make use of the foreign exchange differences with Bitcoin, so it must be at least a little efficient. So, if it’s efficient, it’s really weird that the pricing is not priced in, so that can mean a couple of things. It can mean that the halving effect isn’t there; I believe it is, but it could be that I’m wrong. It could also be that a lot of new people who are not in the market yet, and who don’t know about the halving, are going to learn about the halving, and in that sense you have an enormous information asymmetry at the moment, and I think it’s very well possible that it’s the case here.
Stephan Livera: Yeah. It’s an interesting way to think of it. I, obviously being more on the Austrian side, I disagree with the idea of the EMH, and I think it takes things a little bit too far. Whereas from an Austrian economic point of view we might view, as Mises said, the market is a process, and people are continually trying to serve consumer… you know, if you’re an entrepreneur you’re trying to serve consumer demands, or if you’re a speculator you’re trying to correctly speculate… and it may just be that right now Bitcoin it’s very poorly understood. Whereas assuming if everyone understood Bitcoin from day one, if everyone knew the exact supply curve… or not the exact supply curve, but good enough that they could predict it out over the next hundred years or whatever… and then that they should take the exact actions now to try and best speculate, or profit based on that. Whereas perhaps in the foreign exchange example, maybe it’s a little bit easier to do that now for the profit straight away, where perhaps if you were to try to apply that with Bitcoin, “What’s the way to profit from that?” you’ve got to buy it now, and does everyone have money available now to buy into that?
PlanB: Yeah. I agree with the Austrian view as well. I think if nobody tries to arbitrage those differences away, they would be still here, so somebody has to try; and there will always be profit opportunities that deviate from the efficient markets, and you should try to trade it, but only if you have a niche, a special edge over others in terms of information or knowledge, etc.
PlanB: There’s one big example that I kept in my head since my university time, and it’s that option that Black and Scholes have invented, since 1973 I thought it was. They had this classic paper, they received a Nobel Prize for it, where they said, “Okay, there is an arbitrage relation between an option on the one hand, and baskets of the underlying asset, risk-free asset on the other side, and they’re the same price. So, if there is a difference between them, you can arbitrage it.” They put that out in the paper, it was out in the open, but I think people had to learn it, people had to digest it and believe it, because it wasn’t used, and you didn’t see prices move right away. So, those were excellent opportunities for both gentlemen to trade. I think they did it for about 10 years without the opportunity going away, so they became millionaires trading their publicly available model.
Stephan Livera: That’s an interesting one. As a finance professional, I’m sure you have heard, or you’ve probably read Nassim Taleb, right? Do you have any thoughts? Obviously, Nassim Taleb is quite skeptical of the Black-Scholes model and suggests that many traders in the real world don’t even use that model. So, I wonder what your thoughts are there.
PlanB: He’s one of my heroes. I read all of his books. He’s a great quant, but also an investor, so he has skin in the game, he even called one of his books, of course, “Skin in the Game.” He’s very good. He’s a very good statistician, a mathematician. I understand what he says about the Black and Scholes model because it assumes normality, which is not present in the current markets; and there’s Black Swans, there is different behavior of market prices, and you should model that with different formulas and models. We will probably get later to that, and this is why I think it’s so very interesting that the model I found, that simple linear regression, can be rewritten as a power law with a fractal dimension that exactly has all those asymmetric dimensions and properties that Taleb describes and loves so much.
Stephan Livera: Yeah, exactly. I guess, just to my mind, I’m obviously not as much deeply steeped into doing statistical analysis, but perhaps Nassim Taleb might view that Black-Scholes model as… I guess in Talebian terms he might say, “These people are thinking it’s a standard world when actually we live in extremistan, and maybe these people who are profiting from that are the proverbial “picking up pennies in front of a steamroller.” What do you think about that?
