Оглавление
- Bitcoin stock-to-flow deviation data
- The rate of adoption model might be more accurate
- The 6th bounce off the long-term trendline
- Stock-to-Flow deflection gives bullish signal
- Conclusion
- Stock-to-Flow Cross-Asset Model
- The 6th bounce off the long-term trendline
- Bitcoin value and scarcity
- How to Use Bitcoin Stock to Flow Model
- Коинтеграция
- Соотношение предложения стейблкоинов и BTC
- Stock-to-Flow deflection gives bullish signal
- Conservative price model based on miner adoption
- Problem #6: Gold’s stock-to-flow does not drive its price
- Why did traders use the SF model first place?
Bitcoin stock-to-flow deviation data
According to Bitcoin’s price — depicted as the red line on the chart — BTC price has reached comparatively higher separation above its median during bullish periods than the times it dropped below its median during bearish periods. Bitcoin also has followed its median line, leading to higher prices in conjunction with halving events.
After its halvings in 2012 and 2016, Bitcoin followed the median upward trend but rode that trend mostly below the median line until large bull run spikes drove its price high above the median.
Additionally, prior to the 2012 and 2016 halvings, Bitcoin appears to have experienced bear market drops, spending time near the bottom of the dark blue deviation band.
A similar bear market period near the bottom of the dark blue deviation also occurred after 2018, but appears to have happened comparatively earlier than the other two pre-halving bearish periods.
Wolfram also suggested an interesting observation, pointing to reversion and decreasing highs.
“At both halvings I see the price overshooting the model price and then coming back down,” Wolfram told CoinTelegraph. “It does seem that the overshooting becomes less though.”
Notably, the above chart is an updated version using past information, in contrast to the one originally posted on Twitter, which used future data predictions. Wolfram also developed this chart before Bitcoin’s 42% spike on Oct. 25.
The rate of adoption model might be more accurate
While the S2F model is one of the most widely known quantitative models that predicts Bitcoin’s price in the short term (less than five years), there are several other models that are often used to gauge its price potential. Daniele Bernardi, founder of the PHI token project and CEO of Diaman Partners Ltd., a fintech asset management company, explored some of these models in a recent paper. Bernardi evaluated the inadequacies of the S2F model, stating to Cointelegraph:
Instead, Bernardi prefers the rate of adoption model, which he explores in his paper. He stated that, according to this model, the “fair price” of Bitcoin can be around $60,000, but not more than that. This estimate is based on the “actual users of Bitcoin and the wallets created.”
He went on to explain the probability of PlanB’s S2F model actually coming into fruition this year: “Of course, anything can happen, but from my point of view, there is less than 20% of probability, based on Monte-Carlo simulations, that the Bitcoin price will reach a value greater than $100,000 in 2021.”
Related: Forecasting Bitcoin price using quantitative models part 3
That said, it is important to remember that Bitcoin was exchanging hands at $18,000 for a few days in the March 2017 bull run and went straight to trading at $64,000 earlier in February this year.
There are not many assets in financial markets that have witnessed gains at these levels within such a short timespan. Bernardi explained the impact of this growth:
Fair value or not, Bitcoin seems to be in a period of turmoil, more often than not facing downward pressure on the token since the flash crash on “Black Wednesday” earlier in May. However, positive institutional news keeps flooding in. Most recently, Grayscale CEO Michael Sonnenshein said that Grayscale is “100% committed” to turn GBTC into a Bitcoin exchange-traded fund.
The 6th bounce off the long-term trendline
In the same tone, popular on-chain analyst Will Clemente tweeted yesterday, drawing a long-term trendline on the S2F deflection chart. This line goes back to the first BTC cycle of 2011. He then marked the points where the deflection chart touched that line and connected them with vertical lines to the BTC price from that period.
Source: Twitter
It turns out that whenever the deflection reached this long-term trendline, the “Bitcoin has gone on an absolute tear”. If this scenario were to repeat itself, we can expect not only a reduction in the S2F deflection in the coming months, but also a continuation of the long-term bull market in crypto.
Stock-to-Flow deflection gives bullish signal
Stock-to-Flow (S2F) deflection is a way to estimate Bitcoin’s value against one of the most popular models of its price.
If the chart turns green, then Bitcoin’s value is undervalued in relation to S2F. If it is red, it is overvalued. The chart therefore allows one to determine whether the price of Bitcoin relative to the S2F model is low, normal or high.
Bitcoin Stock-to-Flow Deflection / Source: Glassnode
Currently, the S2F deflection chart is deep in green undervalued territory. We recently pointed out at BeInCrypto that this is the largest undervaluation in 10 years. This was happening with Bitcoin trading in an area of support between $29,000 and $31,000 from May 19 to July 21, 2021.
