Dilutionproof @[email protected]

I'm excited to share "Modeling Value Based on Scarcity - A brief history of #Bitcoin Stock-to-Flow models"! 🔥

Like the title suggests; the article attempts to provide an overview of all developments in the S2F & S2FX models in an easy to understand way.

https://medium.com/@dilutionproof/modeling-value-based-on-scarcity-7fa7d754a58

LMAO off course this was meant to say that S2F is a surrogate of scarcity, not privacy 🤣

10/10 The article is concluded by stating that:

1) Bitcoin is designed to become more expensive - forever

2) No tops or rubber bands holding the #bitcoin price to any level

3) Given the obvious increasing demand, at some point demand increase > supply increase, which means 🚀

9/10 Finally, @btconometrics performs a different statistical technique (Fourier Analysis) to show that the #bitcoin price does in fact move in 4-year cycles thanks to its halvings - which is part of why S2F *seems* to work

8/10 @btconometrics then gives another example of a nonsensical model, illustrating that 93.5% of the #bitcoin price can be explained simply by the supply curve

This relationship is theoretically nonsensical and simply an artefact of both time series trending up

7/10 @btconometrics then suggests that instead of attempting to forecast price action, first principle reasoning on why #Bitcoin is (increasingly) valuable may provide a useful fundamental framework

6/10 Next target: the S2FX model, that was designed to overcome these limitations

His arguments:

1) The choice of creating 4 clusters was arbitrary & prone to bias

2) The fact that the phases monotonically increase over time would mean it is still a time series by definition

5/10 @btconometrics goes on to discuss the famous cointegration analysis (that he introduced himself in ‘19)

These analyses were originally thought to prove that S2F WAS non-spuriously related to price, which was invalidated by the fact that #Bitcoin S2F ratio is deterministic

4/10 He then introduces the “whitepaper to first block mined ratio” (WP2Rel) model, that does a better job at explaining the historical #bitcoin price, even after controlling for autoregression

The model is completely meaningless though and was essentially introduced as a parody

3/10 To prove point 2, @btconometrics recreates the S2F model & shows that:

1) The S2F model parameters look great at first

2) ... but after controlling for autoregression (the fact that price on any date is related to price on the day(s) before), S2F no longer predicts price

2/10 He sees three primary components to the underlying theory:

1) S2F is a surrogate of privacy -> undisputed

2) S2F causes the #bitcoin price rise -> disputed

3) S2F ratio can be used to estimate estimate the future #bitcoin price [in a statistically valid way] -> disputed

1/10 @btconometrics published a new critique on @100trillionUSD’s #Bitcoin Stock-to-Flow (S2F) & S2F Cross Asset (S2FX) models today, underlining the statistical flaws in both models

Time for a (hopefully simplifying) summary 🧵

https://btconometrics-84377.medium.com/bitcoin-and-stock-to-flow-7909784da261

Really enjoyed listening to this @stephanlivera podcast, where @IIICapital expresses a very accessible exploration of what the function and value of #Bitcoin in the financial markets of the future might look like
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RT @stephanlivera
SLP267 @IIICapital Joe Burnett - How Big Is The Market For #Bitcoin?

Joe and I chat:
- Why many are underestimating bitcoin's potential market
- valuation in a post hyperbitcoinization world
- growth…
https://twitter.com/stephanlivera/status/1381738845734010882

Looks like this was related to a scheduled maintenance. Perhaps a large entity that went fishing for some stop losses? 🤷‍♂️
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RT @Bitstamp
COMPLETED: All #Bitstamp services are back online after scheduled infrastructure upgrades. Thank you for your patience!
https://twitter.com/Bitstamp/status/1382273230766022657

Looks like @Bitstamp just might have had a liquidity or trading engine problem..? 👀

(The wick on this dip went much deeper than on other exchanges)

#Bitcoin closed at a new all-time high and thus highest daily close ever last night 🍾

If these price movements are another of iteration of its 4-year cycle, this #Bitcoin Halving Cycle Roadmap visualizes what can roughly be expected next based on various valuation models 👀

6/6 Finally, one address can represent many entities

Based on these numbers, ~15 exchanges hold ~13.3% of the #bitcoin supply; representing millions of entities

Source: https://twitter.com/n3ocortex/status/1356673243734822912

TL;DR: much more nuances apply to addresses than to mobile phone subscriptions
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RT @n3ocortex
"2% of accounts control 95% of all #Bitcoin "

Wrong.

BTC ownership is much less concentrat…
https://twitter.com/n3ocortex/status/1356673243734822912

5/6 Second, by looking at #bitcoin addresses holding ≥$1, dust addresses that hold less BTC than is needed to transact are increasingly included, as fees are trending upwards (in fiat terms) over time

As a result of this trend, aggregating demand in addresses will also increase

4/6 First, you can have large demand without a necessarily seeing a large uptick in address growth

For example; we've seen ~12k #BTC outflows from large exchanges over the past few months, often in 1 address

Important: Not all addresses represent the same amount of demand

3/6 While interesting, I think @TimmerFidelity's assumption that the number of addresses worth ≥$1 is an appropriate proxy for #bitcoin demand is flawed, and potentially causes an underestimation of the true demand for #bitcoin

I'll make three arguments:

2/6 In his 🧵, @TimmerFidelity observes that the growth of #bitcoin addresses worth ≥$1 follows a similar growth curve to that of mobile phone use

Based on the assumption that the number of addresses worth ≥$1 is thus a proxy for demand, a #bitcoin valuation model is presented