PlanB: That’s true, but you can speculate with options, so the Black and Scholes model, and you can hedge with options. I think if you hedge with options, you just buy a contract and you pay the price that’s in the market and you’re hedged, so that’s one way; the other way is betting on it, and that’s where you can really go wrong with the Black and Scholes model. I think the 3-sigma events or 10-sigma events are much more frequent than the normal distribution assumes. So, yeah, Taleb really has a point there, but I also think that it works in a lot of cases, and what Taleb does is the next step. It’s a little bit like saying, “Okay, Einstein’s relativity theory is nice, but we have quantum mechanics and that’s much better.” Yes, it is, but at the time Einstein was also very close to the truth. So, I think it’s a logical next step, and certainly a must-read for Bitcoin quants.
Stephan Livera: Yeah. Really interesting stuff. The other big obvious question that I’m sure every listener wants to understand here is the question around sample size. Obviously, we’re very early in Bitcoin, it’s only been 10 years, and we’ve only seen two halvings. Do you have any hesitations about the fact that we’ve only seen two halvings? Can we really predict further out based on only a “sample size of 2”?
PlanB: Yeah, good question, and indeed I get it a lot. Maybe one step back, if we go to the model. Coming from this chart, this scatterplot that we just described, I wanted to make a more formal model to see if there is any significant statistical relationship; and since there was a straight-line visual, I thought, “Okay, let’s do a simple linear regression,” and that confirmed what could already be seen with the naked eye, that there was a statistical significant relationship; so F and P values were very, very low, and it had a nice 95% R-squared, so that gives some confidence in the model. Of course, I also added gold and silver in there, which were totally unrelated markets, but they turned out to be right on this model line, and that to me gives some extra confidence in the model.
PlanB: About the halving, and that there is only two halvings, I think that’s a good point, and that’s why I call it a hypothesis; we’re going to see if it’s right in May 2020, or actually after May 2020 halving. It can be wrong. On the other hand, if we look at the halvings, I use 111 data points, so not only two data points, and the stock-to-flow also rises in between the halvings, so not only at the halvings, then it makes a big jump, but it also rises in between the halvings. For example, if we take the first four years before there was even a halving, so the period until November 2012, Bitcoin stock-to-flow increased in that period from below 1 to 3-4ish around the halving; and if I would have made that model, the linear regression, only in the first four years, it would have been exactly the same. So, I could have predicted the next halving value and the second halving value with only the first four years of data, and that gives me some confidence in the model.
PlanB: Also, if you look at this period between the first and the second halving, 2012-2016, it starts in the bottom left and it ends in the top right, and that’s true for the first four years, the second four years, and the current period we are in. So, I think it’s not only the two halvings and that we only have two data points, but I agree that a third and even a fourth halving would add credibility to the model.
Stephan Livera: Excellent points there. I guess I’ll just summarize that then and paraphrase it in my own thoughts. So, essentially it’s not just the two halvings, but it’s also the movement in between those halvings; and in that case, we’re using month-by-month data.
Stephan Livera: I suppose the other concept that you mentioned there is that perhaps we can draw some level of confidence from the ability to back-test the model… or in this case give the model, in a sense, data only up to say the first four years of Bitcoin, and then try to predict what the model would have predicted the value in the next halving and the time to now… and what you’re saying there is that essentially the model could have given us, even if you only, so to speak, fed it the first few years of data, it could then have given us similar values to what we have seen. Is that a fair summary of what you said?
PlanB: Absolutely. Yeah, that’s true. I agree that back-testing is always very useful. But the limited period, so only 10 years of data for Bitcoin, is a bit of a nuisance here. But, yeah, like you describe it is perfectly right.
Stephan Livera: Excellent. I think the other thing that can come up… I’ve forgotten what book I read this from, but I was very moved by Burton Malkiel’s book, A Random Walk Down Wall Street… and I think others, such as perhaps John Bogle, I can’t remember exactly who… but they have spoken about this idea of potentially what’s called “curve overfitting.” Do you have any thoughts around are we just sort of… or even Nassim Taleb, again; this idea of fooled by randomness. Are we seeing a pattern in the data that looks like a pattern, but actually is not a pattern? What do you think about that?
