When Will Bitcoin Hit 100.000?

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When Will Bitcoin Hit 100,000?

A macro-economic growth model for the cryptocurrency market

When you google the terms “Bitcoin price doubles every”, you find statements ranging between 3 and 8 months (or even 18 days, but only under Venezuelan hyperinflation conditions). The tricky part about these calculations is that they tend to ignore the influence of bull and bear market cycles and simply extrapolate market data linearly. While this doesn’t really create meaningful results, a slightly more elaborate model might to the trick.

Looking Backwards: Analyzing the Past Market Trend

First, let’s have a look at market performance based on the aggregate market cap of all cryptocurrencies over the past years. Showing the data on a logarithmic scale creates quite a clear picture of its movements including the peaks in late 2013 and early 2018.

Figure 1: Aggregate market cap (MC) of all cryptocurrencies in billions USD over time

What stands out when looking at the chart is that there seems to be a macro price channel, i.e. the aggregate market cap always moves in between two straight parallel trend lines that can be drawn above and below (black lines in Figure 2).

Figure 2: Aggregate market cap (MC) incl. trend lines for top, bottom, and average

The middle between those trend lines represents the average growth without the influence of bull / bear market cycles (blue line in Figure 2). Since the scale is logarithmic, it can be easily expressed as an exponential function (Figure 3). Put simply, there’s a 10x increase every 2.5 years.

Figure 3: Exponential growth function to determine aggregate market cap over time

Looking Forward: From Exponential to Logarithmic Growth

Since there’s no indefinite growth, what we need to model to reflect reality is something like an s-curve. In economics they are typically used to describe the progress of an innovation through its life cycle; should be a good fit. In such a model, the initial stage of growth is exponential, then saturation begins and growth slows to linear, and then at maturity it becomes logarithmic.

An s-curve can be described using a logistic function such as TANH. To define its properties, three parameters are required: The maximum value, the steepness of the curve and the duration.

Figure 4: Logistic (s-curve) growth function to determine aggregate market cap over time

Since it’s a bit difficult to tell how big the total cryptocurrency market cap can be one day, I created a few different scenarios with maximum values of between 1 and 20 trillion USD. It’s probably fair to assume that it will be in the the trillions considering the order of magnitude of current financial market size numbers (even when only considering a fractional market share). As for steepness and duration, I simply selected parameters so that the exponential part of the curve would match with the historic growth curve (as described in Figure 3).

Figure 5: Five scenarios of aggregate market cap of all cryptocurrencies in billions USD over time

Understanding Bull and Bear Cycles

It’s probably not a coincidence that the max and min trend lines that describe the price channel in which the aggregate market cap moves (black lines in Figure 2) match with the 0.236 and 1/0.236 Fibonacci retracement of the average trend line (blue line in Figure 2). Using Fibonacci retracement bands on bottom and inverse (i.e. 1/x) on top allows to look at market movements in ab bit more detail.

Figure 6: Fibonacci retracement bands on bottom and inverse bands on top of the trend line

It becomes even easier when the normalizing the market cap data to show movement between horizontal trend lines (Figure 7).

Figure 7: Fibonacci retracement bands on normalized market cap

A few immediate observations include:

  • At the peaks in late 2013 and early 2018, the market touched the 1/0.236 Fibonacci retracement trend line which seems to be a major resistance
  • During the bear markets in 2015 and 2016 as well as late 2018 and early 2019, the market similarly touched the 0.236 Fibonacci retracement trend line which seems to be a major support
  • The other bands seem to provide strong resistance and support as well, especially the 0.618 line as seen on multiple occasions
  • Strongest volatility seems to happen in the middle regions between the 1/0.618 and the 0.618 Fibonacci retracement lines
  • A crossing of the 0.5 Fibonacci retracement line seems to increase the likelihood of ending a bear market

Potential Applications for This Model

The described model can be used to determine the trend as well as Fibonacci retracement values for any specific date with only the maximum growth scenario needed as a static input parameter.

Figure 8: Example calculation for a 10 tUSD maximum growth scenario for 2-Jun 2019

Provided the model holds true, these calculations can help:

  1. Determine if a peak or bottom has been reached during a market cycle
  2. Determine macro resistances & supports for a specific date
  3. Comparing asset costs from different market cycles by normalizing them to the trend line
  4. And of course, determine the future price of market dominating assets

So when will Bitcoin hit 100.000? Using the scenario with a 10 trillion USD maximum and assuming a continued 50%-ish market dominance, Bitcoin would hit 100.000 USD in mid 2021. However, this is based on the average growth, so future bull / bear market conditions will still shift the date.


When Will Bitcoin Hit 100.000? was originally published in Coinmonks on Medium, where people are continuing the conversation by highlighting and responding to this story.