Category Archives: Crypto

ETH Inflation Rate: 5%

Source: TrustNodes, Jan 2020

an inflation rate of circa 5% a year which will increase a bit further potentially this summer once hybrid Proof of Stake (PoS) launches.

Then onwards it looks probable it will stay around these levels until around September 2021 when the difficulty bomb is to kick-in again.

Around that time full Proof of Stake might launch, at which point the Proof of Work (PoW) chain is set to be discarded.

This 5% inflation from the PoW chain will be discarded with it, leaving an inflation rate of only 0.22%.

These timings however are an estimate as are future inflation levels as packaging the PoW chain into a PoS first shard is very complex and something to be done with great care.

Yet the aim is to eventually get down to this 0.22% inflation level, but in the meantime ethereum’s inflation will stay at 5%.

90% of All ETH Wallets Now ‘Out-of-the-Money’

Source: CoinDesk, Jan 2020

The second-largest cryptocurrency, which powers ethereum’s blockchain, is currently trading at $131, representing a 90 percent drop from the all-time high of $1,431 reached in early January 2018, according to CoinDesk’s ether price index.

The relentless price slide has pushed 90 percent or 31.31 million ether addresses “out-of-the-money,” according to blockchain intelligence firm IntoTheBlock.

An address is said to be out-of-the-money if the current price of ether is lower than the average price at which the coins were acquired or sent to an address.

So, the 31.31 million ether addresses have acquired coins at an average price higher than the ether’s current value of $131.

A major chunk of out-of-the-money addresses purchased coins in the range of $211 to $530. Notably, the biggest cluster, some 4.77 million addresses, is in an average cost range of $262 to $352.

Meanwhile, a mere 8 percent or 2.79 million addresses are “in-the-money” – the cost of acquisition is lower than the current price of ether – and 1.78 percent addresses are “at-the-money,” with an average purchase purchase price almost equal to the current spot price.

The majority of the in-the-money addresses have acquired coins in the range of $0 to $130, while 4,120 addresses have an average cost of $0. These could be early buyers who bought ether in the period between August  2015 and December 2015, when the cryptocurrency was trading in cents.

While the number of addresses in-the-money is small, the volume of ether these addresses are holding is quite significant.

Only 8 percent of addresses are in-the-money, but hold 31.24 percent of the total ether held in all addresses. That amounts to 34.05 million ethers ($4.5 billion).

These investors have already seen their massive profits evaporate in the last 23 months and may offload their holdings if prices find acceptance under $100, adding to bearish pressures around ether.

Out-of-the-money addresses are holding 73.13 million ethers. Clusters of addresses with an average price in the range of $144-$170, $212-$262, or $262-$352 are holding a total of 36.24 million ethers.

A few observers believe ethereum’s persistent scalability issues likely dented investor confidence, leading to a price drop.

Ethereum has consistently missed deadlines for protocol upgrades,” said Connor Abendschein, research analyst at Digital Assets Data, to CoinDesk. “Ethereum 2.0 was supposed to have already gone into effect earlier this year, and it still hasn’t gone through.”

Ethereum 2.0 is a major network upgrade that will shift the blockchain’s current proof-of-work consensus algorithm to proof-of-stake and transfer validation function from miners to special network validators.

Under proof-of-work, miners compete with each other to solve a difficult puzzle (algorithm) to add each block to the chain. Under proof-of-stake, there is no competition as the block creator is selected based on the user’s stake in the project – in other words, ether holdings.

The market is expecting the first upgrade to be rolled out in January 2020. Ryan Selkis, CEO of Messari, however, thinks the transition won’t happen until 2022.

Bitcoin Gained Almost 9,000,000% (90,000X) in the Last Decade (2010-2019)

Source:, Dec 2019

Netflix gained +4,177%, Amazon (+1,787%) Apple (+966%), Microsoft (+556%), Disney: (+423%) and Google (+335%), gold only saw a +38% gain. Bitcoin rose by +8.9 million percent between January 2010 up until now.

China Dominates Bitcoin Mining (Hashrate) – 65%

Source: ZeroHedge, Dec 2019

In June, China’s Bitcoin miners controlled 60% of the global hash rate, and now the figure is up to 65% in December.

Mining crypto has become more difficult over the last several years as profitability sags. The overall Bitcoin hash rate has risen 80% since June, which in recent times, has created stronger profitability for miners who have access to cheap electricity.

ETH’s Initial 2015 Distribution

Source: TrustNodes, Dec 2019

On July the 30th 2015, at 3:26 PM London time, 8,893 transactions were undertaken, with the very first transaction being for 1337 eth.

The ethereum genesis block had just launched, and with it, a massive distribution of eth to nearly 9,000 accounts.

Analysis of this historic moment are sparse, but 72 million eth was created on that day. 60 million went to these 9,000 accounts, and 12 million went to the founding team.

