Bitcoin course uses data science and predictive models to reveal 5 important conclusions in the search for the answer to the question: When moon?

Bitcoin (BTC) Course Rocket

The Bitcoin Halving is now almost exactly 6 months ago and although we may already experience a positive development in the Bitcoin course, the big „wow effect“ is still missing for many. The old all time high lies still in far distance and many still ask themselves therefore still: When moon?

Benjamin Cowen, founder of Into The Crypto Verse, has addressed this question by taking BTC’s historical price data from the last decade and using data science and predictive models to draw five important conclusions. With the help of these findings, participants should be able to better assess, based on the current Bitcoin price, which market cycle we are currently in.

When moon? Well, this much is already revealed at this point: You probably do not have much time left to accumulate BTC at these prices.

Investments in Bitcoin over the last decade have dwarfed the returns on most other investment vehicles.

While a quick glance at the Bitcoin price over a short period of time can still look somewhat discouraging, according to Cowen, this is because short-term price movements are best attributed to a random walk or geometric Brownian movement.

In his opinion, traditional technical analysis is often interspersed with waivers at every turn, and for every type of price movement that resembles some sort of textbook pattern, there are countless others that do not „go according to plan“.

Alternatively, a macro view of the Bitcoin course development results in something that can be deciphered somewhat better with the help of data science. A quick analysis shows that there are market cycles that have resulted in lower ROIs, while the realization of these ROIs takes longer. Put more simply, BTC’s macro trend shows a lengthening of cycles with decreasing ROIs in each market cycle.

In cases where an annual loss after a speculative bubble can exceed 80%, there is much to suggest that not only the time in the market is important, but also the timing of the market.

The time value of money is crucial in an era when it is all about defeating inflation.
The above diagram shows the price of Bitcoin and a logarithmic regression adjusted for „non-bubble“ data and speculative bubble peaks. Looking at the price from a high level, it is much easier to identify accumulation areas and speculative bubble formation.

To better understand these trends, we can calculate the percentage difference between the Bitcoin price and the logarithmic fair value regression fit, which is a monotonically increasing function (Fig. 2).

2. market cycles become less explosive

The graph below shows that the speculative bubble formation with respect to the fair value regression band becomes less and less explosive at each subsequent peak.

In fact, the percentage difference between the first peak at the Bitcoin price in 2011 and the logarithmic regression band is about 6,000%, while the second peak in 2013 is only about 3,000% above the band.

The third speculative bubble in 2017 peaked about 1,000% above the regression band. Although three data points certainly cannot constitute a definitive trend, we can at least speculate with the data available to us so far. For example 6000/3000 = 2 and 3000/1000 = 3. If this trend continues (which is of course a big „if“) and we see a division by 4 from the third bubble to the fourth, we can expect the Bitcoin price to be overvalued by about 250% in about three more years (2023).