Valuing BTC Using On-Chain Analysis

If Bitcoin and statistical models for Bitcoin pique your interest then this blog is worth tracking. The model tries to estimate if the current price of Bitcoin is overvalued or undervalued.

This is done by considering the price at which each BTC moves (i.e. realised price), the age of the tokens when they move (i.e. token age consumed), the nature of the address they move from and to (i.e. hodlers, fresh or short-term traders etc.), 1 yr. active supply and long-term volatility shifts. The idea is to gain an approximation for macro supply and demand for BTC, while also accounting for its nature as a store-of-value. All on-chain, arriving at a simple number I’m calling OBTC. Of course, it’s rather flawed to only consider on-chain activity, and most of the above-mentioned data are approximations at best. And yes, this accounts for halvings and declining volatility.

You can read more here and if you are keen to learn how you can take advantage of this model and use it to plan your entries over a longer period of time and also de-risking when BTC approaches bubble territory then this post on OBTC Valuation Gap is worth a read.

Anytime VG is in negative territory is the best time to accumulate. Extremes under -5 are increasingly rare and mark jackpot-tier opportunities. -1 to +1 often act as pivotal support/resistances, while +1 to +5 is general accumulation or distribution territory. Anything above +5 is in overvalued bubble territory, with numbers above +8 denoting a parabolic melt-up.

This is more suited towards positional traders interested in the macro outlook. However, if you are keen on building your portfolio in BTC over a long period of time then its worth some consideration.

Ofcourse, there may be other models for one to consider but today I found this quite interesting and worth a read. I hope this blog publishes a similar model for ETH in the near future.

^{This post is not financial advice.}