Commenting on such low S2F deflection values, cryptocurrency trader Michaël van de Poppe said in his YouTube video:
He further added that the current S2F deflection is reminiscent of the first half of 2017. At that time, the BTC market also experienced a deeper correction, and the deflection went deep into undervalued territory. In hindsight, this moment proved to be an excellent opportunity to invest in BTC.
Conclusion
The Stock to Flow model measures the relationship between the currently available stock of a resource and its production rate. It’s typically applied to precious metals and other commodities, but some argue it may apply to Bitcoin as well.
In this sense, Bitcoin may be viewed as a scarce digital resource. According to this analysis method, the unique propositions of Bitcoin should make it an asset that retains its value over the long-term.
However, every model is as strong as its assumptions, and it may not be able to account for all aspects of Bitcoin valuation.
Any information found on this page is not to be considered as financial advice. You should do your own research before making any decisions.
WazirX Warrior Author: Jay Tanwar
Jay Tanwar is a cryptocurrency enthusiast and supporter of decentralized applications. He is basically from Rajasthan and a Network manager by profession.
Stock-to-Flow Cross-Asset Model
The main difference between this new model and the old one is that the old one was a time series model for bitcoin, and this new one is a model that you can use to value all similar assets. Basically, time has been swapped with other assets in this new formula. Plan B also mentions that to use this new model, you need to understand phase transitions which play an essential part in using this model.
To explain phase transitions, Plan B uses three examples, water, dollar, and bitcoin. As probably all of us know, water can be solid, liquid, gas, and ionised; it is still water but just in different phases.
Typically we only talk about three of these, solid-liquid-gas. Image via PlanBTC.com
Plan B explains that phase transitions also appear in finance, for example, in the dollar. First, it was a gold coin, then a paper backed by gold, and then just paper backed by nothing. In all these phases, it was called the dollar, although it was a completely different thing.
Gold coin – paper backed by gold – paper backed by nothing. Image via PlanBTC.com
Now to the bitcoin phases. First, we had “proof-of-concept” when Bitcoin was first released. Then we had the “payments” phase when one Bitcoin was equal to one dollar. Thirdly came the “e-gold” phase, which was after the first halving. And then now we are in the “financial asset” phase.
Okay, so how do these phases work then? In the chart down below, you can see monthly data from the original SF model and how they form these clusters. You can also see the gold and silver data points which seem to line up with the rest. Plan B explains that these clusters are being formed and correlated with the SF and market cap; according to him, this model has an R2 of 99.7%.
Chart made by Plan B. Image via PlanBTC.com
The 6th bounce off the long-term trendline
In the same tone, popular on-chain analyst Will Clemente tweeted yesterday, drawing a long-term trendline on the S2F deflection chart. This line goes back to the first BTC cycle of 2011. He then marked the points where the deflection chart touched that line and connected them with vertical lines to the BTC price from that period.
Source: Twitter
It turns out that whenever the deflection reached this long-term trendline, the “Bitcoin has gone on an absolute tear”. If this scenario were to repeat itself, we can expect not only a reduction in the S2F deflection in the coming months, but also a continuation of the long-term bull market in crypto.
Bitcoin value and scarcity
One well-respected Bitcoin analyst with the pseudonym ‘PlanB’ published an article on Medium in March 2019 called Modelling Bitcoin Value with Scarcity. The article suggests a statistical relationship between the S2F ratio of Bitcoin and its price—and that this can be used to help forecast the future price of Bitcoin.
In order to get this relationship, Plan B ran a statistical model which estimates Bitcoin’s price using a regression equation involving annually smoothed S2F ratios. The next chart shows this from 2011 until the sixth halving event in 2028.
Bitcoin Price vs. Stock-to-Flow. Log scale. Source: authors own calculation using data from blockchain.com and lookingintobitcoin.com. The concept of this chart is attributed to ‘Plan B’.
Looking at the chart, there has been a strong relationship in the past between the S2F model and Bitcoin’s price. But it would be dangerous for an investor to think that this model can predict the future. The model suggests that Bitcoin will (give or take) go up by ten times sometime after each new block reward halving date.
As with gold, Bitcoin’s price could go up in the future because dollars get printed at a faster rate—not because Bitcoin’s supply keeps increasing at a slower and slower rate. Ninety percent of all bitcoins in the world have already been mined. In other words, Bitcoin is already extremely scarce.
The model suggests a $1 million Bitcoin in the year 2028 and a $10 million Bitcoin in 2032. We can’t assume Bitcoin’s price will increase by an order of magnitude each time we have a halving event.