PlanB: Good point. It could be. By the way, that’s an excellent book, a must read. Malkiel’s Random Walk Down Wall Street, it’s a real classic with lots of stuff about efficient market hypothesis. Yeah, the point, curve overfitting: I’m very keen to curve overfitting because I have a little background in artificial intelligence as well, and there it was an especially big problem because those algorithms can fit everything, also noise, and you only want to model the signal of course. I do think with linear regression, overfitting is not such a big problem, especially since in this model we use only one input variable, stock-to-flow, and there’s only two parameters. If you go to non-linear functions with multivariate analysis, multiple inputs, that becomes a bigger problem; however, there might be other problems, and that’s also why I put the article out. I’d like to discuss all the comments, and especially the critiques and reviews; because I’d like to know, if I’m wrong, because of the skin in the game.
PlanB: One of the things that could be an issue is the data itself. The price data, before July 2010, is really iffy. There were not very much exchanges before July 2010, so I think it’s fair to call all that data “data archeology.” To give an example, there’s this famous example of somebody paying 10,000 Bitcoins for $41 of pizza, so that gives you a price dot; and there is also a very early, I think it’s my earliest data point, 1309 Bitcoins for $1 of electricity. Yeah. So, that’s not really an exchange price, but more a case-by-case price that’s found by data archeology; and it’s important because those early data points with a very low stock-to-flow, very low market values, they have an influence on the R-squared, on the fitness of the function, of course. I think it will probably cost you a couple of percentage points, R-squared, if you leave them out and start modeling from July 2010.
Stephan Livera: All right. So, your R-squared would not be 95%. If you take those two data points out, it would be lower?
PlanB: Yeah. Like 92% or something.
Stephan Livera: For those people who are not as familiar with statistical modeling, what does it mean to have a 95% R-squared?
PlanB: It means that the chance that the change in value is caused by random events, or other events than your input variable, is very low. It’s really the input that correlates with the output variable; the chance of random, other variables, influencing that same output are very low, close to 0 in this case. 95% is really high.
Stephan Livera: Okay. I think another interesting meme that’s been going around in the community, and this is something that went around particularly in 2017 with this whole, “Institutional money is coming,” and that was one of the ideas rapidly flying around; and on the counter side of that, some detractors might say, “Oh, look. So, much of the volume is fake, and maybe tether is fractional reserving, and that that is what’s driving the volume and the price rise.” Do you have any thoughts on that idea, that the volume is fake and tether is driving it?
PlanB: That’s an interesting question especially because I’m an institutional investor. I think some institutional investors really get it on C-level, like Fidelity, I think that’s a very good example; but actually I don’t see much banks and insurance companies that have to deal with central bank capital regime, like Basel or solvency; I don’t see them invest in Bitcoin very soon. If you look beyond the C-level at banks and insurance companies and institutional investors, say at a dealing room where the traders are, or the quants, or even the young employees, then I see a lot of interest and a lot of buy-into. I think the institutional money is coming meme? Yes, I hope we do. I’m also personally working towards that. I’d like to be a bridge between Bitcoin and traditional institutional money, but we have a long way to go.
PlanB: It’s funny because I also get the question a lot like, “Okay, you’re predicting a $1 trillion to $10 trillion Bitcoin market; that’s an enormous amount of money. Where does that come from?” and indeed it will not take $1 trillion or a couple of trillion, just a percentage of that, but still a lot of money. My answer to that question is I think, first, it’s the silver and gold market where money is coming from, and people selling silver especially, and gold more, if we approach the halving, and they will rotate to Bitcoin a bit.
PlanB: The second source of new money would be countries with negative interest rates, like Europe and Japan at the moment, and the US soon I guess. It must be really hard for people in the US to imagine what its like in Europe and Japan to have zero interest on your saving accounts, and sometimes negative interest on your mortgage. I have friends that have a negative interest mortgage rate, so they get money for living in their house; it’s really a weird world. If you get zero percent on your saving accounts… or even have to pay in the future, who knows… it makes you do different things with your money, and you might be looking for a plan B and invest some of it in Bitcoin.
Stephan Livera: Exactly. I think it’s around this idea that Bitcoin may displace other markets and other… where previously things that held some level of what we might call “a monetary premium.” I was interested just to get some of your thoughts in terms of overall finance and investing philosophy. An example would be: where do you sit on the active or passive debate?
