How the price elasticity of supply may be governing the Bitcoin price
Summary
The supply of Bitcoin is finite and it is a scarce digital commodity. Those properties impart a large portion of Bitcoin’s attraction as an investment, and its value. But in practice the majority of market participants have a price at which they’re willing to part with their coins. In economics this is called the price elasticity of supply.
This article argues the price elasticity of supply governs the market capitalization of Bitcoin and can be measured via liquidity and invested capital metrics. It can also explain the mechanics behind the price development theory that resembles an inverse hyperbolic tangent function.
The Illiquid Supply Pendulum
The illiquid supply ratio has come down in bitcoin’s history, from highs of 1.0 (100% illiquid) in the early days of Satoshi mining to 0.73 in the bear market of 2019, first falling rapidly, then more slowly. It has stabilized since then and resumed an uptrend since early 2020. One is reminded of a pendulum swinging past its lowest point and proceeding back upwards.
While the rise of professional crypto exchanges increased liquidity for supply- and demand- side, we now see reducing liquidity due to increased HODLing behavior, likely due to improved confidence in the future of the network and increased capital inflow with long-term investment horizons.
Chart 1 — the Bitcoin illiquid supply ratio — history and prediction
The mcap growth multiple
As the illiquid supply ratio has come down, so has the invested mcap multiple (the mcap growth multiple from 1.0 mcap in invested capital). Based on the price elasticity of supply economic theorem, the thesis is that these are correlated. More liquid markets lead to lower growth per unit of invested capital. The illiquid supply ratio correlates to the log10 of the invested mcap multiple with a 0.85 coefficient, on the boundary of a moderate and a strong correlation.
Chart 2 — the Bitcoin illiquid supply ratio and invested mcap multiple — history and prediction
Market capitalization
The consequence of a high invested mcap multiple is seen in the rapidly rising market capitalization, especially in the early years. As the invested mcap multiple declined and flattened off in recent years so did the market capitalization growth.
Chart 3 — the Bitcoin illiquid supply ratio, invested mcap multiple and market capitalization — history and prediction
Invested Capital
The astute observer will be missing one data point in the logic and thesis presented above: the invested capital. The invested capital as measured by % of mcap is calculated by multiplying spent coins aged >3 months by the then prevailing market price on a daily basis. In the methodology section a paragraph is devoted to this method of capital inflow calculation vs the RCAP growth method. While still a proxy for actual net capital inflow, it suffices to show a consistent rise in Bitcoin’s history. Not only is the absolute amount increasing, the capital inflow as a % of mcap is also increasing, though strongly fluctuates over time. The baseline of capital inflow currently stands at ~100% of market capitalization on an annualized basis.
Chart 4 — invested capital as a % of market cap on an annual basis
Predictions are not forecasts, as the latter implies some mathematical rigor. Ultimately the thesis hinges on a continuing increase of the illiquid supply ratio. This in turn drives the invested mcap multiple higher and coupled with stable or higher capital inflows (as a % of mcap) leads to a higher market capitalization of Bitcoin. The first step — a higher illiquid supply ratio — is a prediction. The steps after can be derived by logic and observations of historical data. A next step should include some more mathematical rigor and I will return to that in a future article.
Context and Rationale
Price Elasticity of Supply
A core part of the thesis relates to the economic theorem of the price elasticity of supply (PES). How much does supply increase for a given rise in price?
For almost every good an increase in price leads to an increase in supply and has a unique curve along which price and supply ratio can be plotted. The curve also changes over time, as we have seen.
To model the PES for Bitcoin we utilize on the one hand the change in supply through the illiquid supply ratio, and the price change via market capitalization growth. More on both metrics below.
Liquid Supply
See https://insights.glassnode.com/bitcoin-liquid-supply/ for more detail on liquidity calculations. All data presented in this article comes from Glassnode and its calculation of liquidity numbers.
The illiquid supply ratio often cited in this article is calculated by dividing the total illiquid supply (in coins) by the circulating supply (in coins) on that day.
You will note how illiquidity has dropped consistently from 2009 onwards, starting at 1.00 (100% illiquid) as Satoshi was mining his/her coins. The highest liquidity environment to date was encountered around the start of 2019 during the bear market with the illiquid supply ratio bottoming at around 0.73.
Despite the HODL mantra that first appeared in 2013 liquidity has increased steadily. Why is that? Two key reasons appear to be the rapidly growing depth of liquidity in the Bitcoin market, and the ease of access to those markets via cryptocurrency exchanges. Life-changing gains were made by early investors that have had every reason to cash out from an at times uncertain future. Despite the Lindy effect implying Bitcoin has a greater chance of making it through the next 10 or 20 years with every passing day, week and month, the amount of FUD in circulation never lets up, from environmental concerns to governments bans, and from exchange hacks to block-size wars. A strong conviction is needed to HODL and to do so for many cycles.
The role of exchanges in improving liquidity should not be underestimated, specifically in the period of 2016/2017 when volumes on exchanges exploded 100x.