How to Use Bitcoin Stock to Flow Model
Bitcoin’s S2F model is a live chart data model that can be used easily to track the predicted price of the asset at a given point of time and the actual market price of the asset at the time. As the data points are indexed in accordance with time, it is a time series model.
The charts have the forecasted price of Bitcoin on the y-axis and the timeline from 2010 to 2026 on the x-axis. Over this line chart, the market price of Bitcoin is plotted across the chart to create a comparative view of the forecasted price vs the market price. Using this chart you can see how much the current price of Bitcoin varies from the forecasted price at a given time, historically as well.
For believers of the model, the charts combined together can also be viewed as an indicator to buy or sell the asset. Negative deviations from the forecast price line could be interpreted as signals to buy the dip while positive deviations could be construed as signs to sell as the asset is now overvalued. The stock-to-flow deflection ratio is the best metric to evaluate this.
Коинтеграция
Коинтеграция – это способ разобраться с парой (или более) процессов I(1) и определить, есть ли между ними взаимосвязь и в чем она состоит. В качестве наглядной иллюстрации коинтеграции часто приводится упрощенный пример пьяницы и его собаки . Представьте себе пьяного человека, направляющегося домой, выгуливая на поводке собаку. Пьяницу совершенно непредсказуемым образом шатает по всей ширине дороги. Собака двигается тоже довольно сумбурно: обнюхивает деревья, лает, что-то роет лапами – такая беспокойная собачонка. Однако радиус движения собаки будет ограничен длиной поводка, удерживаемого пьяницей. То есть можно утверждать, что в любой точке маршрута пьяницы собака будет находиться в пределах длины поводка от него. (Конечно, мы не можем предсказать, в каком направлении от пьяницы она будет находиться в каждый момент времени, но она будет в пределах поводка.) Это очень упрощенная метафора коинтеграции – собака и ее хозяин двигаются вместе.
Сравните это с корреляцией: скажем, бродячая собака следует за собачонкой пьяницы на протяжении 95% их пути, а затем убегает с лаем в другую сторону за проехавшим мимо автомобилем. Корреляция между маршрутами бродячей собаки и пьяницы была бы очень сильной (буквально R²: 95%), однако, как и многие случайные связи пьяницы, это отношение ровным счетом ничего бы не значило – его нельзя использовать для прогнозирования местонахождения пьяницы, поскольку для какого-то фрагмента пути прогноз на основе этих данных окажется верным, но для некоторых частей он будет совершенно неточным.
Для того чтобы найти местоположение пьяницы, сначала мы должны понять, какую спецификацию порядка запаздывания следует использовать в нашей модели.
Рис. 16 – спецификация порядка запаздывания. Минимальное значение AIC, используемое для определения.
Здесь мы определяем наиболее подходящий для исследования порядок запаздывания через выбор минимального значения AIC порядка 2.
Далее нам нужно определить наличие коинтегрирующего отношения. Фреймворк Йохансена дает нам для этого превосходный инструментарий.
Рис. 17 – тест Йохансена на коинтеграцию.
Результаты, представленные на рисунке 17, дают нам основания утверждать, что между ln(стоимость) и ln(S2F) есть по меньшей мере одно коинтегрирующее уравнение.
Мы определяем нашу VECM как:
Δy@t =αβ`y@t-1+Σ(Γ@iΔy@t-1)+v+δt+ε@t
Рис. 18 – информация обо всех уравнениях модели.
Рис. 19 – расчетные значения краткосрочных параметров и их статистика.
Рис. 20 — коинтегрирующее уравнение для модели.
Рис. 21 – информационный критерий Акаике для VECM.
На рисунках выше мы имеем следующие расчетные значения:
- =
- = ,
- = и
- = .
В целом результат указывает на то, что модель подходит хорошо. Коэффициент ln(S2F) в коинтеграционном уравнении является статистически значимым, равно как и параметры корректировки. Параметры корректировки указывают на то, что, если прогнозы из коинтеграционного уравнения являются положительными, то ln(стоимость) находится ниже своего равновесного значения, поскольку коэффициент на ln(стоимость) в коинтеграционном уравнении отрицателен. Расчетное значение коэффициента L. ce1 составляет -0,14.
Таким образом, если стоимость биткойна слишком мала, она быстро поднимается обратно до уровня соответствия ln(S2F). Расчетный коэффициент L. ce1, равный 0,028, подразумевает, что при слишком низкой стоимости биткойна он корректируется до равновесного уровня.
Рис. 22 – прогнозируемое коинтеграционное уравнение.