PlanB: A bit in line with the efficient market and the Random Walk Down Wall Street book you mentioned from Malkiel, I think it’s very hard to outperform the market and generate Alpha. Unless you have a real edge, some info that others have, some models, some big dealing room and access to markets that others don’t have, I would stick to passive; there’s overwhelming evidence that that’s best for 80% of the people. Also, with Bitcoin you can do technical analysis and trade a lot for fun, try to time tops and bottoms. I personally prefer averaging-in, HODLing as an investment strategy.
Stephan Livera: PlanB, you’re a man after my own heart. I’m very similar. I’m very much about passive just long-term buy and hold. I suppose that then brings also the question around allocation. What Bitcoin allocations do you think might be reasonable, depending on what sort of person you are, whether you’re just a retail individual, whether you’re a high net worth individual or whether you’re a fund? Do you have any ideas on that?
PlanB: That’s a difficult question. It depends, of course, on the specific case. Let me warn that this is not financial advice, of course… which is true for everything, all the ideas I have… but that’s really difficult to answer. Maybe some general guidelines is: never invest more in Bitcoin or any other assets than you’re willing to lose, and especially true for Bitcoin because there is I think a small probability, but there is a probability that it goes to zero, so I think you should be willing or prepared to lose it all. So, don’t do it with your pension funds, or don’t do it with money you need for something else; do it with some money you have laying around doing nothing. Also, never invest in something that you don’t understand, so do your research first, and do it really well, because there’s lots of scammers out there. It’s really easy to get caught into some shitcoin and lose all your money. So, do it really good, read the whitepaper, follow the white rabbit, the trail is very clear, but do your research. If you then still want to buy Bitcoin…
PlanB: Say you’re a millionaire, “I want to have some fun and take some high risk with a small stake,” I would say one to 10 Bitcoins buys you a lot of fun for the years to come. For institutions, it’s a different game because they have obligations to their clients, and liabilities and regulators. What I would do is at least research the best performing asset of the last 10 years and do it well. So, study Bitcoin, and not blockchain, and understand it deeply, “Why is it here? Why is it still here?” and that kind of stuff.
Stephan Livera: Some very commonsense tips there. I think the other thing that people face, once they have been in Bitcoin for some time, is this question of rebalancing. Many people come up with a certain allocation; for argument’s sake, they might normally do 60:40 stocks and bonds. But let’s say they do that, let’s say they put maybe 1% Bitcoin, so they just want to have a small allocation in Bitcoin, but then let’s say there’s a big bull market and now that Bitcoin allocation is a lot more than 1%. Do you have any thoughts on whether people should rebalance? Or on the other hand, if they view it like a once in a lifetime opportunity, would they just not rebalance that Bitcoin aspect or component of their portfolio?
PlanB: That’s a complex question; let me say two things about it. I view Bitcoin also as the biggest asymmetrical bet of our time. Yeah, if you see it that way, if you did your research, and if you have some money around, go for it and have some fun. But I also think, even if it’s the biggest opportunity in a lifetime, that there is nothing wrong with taking some chips off the table after it goes 10 to 100x. I mean you have to live as well. So, take a couple of percent off, do some nice things, and make sure you survive the next bear market, that kind of stuff. I sure did in the beginning of 2018, so that was after the all-time high; I didn’t sell the top, of course, because that’s really hard to do, almost impossible. But if something goes 10 to 100x, make sure you have some fun with it, and I can tell you I’ll do it again. If Bitcoin indeed overshoots the stock-to-flow model price after next halving, so the $50,000 it overshoots to maybe $100,000 or maybe $200,000, I’ll take some chips off the table. Why not? So, that’s one point.
PlanB: The other point is, if you look at it from a quant investor perspective, this is a very technical thing. If there is asymmetrical distributions, so a power distribution which I think is there, then it really makes sense to bet with small sizes… so not put 100% of your money in; but put, for example 1% or 10% of your money in… and then your return will be very much smooth over time and still very high; not as high and also not as low as if you go all in, but it would bring your return very close to the highest return possible in that kind of situation, a bit like delta hedging options.
