Most metrics aimed at timing or quantifying Bitcoin’s market cycles, from a fundamental perspective, have by and large focused on the velocity of value settled on chain, or lack there of, thus analysing the cycles from a buyer/investor’s perspective. Realised Cap, NVT Ratio, Market-Value-to- Realised-Cap (MVRV) and HODL Waves are just a few powerful metrics and visuals that have provided valuable insight.
Another type of metric, which has recently gained some attention in the Crypto community, is the the Dollar Value of Mined Coins on daily basis or Bitcoin’s Daily Issuance. This metric proved to have consistently identify all the swing lows based on previous All Time Highs like clockwork. …
As stated in all the previous articles, the only way to make sense of NVT (Signal) Ratio at this point in time is by adjusting it for inflation of Bitcoin’s Coin Supply a.k.a. the Wookalich Ratio. Furthermore, incorporating some hypothetical percentage of off-chain Transaction Volume would be a sensible way of staying true to the meaning of this metric and thus retain its usefulness as a barometer of Bitcoin’s market cycle.
Two profitability mining metrics have been developed in order to gauge the selling pressure coming from these Mandatory Sellers. The 24th of February flash sell-off provided new evidence that a new uptrend in profitability is establishing, a positive feedback loop that will slowly but surely carry us into the next halving and a new bull market in Bitcoin. …
January Wrap-up & Updates
The NVT Signal continues its upward skew as it fails to take into account the coin supply factor. Factors such as the Transaction Volume over the Lightning Network and Liquid side-chain are not sufficient to mitigate for such a trend, as its gradient became obvious before their launch and sufficient adoption.
Nevertheless, it is sensible to assume that Lightning Network, with a sharp increase in channel capacity in mid November of c. 450% is accounting for ever more significant portion of the transaction volume that would otherwise have been settle solely on-chain. …
In spite of the contentious Bitcoin Cash fork dominating the headlines of the past week, this postmortem chooses to focus on the selloff in Bitcoin (inevitably followed by all other cryptocurrencies). It is merely out of convenience to conduct this analysis on a fresh subject, rather than a much messier endeavour in analysing a subject that has been dead in the water for over a year.
From the last article:
“For the Mining Profitability Ratio to touch baseline at the end of October, the price of Bitcoin would have to take a dive down to anywhere in between $5,385 and $4,406, assuming 10% increase or decrease from current hash rate respectively, and an average mining revenue of c. …
The PetaHashDollar (PHD) metric is a robust way to quantifying mining profitability over short timeframe, while also broadly describing the progress in mining efficiency over longer timeframes. As outlined in PHD Ratio, Rock Bottom Mining & Peak Tether, the PHD metric is calculated by dividing Bitcoin’s Hash Rate (Daily PetaHashes) by Daily Mining Earnings (USD) to include block reward & transaction fees.
In this article, the data sources on which this metric relies have been changed. The methodology and rationale for doing so are described in the article What is the Price of Bitcoin or its Market Cap… Exactly? The rest of the data sources concerning this metric have also been changed after analysing and comparing several sources. …
This is a brief empirical analysis of the degree of randomness of the public keys/addresses, currently in use on the blockchain, for the purpose of ensuring that what is meant to be random theoretically, it is so in practice too.
BIP39, BIP32 and BIP44 have made significant progresses in standardising the private and public key generation, whilst at the same time not compromising their security by bringing a significant amount of entropy into the process.
However regardless of these developments, Bitcoin’s security is solely reliant on the robust cryptography derived from secp256k1 parameters within the ECDSA. This is also true for the majority of blockchains and pseudo- blockchains technologies currently in use. In addition to this, in what concerns the private to public key cryptography, the further obfuscation and compression of this encryption by sha256 in tandem with ripe160 plays also a factor. …
I claim I walked by the tide line
in pitch dark night
As not to step on the dogs that lay asleep on the beach,
Or on the ones that kept
to and fro barking at my feet.
For a torch I had only a lighthouse, perched
high on a cliff,
A beam that searched the darkness from the crests
of the palm trees
Far out into the Malabar Sea.
How did I end up here — washed up onto these shores,
at this forsaken hour?
This analysis aims to take a closer look at the NVT Signal/Ratio adjusted for Bitcoin’s inflation in circulating supply, in the light of recent price developments and comparing it to the original NVT Ratio/Signal developed by Willy Woo and Dimitri Kalichkin. The data of these ratios, provides a good insight regarding the current market cycle, as well as a better understanding of the wider perspective in regard to the relevance & applicability of these metrics going forward.
“Bitcoin’s NVT Ratio Normalised for Inflation in the Circulating Supply” will be referred to as: Wookalich Ratio for short and as credit to the developers of the original NVT Ratio & Signal. …
This is perhaps a too of a granular look at Bitcoin’s price valuation & market cap data; hence I apologise for the clickbaity title… as the article will not actually tell you anything of substance about Bitcoin’s valuation unless you are doing data analysis OCD-style.
While searching for reliable / accurate data to incorporate into other metrics, there were a few details which stood out:
Bitcoin’s Hashrate (Daily PetaHashes) to Daily Mining Earnings (PetaHashDollar) is a robust metric to asses the day to day mining profitability. In addition, when plotted over the past five years, its overall trend represents a good way to quantify and visualise the relative progress in efficiency of ASICs (more specifically the inverse of that metric: 1/relative mining efficiency).