На рисунке выше видно, что результат коинтеграционного уравнения имеет тенденцию стремиться к нулю. Хотя формально оно может быть и нестационарным, оно определенно стремится к стационарности.
Из пользовательского руководства ПО Stata:
Рис. 23 – корни сопровождающей матрицы.
Графическое изображение собственных значений показывает, что ни одно из оставшихся собственных значений не находится близко к краю единичной окружности. Проверка устойчивости нашей модели не указывает на ее ошибочность.
Рис. 24 – функция импульсного отклика.
Приведенный выше рисунок указывает на то, что ортогонализованный скачок к значению коэффициента S2F оказывает постоянное влияние на стоимость биткойна.
И в этом месте мы подведем черту. Отношение запасов к приросту не является случайной величиной. Это функция с известным значением во времени. Никаких скачков значений S2F не будет – его стоимость может быть с точностью рассчитана заранее. Однако эта модель дает очень убедительные доказательства того, что существует фундаментальная неложная зависимость между значением коэффициента S2F и стоимостью биткойна.
Соотношение предложения стейблкоинов и BTC
Коэффициент предложения стейблкоинов (SSR) представляет собой соотношение предложения стейблкоинов и текущей эмиссии биткоина. Он представляет интерес, поскольку трейдеры часто используют поддерживаемые традиционным фиатом стейблкоины для покупки (или продажи) биткоинов.
Низкие значения SSR традиционно указывают на высокую покупательную способность стейблкоинов относительно биткоина. Так, значение 5 говорит о том, что стейблкоины могут купить 20% (1/5) всего объема предложения BTC.
Если коэффициент предложения стейблкоинов снижается, потенциально это может указывать на вероятность роста курса биткоина.
Индикатор SSR обновлял исторические минимумы с 17 мая, когда он впервые достиг 9,4, поглотив прежний рекорд 9,57 от октября 2020 года.
26 июня SSR передвинул исторический минимум на 5,56. Также отметим, что показатель четвертый раз с октября 2018 года просел под нижнюю границу полосы Боллинджера.
Предыдущие три раза (выделено кругами) рынок формировал после этого дно и запускал существенный рост. Соответственно, если история снова повторится, биткоин вскоре может перейти в фазу роста.
Stock-to-Flow deflection gives bullish signal
Stock-to-Flow (S2F) deflection is a way to estimate Bitcoin’s value against one of the most popular models of its price.
If the chart turns green, then Bitcoin’s value is undervalued in relation to S2F. If it is red, it is overvalued. The chart therefore allows one to determine whether the price of Bitcoin relative to the S2F model is low, normal or high.
Bitcoin Stock-to-Flow Deflection / Source: Glassnode
Currently, the S2F deflection chart is deep in green undervalued territory. We recently pointed out at BeInCrypto that this is the largest undervaluation in 10 years. This was happening with Bitcoin trading in an area of support between $29,000 and $31,000 from May 19 to July 21, 2021.
Commenting on such low S2F deflection values, cryptocurrency trader Michaël van de Poppe said in his YouTube video:
He further added that the current S2F deflection is reminiscent of the first half of 2017. At that time, the BTC market also experienced a deeper correction, and the deflection went deep into undervalued territory. In hindsight, this moment proved to be an excellent opportunity to invest in BTC.
Conservative price model based on miner adoption
A more conservative model price can be derived by doing a back calculation based on a roughly estimated number of today’s world’s electricity percentage used for mining Bitcoin in the future and the general assumption of a healthy ratio of spot price to mining cost like stated above for gold. The assumption for this model is that a significant amount of Bitcoin’s value lies within the amount of hardware and electricity put towards mining daily.
model price based on estimation of world’s electricity percentage used for mining Bitcoin in the future
Therefore, a plausible increase of the world’s electricity amount put towards Bitcoin mining during the next few cycles is estimated and set first. The percentages in the rightest column are manually set. A mean mining cost of $4,000 (roughly half of today’s spot price) per Bitcoin is set as well. Based on these set numbers and the known flow of Bitcoin in the future, a future mining price can be calculated for each cycle. Then, a model price is derived by multiplying the calculated mining cost by two. It took Bitcoin’s network three cycles to claim 0.25% of the world’s electricity for mining, which is less than a 0.1% increase per cycle. In this scenario, the percentage increases 0.25% into the next cycle and another 0.5% per future cycle. Therefore, a total of 2% of the world’s electricity would be used for mining Bitcoin in 2032. The set parameters and calculation approach would result in a Bitcoin spot price of roughly $1 million within the 2032–2036 cycle. In the upcoming cycle, a spot price of $32k can be estimated based on a ratio of 0.5% world’s electricity put towards mining.