Chart 5 — volume on bitcoin exchanges (blockchain.com trade volumes)
The exchanges provided an efficient mechanism and gateway to miners to cash out their Bitcoin holdings. The gateway clearly worked both ways with a 7-fold growth of net entities between early 2016 and late 2017.
Chart 6 — net entities growth (glassnode/twitter))
Generally, illiquidity rises in bull markets only to fall during bear markets. From the beginning of 2020 onwards there has been a steady rise in illiquidity. As this coincides largely with a bull market it remains to be seen whether the rise can hold through a persistent market downturn. There is a case to be made for this trend to persist:
1. the aforementioned Lindy effect has boosted confidence in the network.
2. the amount of information on bitcoin is growing and more people are aware of its positive properties as sound money.
3. it has growing recognition of being a safe haven asset class with zero counterparty risk, an important property after the global financial crisis of 2008.
4. given loose monetary policy around the world people are looking for a store of value asset.
5. institutions with long time horizons have made investments — these are investments that are made for the long term, they are balance sheet investments and not P&L hedge fund investments.
6. the lightning network enables Bitcoin to be viable as a medium of exchange. Furthermore, Bitcoin committed to the Lightning network’s liquidity pool is essentially illiquid. In this scenario the velocity of Bitcoin can be very high, while on-chain the illiquidity persists.
Invested capital calculation and its impact on market capitalization
The proxy for invested capital we use for our calculations is the spend of coins aged >3 months. An alternative to this method is using the realized cap development over time and assuming any delta from day to day is due to capital inflow (or outflow). Ultimately, a decision was made against the RCAP method for three reasons. The first is that capital flows turn negative in market downturns. While this is an accurate portrayal of the situation, it is exaggerated and doesn’t accurately reflect capital outflow. In the opinion of the author the spend of aged coins provides a more accurate view of external capital flowing into the network. Secondly, using realized market cap inflates the actual capital inflow in the early years when inflation was high. While there is a cost to mining, this doesn’t represent actual capital inflow but additions to circulating supply at the then prevailing market price. Thirdly, because the intent is to make predictions into the future when inflation is negligible, we look to find dynamics that aren’t influenced by inflation so that we can more accurately compare time periods in Bitcoin’s history. This is a contentious point so feedback and discussion is appreciated.
To normalize to a single unit of measure for invested capital we will use units of market capitalization. The best way to illustrate this is through an example:
If on a given day 10,000 coins (aged > 3 months) are spent and the price is $10,000, we calculate that $100MM was spent, and as such $100MM of capital inflow is recorded.
If the market capitalization of bitcoin was $200Bn on that day the capital inflow was .05% of mcap (or .0005 units of mcap).
To calculate the invested mcap multiple, we take the following steps:
1. Calculate the 180day average of capital inflow in units of mcap for every day in Bitcoin’s history. (.25% is a reasonable number for an arbitrary day)
2. Multiply by 364 to annualize the number (.25% * 364 gives us an annualized number of 0.91 mcaps in invested capital)
3. Calculate the mcap multiple between day-180 and day+180 (let’s assume for that time period it is 1.8x, rising from $100Bn to $180Bn))
4. Divide the 360day mean mcap multiple (step 3) by the annualized capital inflow number calculated in step 2 (1.8 divided by 0.91 = 1.98 i.e. for every 1.0 mcap investment the market cap will rise by 1.98x).
This number represents the market capitalization growth multiple for every unit of capital inflow expressed in units of market capitalization. Yes, it does seem like the snake is swallowing its own tail. Bear with me here.
Important note — It is not lost on the author that deciding on the method for calculating capital inflow makes or breaks the thesis put forward in the article. Using the prior method, the thesis put forward in this article can be assessed on its merit. Using the RCAP method the main thesis of the article does not hold as there is no meaningful correlation between the illiquid supply ratio and the invested mcap multiple.
Inspiration
Shout-out to Steve Babour, David Puell, Rafael Schultze-Kraft, Checkmate, TXMC, Captain Jack, Willy Woo, Logscale, and Will Clemente. Your content is gold and instrumental in inspiring me to write this piece. Also the Erasmusian Dave the Wave. While the math that Dave employs works out and I have published on it myself, I could not help but remain dissatisfied with the LGC and diminishing returns. Steve ‘s article gave me a way out. I had been interested in capital flows for a while, and Willy and Will kept raising the profile of scarcity and liquidity through their posts and forecasts. Glassnode has been a tremendous source of insight for me, even though I only have access to the poor man’s version and miss data from the past 365 days on key metrics that I then piece together from twitter posts by Rafael, Will, or Willy. Thank you!
A special shout-out to Bitcoin Jack who first flagged the declining illiquid supply ratio on twitter. It alarmed me at first. With decreasing illiquidity the prospect of continued price growth was disintegrating before my eyes. But I took heart from the more recent rise in illiquidity and the idea of a pendulum took shape. A history of increasing liquidity from improved access to markets for all mined coin, then growing illiquidity from growing and persistent HODLing.
My rabbit hole journey has been extremely fulfilling. Thank you, Satoshi. And thank you to all those who post insightful, informative content out there. Keep going.
