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This is an expanded version of a post from the Sumer dip price guessing thread:
https://bitcointalk.org/index.php?topic=5346118.msg58567206#msg58567206
The thread compares and contrasts bitcoin price behaviour between the three halvings we have seen so far: 2012, 2016 and (partly) 2020.
First some basic data:
Note, there is a bit of rounding in prices, dates, etc.
The first point of interest is that the halvings are somewhat less than the expected four years apart – 2016 was 3 years and 7 months after the 2012 halving; 2020 was 3 years and 10 months after 2016. This is not entirely surprising as there has been a pretty steady increase in hashrate over Bitcoin’s life and so mostly each difficulty adjustment will have arrived early.
Next, let’s consider what proportion of the total supply had been mined at the date of each halving:
Key point here is that because the rate of emission halves each time, the number of coins affected gets rapidly smaller: and the proportion of new coins issued, starts to become trivial: in the current epoch less than 7% of the total supply will be mined against the 88% already mined and in circulation. Accordingly the impact of each halving is likely to be smaller and potentially take longer.
If we add in the subsequent highs and lows after each halving:
As expected much higher highs, and significantly higher lows.
But add in the time taken to reach the highs and the relative increases (over the price at halving):
We can see that the high takes longer to arrive: 526 days vs 366 or 1.44x longer
And the relative increase has reduced: 103x vs 30x or about 29% of the increase
For completeness add in similar figures for the following lows:
Interesting to see that the falls are very similar, if anything faster after the 2016 halving, but the impact almost identical (note they aren't actually identical its just the rounding took them both to 84%).
So can we use this data to predict the highs and lows for this halving?
Probably not … 😉 … there are really only two data points here which isn’t enough to draw a proper projection, but let’s do it anyway.
If we assume:
a. Each high takes 1.44x as long to arrive after the halving as the one before;
b. Each high is proportionately 30% as great as the one before;
c. Lows take about a year to arrive (388 days is the average) after the high
d. Lows result in an 84% drop
We get the following, predictions are in BLUE
So in short:
First I don’t think there is enough data to use the prior halvings to predict future halvings, but if we are going to try to do that we ought to at least use the data we have. The data we have suggests that the impact of each halving will be smaller than the one before, as the proportion of the total supply that is affected by the halving reduces over time.
Extrapolating forward from the 2012 and 2016 halving suggests that the next “high” will be in June 2022 and will be around $77,000.
Here’s the whole post summarised in a handy chart (with thanks to mikeywith for the underlying chart to which I added this speculation):
(Edited to tidy up the tables and stop the wrapping which was annoying me.)
