The question of if a floor exists in the price of Bitcoin ()()(OTCQX:GBTC), and if so, what is that figure, has become a hot topic recently.
I would argue that the floor is determined by the probability of finding a gap between the fundamentals and the price. In other words, how many standard deviations below or above the price target are we at now? Any number is possible, but the extremely low and extremely high are both very rare, and therefore much less likely to occur. That’s the best we can do with the price floor. Watch the fundamentals and the rest is statistics.
However, the price ceiling is different. This is because we know there is a strong relationship between network activity and the price. To put it more succinctly, the more network activity we have, the higher the price. But, there are limits to network throughput, and this puts a lid on the price in the short to medium term.
We have seen this limit tested recently, when the Bitcoin blocks filled up. This gave us the upper limit on the maximum number of daily transactions that people were willing to pay, because of the price of the fees. I would call this the “soft limit” because you could squeeze more out of it, but it’s just not practical because it’s expensive.
The soft limit and the hard limit change over time as new technology comes online, such as SegWit, Schnorr Signatures, and The Lightning Network.
Network Fees and Bitcoin Price
Near the end of 2017 and the beginning of 2018, we tested the soft limits of the Bitcoin network. The high price for Bitcoin was around $19,475 on December 17th, 2017. The average fee was $62.50 on December 22nd, just five days later.
The price is the red line (left axis), and the fees are the red shaded area (right axis). See below:
The high number in daily transactions took place on December 13th, 2017, which was four days before the peak price.
Image Source: blockchain.com
Now, what’s changed since then? Well, the price has gone down, but also we have new technology online. SegWit is the biggest change, so let’s look at that real quick to refresh our memory. Below is a chart showing SegWit adoption.
SegWit was active during the last bubble, but only 12.5% of the network was using it at the time. Just in the last couple weeks, we had a spike over 53%, and the trend is clearly pointed upwards.
Recall that SegWit changes the maximum block size calculation by swapping out block size for block weight. The more SegWit transactions are used, the larger the block can become, up to a maximum of around 4MB, which is 4 times the current block size. So, speaking in theoretical best-case-scenario terms, 100% SegWit adoption would enable the Bitcoin network to process 4x as many transactions per day.
If we take the max daily transactions from last year, 490k, and SegWit was being used around 12.5%, that means we were already receiving a 50% daily TX increase from the technology back then. Today, we could get a benefit of 212% from this upgrade.
The maximum number of daily transactions (soft limit) without SegWit is around 327k per day. With adoption levels around 53% as of this month, this puts the daily maximum number of transactions at 693k per day.
Now, stick with me because the number of daily transactions and the price in log scale are highly correlated. Earlier this year, we saw the price/predicted using this model hit a Z-score of over 5.
For that to happen today, the network would have to hit its maximum throughput of 693k transactions per day, and then the price would explode through the roof and top out around $100k per bitcoin before the high fees caused another price collapse.
If you’re a spreadsheet junkie and you want to follow along, these are the steps you would follow:
- Take the maximum network throughput of 693k daily transactions today (327k daily transactions plus 53% of a 400% increase from SegWit).
- Take the log base ten of that number, which is 5.8407.
- The predicted “fair price” (a Z-score near zero) at this level of activity would be $7,420, based off regression analysis of the price and number of daily transactions going back to 2010.
- The highest Z-score of price/predicted this year was just over 5, the highest price over predicted was just over 13.
- In order to find the equivalent price in terms of Z-score, find a number that generates a Z-score, by determining what ratio of price/predicted gives you a value slightly over 13 (which was the highest recorded this year).
- That figure in log scale is very close to 5.
- Convert 5 back into linear scale, and you get $100,000.
You should see something like this when you run the regression of log price and log daily transactions.
Image Source: Author’s Regression Analysis
When you plot the Z-scores over time, you should see something that looks like this:
Image Source: Author’s charts
What we’re essentially doing here is re-creating a bubble by rewinding history, and then mapping those findings onto today. Will there actually be a speculative bubble today, or next week? Probably not, but remember this is just an exercise to see if it did happen, what would the maximum price be; the price ceiling (in this case the soft limit).
Image Source: Author’s Excel Worksheet
Max Price and Actual Price (Year to Date)
I looked at the number of transactions per day that could be processed by the Bitcoin network, and then attempted to find the theoretical maximum number of transactions if we added in the gains from SegWit. Then, I mapped that value along with the current price divided by the max price. This was the result.
Image Source: Author’s Charts
Here we’re looking at max capacity in terms of the hard limit. Using this method, it appears that the maximum price on January 1st would be somewhere around $45k per Bitcoin. However, when we add in the extra capacity and compare it with where we are now, today’s price seems to be quite a bargain, hovering around 6% of the maximum we might expect with peak usage and the FOMO premium added on top.
The price of Bitcoin is strongly correlated with the network activity. You can think of this in terms of value transmitted, number of users, number of transactions, or any other way if you can find a good data source and justify your reasoning.
If the network usage exceeds, or even nears its peak capacity, fees will spike and drive people away. This is what happened in the last bubble when the network could not sustain the rapid growth.
As the network gets upgraded, a higher theoretical price becomes possible. However, since the price can also be very volatile, the price at any given point is not likely to be the exact value we predict. Therefore, using a statistical model to find probability of distance from the mean seems to make the most sense.
This article was first released to members of Crypto Blue Chips, along with other research that can’t be found anywhere else (such at the BVIPE).
Disclosure:I am/we are long BTC-USD.
I wrote this article myself, and it expresses my own opinions. I am not receiving compensation for it (other than from Seeking Alpha). I have no business relationship with any company whose stock is mentioned in this article.
This content was originally published here.