In comparison, PlanB’s model price ranges from $55k to $288k within the next cycle depending on the used model. Those spot prices would imply the ratio of world’s electricity used for mining Bitcoin ranging from 0.86% to 4.5% within the next four years — assumption: the hypothesis of a sustainable spot price to mining cost ratio similar to gold stays valid. While the lower boundary value seems quite unlikely but possible the higher boundary value seems highly unlikely.
Problem #6: Gold’s stock-to-flow does not drive its price
Plan B observed that because bitcoin’s mining flow gets cut in half every four years, bitcoin’s stock-to-flow ratio leaps every 4 years. These halving events boost Bitcoin’s stock-to-flow ratio dramatically. It’s reasonable to assume that the contracting supply is fueling the BTC’s dramatic price rise.
Intuitively, the stock-to-flow model makes sense once you conduct a simple thought experiment. Imagine if the flow of gold suddenly slowed to a trickle. Instead of 3,000 tons of gold being mined annually, we only managed to dig 3 tons of gold each year.
What do you predict would happen to gold’s price?
It would skyrocket, right?
That’s because investors, national banks, jewelry makers, phone makers (0.034 grams of gold in each phone), and other industries that use gold would have to fight over a (nearly) fixed supply.
Still, if the stock to flow ratio were such a great price predictor, then we should see gold analysts use it all the time.
But they don’t. Gold bugs only cite gold’s stock-to-flow to help explain why gold has monetary value. But they don’t use it to predict gold’s price.
That’s because, as you can see from Voima’s chart below, gold’s stock-to-flow ratio is sometimes uncorrelated to gold’s price.
The above chart is a bit misleading because it only shows the nominal price of gold, which, before 1971, was fixed by the government.
Below is the real, inflation-adjusted price of gold. When you examine the red line, overlay the cyclical stock-to-flow line over it. You’ll see no correlation.
For example, in the graph above, you can see that the STF (the gold line) hit a high of 95 around 1920. But the graph below shows the inflation-adjusted price (the red line) is rather low in the 1920s. You’ll see the opposite when you compare the 1940 numbers.
In short, gold’s price is uncorrelated to its stock-to-flow ratio.
I haven’t read a single gold expert argue that stock to flow drives gold’s price. As proof, at the bottom of this article, you can watch my interview with Jan Nieuwenhuijs, a famous gold researcher and analyst.
However, according to the S2F model, the alleged driver of bitcoin’s price rise is its ever-increasing stock-to-flow ratio. As bitcoin’s stock-to-flow ratio goes up, bitcoin’s price follows. That is the thesis.
That implies that if bitcoin’s stock-to-flow ever stabilizes, then its price should stabilize too.
Gold’s stock-to-flow and price history tells a different story. Over the last 120 years, gold’s STF ratio has cycled up and down while gold’s inflation-adjusted price has gone all over the place.
Why did traders use the SF model first place?
PlanB’s article “Modeling Bitcoin Value with Scarcity” describes precious metals with unchangeable costliness and limited rates of supply as maintaining monetary roles throughout history. Gold, for example, is valuable because fresh supply (mined gold) is small in comparison to the present supply, and it is impossible to replicate the huge stockpiles of gold across the world. PlanB then claims that the same reasoning applies to bitcoin, which gains value when fresh supply is decreased every four years, eventually resulting in a supply of 21 million bitcoin.
He then graphs the SF of bitcoin versus the USD market capitalization and two randomly picked SF data points for gold and silver. Following a linear regression with the natural logarithm of bitcoin’s SF metric as the independent variable and USD market capitalization as the dependent variable, the study concludes that there is a statistically significant link between USD market capitalization and SF values, as demonstrated by linear regression with an R2 (a statistical measure of how well data fits a regression line) of 0.95. The two randomly selected data points for gold and silver are consistent with bitcoin’s trajectory and are provided as additional support for the hypothesis.
Source: PlanB Original Paper
The method mentioned above, according to PlanB, may be used by investors to estimate the future USD market capitalization of bitcoin. Also, the model lends validity to the $100,000 bitcoin forecasts.
As a result, SF has gone viral and generated rags-to-riches fantasies for people betting everything on the future of bitcoin. However, I anticipate that the model’s accuracy will be roughly as good at forecasting bitcoin’s future price as other models were at predicting financial events.
Even Fidelity Digital Assets examined the S2F valuation model in August 2020, indicating that the stock-to-flow approach had some validity.
However, no model is 100% accurate because of the various unpredictable events that could occur spontaneously. For example, the Covid 19 outbreak was a massive hit for the crypto market as prices crashed over a span of days.
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