Stephan Livera: I really like the insight there, and it reminds me of another book I’ve read by I believe his name is William Bernstein. I think he makes a similar comment there that some people, for example during the dot-com bubble, that they were sitting on fortunes of maybe $10 million or $15 million and they didn’t even think to… As he says, once you’ve already won the game, you should take some chips off the table, right? Some of these people who got really caught up in that hubris of, “I’ve got $10 million worth of dot-com stocks,” in the early 2000s when the dot-com bubble was going, and they thought, “I’ll just keep holding and I’ll become $100 millionaire,” or a billionaire or whatever, and they didn’t think to realize, “Hey, what if I actually took some chips off the table?” Even if you took out $1 million or $2 million of that, that’s still a life-changing amount of money.
Stephan Livera: Are there any other comments you have around finance and investing philosophy?
PlanB: One thing. What really interests me is the arbitrage opportunity that might be there. Suppose that the quantitative easing experiments that we’re in right now, that it goes south and that it doesn’t end well, then you should have a plan B, there should be something after it, but at least I think there should be some arbitrage possible. Maybe with negative interest there will be an opportunity or a model, like the Black and Scholes model, that can earn you a risk-free return. I don’t think it’s impossible that that thing is out there. Maybe it sounds like the holy grail, but in my mind that’s how the next step in Bitcoins growth; not so much the adoption of customers paying for coffee or shops where you can pay with Bitcoin, but really a financial arbitrage that is found between the worlds where you can borrow money against negative interest rates, and the Bitcoin world where you have a super hard asset that will be harder than gold and harder than anything we have seen ever before. My feeling tells me there must be an arbitrage opportunity there, and I’m working day and night to find that one.
Stephan Livera: Interesting. I think people can lose their heads when it comes as well. During the bull market people just go crazy and they don’t really… The random person who doesn’t really know about that, Bitcoin and the whole cryptocurrency market, they’re not paying attention to the cooler heads in the room, and they are all looking for the best way to gamble and get a 10x or a 100x, so that’s something to watch out for.
PlanB: Exactly. In that respect, I really like the movie, The Big Short. You probably saw that one. If you haven’t seen it, it’s a must see. It will show you that during the last global financial crisis, some people saw it coming and had their plan B ready, and I think it’s similar to the times we live in today.
Stephan Livera: Yeah, it is a great movie. I do recommend it.
Stephan Livera: PlanB, I think that’s pretty much all we’ve got time for. If you have any last things you’d like to say just as a closing comment, or otherwise just tell the listeners where they can find you and follow you.
PlanB: Sure. You can find me on Twitter, PlanB@100TrillionUSD; and please Tweet me, DM me with all your comments and questions and critiques. I’m really looking forward to discussion; that’s why I am on Twitter. It’s also maybe good to know I put all the data, all the functions, all the python scripts on GitHub; so if they want to check for themselves, or test it, or improve on the model, please do so. We’re also working with some of my followers at the moment to improve the model, so please reach out and let’s keep the discussion going.
Stephan Livera: Excellent. Well, thank you very much for coming on; it has been a really fascinating discussion. I’m sure the listeners will enjoy when I release this one. So, thank you again for coming on the show, PlanB.
PlanB: Thank you for having me.
Stephan Livera: So, there you have it, some discussion around stock-to-flow ratio and trying to model that into what that means for the price of the asset. So, let me know your thoughts on whether you think we can model this sort of thing, or do you fall more on the side of thinking it’s like data mining, curve overfitting, etc.
Stephan Livera: Also, I just wanted to give shout out to Michael Folkson, the organizer of the London Bitcoin Devs Meetup; he left me a fantastic review. He left me five stars and wrote, “Highest signal Bitcoin podcast. A brilliant podcast. Stephan is great at bridging the gap between highly technical experienced guests and general audiences. If you want to learn about Bitcoin tech, this is the podcast for you.” Thank you, Michael. That’s really kind of you. And guys, I’d really appreciate, if you want to help me out, you can just give me a review on Apple iTunes or any other podcast app. You can give me a review; I’d really appreciate that. Otherwise, you can find the show notes on my website, stephanlivera.com. This is episode 67.
Stephan Livera: Thanks, guys, and I’ll speak to you soon. Bye.