… an ethereum protocol development ecosystem that is hardly managing. Here Péter Szilágyi, who describes his position as Team Lead at the Ethereum Foundation, describing what has gone wrong for eth1x:

“I think the issue stems from everyone jumping on the Eth2 train. That’s all the rage for the past 2 years now, and it just siphons attention away from the system that actually works today. The people remaining behind are just spread too thinly to pay attention to everything.”

Wilcke of course coded geth. That’s what he got all these millions for, but now he’d rather deal with games than work on what he was paid for.

Yet so much remains unknown. Was there a contract? Between who? What were the terms? What were the conditions? Has this contract been breached?

Related Resource: TrustNodes, Dec 2019

Vitalik Buterin, ethereum’s co-founder and its leading figure, promised Proof of Stake (PoS) in 9-12 months all the way back in 2015.

On July 28th 2015, just two days before the ethereum genesis block launched, an etherean said: “I was under the impression that the switch to PoS would happen rather soon (~1 year).” (of 2015)

However, the ethereum development team was not quite working on Proof of Stake in 2015 or 2016.

… even in 2017 there wasn’t much focus on PoS.

As a hybrid version of it was about to launch in mid-2018, the whole thing was completely scrapped in a surprise move.

.. with full Proof of Stake unlikely before circa 2021.



China Dominates Hashrate Processing

Source: ZeroHedge, Dec 2019

China’s Bitcoin miners now control a whopping 66% of the world’s crypto network’s processing power. This could be bad news for US miners as it signals China is quickly advancing.

Also known as “hashrate,” it’s the speed at which a computer is performing an operation in Bitcoin code to unlock coins, China has been steadily gaining hashrate share this year.

Vitalik Buterin’s Review of 2014 Crypto Challenges

Source: Buterin website, Dec 2019

  1. Useful Proof of Work

making the proof of work function something which is simultaneously useful;

a common candidate is something like Folding@home, an existing program where users can download software onto their computers to simulate protein folding and provide researchers with a large supply of data to help them cure diseases.

Status: Probably not feasible, with one exception

The challenge with useful proof of work is that a proof of work algorithm requires many properties:

  • Hard to compute
  • Easy to verify
  • Does not depend on large amounts of external data
  • Can be efficiently computed in small “bite-sized” chunks

Unfortunately, there are not many computations that are useful that preserve all of these properties, and most computations that do have all of those properties and are “useful” are only “useful” for far too short a time to build a cryptocurrency around them.

However, there is one possible exception: zero-knowledge-proof generation. Zero knowledge proofs of aspects of blockchain validity (eg. data availability roots for a simple example) are difficult to compute, and easy to verify.

Furthermore, they are durably difficult to compute; if proofs of “highly structured” computation become too easy, one can simply switch to verifying a blockchain’s entire state transition, which becomes extremely expensive due to the need to model the virtual machine and random memory accesses.

Zero-knowledge proofs of blockchain validity provide great value to users of the blockchain, as they can substitute the need to verify the chain directly; Coda is doing this already, albeit with a simplified blockchain design that is heavily optimized for provability. Such proofs can significantly assist in improving the blockchain’s safety and scalability.

That said, the total amount of computation that realistically needs to be done is still much less than the amount that’s currently done by proof of work miners, so this would at best be an add-on for proof of stake blockchains, not a full-on consensus algorithm.

  1. Decentralized Public Goods Incentivization

One of the challenges in economic systems in general is the problem of “public goods”.

For example, suppose that there is a scientific research project which will cost $1 million to complete, and it is known that if it is completed the resulting research will save one million people $5 each. In total, the social benefit is clear … [but] from the point of view of each individual person contributing does not make sense …

So far, most problems to public goods have involved centralization Additional Assumptions And Requirements: A fully trustworthy oracle exists for determining whether or not a certain public good task has been completed (in reality this is false, but this is the domain of another problem)

Status: Some progress

The problem of funding public goods is generally understood to be split into two problems: the funding problem (where to get funding for public goods from) and the preference aggregation problem (how to determine what is a genuine public good, rather than some single individual’s pet project, in the first place).

This problem focuses specifically on the former, assuming the latter is solved (see the “decentralized contribution metrics” section below for work on that problem).

In general, there haven’t been large new breakthroughs here. There’s two major categories of solutions. First, we can try to elicit individual contributions, giving people social rewards for doing so. My own proposal for charity through marginal price discrimination is one example of this; another is the anti-malaria donation badges on Peepeth.

Second, we can collect funds from applications that have network effects. Within blockchain land there are several options for doing this:

  • Issuing coins
  • Taking a portion of transaction fees at protocol level (eg. through EIP 1559)
  • Taking a portion of transaction fees from some layer-2 application (eg. Uniswap, or some scaling solution, or even state rent in an execution environment in ethereum 2.0)
  • Taking a portion of other kinds of fees (eg. ENS registration)

Outside of blockchain land, this is just the age-old question of how to collect taxes if you’re a government, and charge fees if you’re a business or other organization.

  1. Proof of excellence

One interesting, and largely unexplored, solution to the problem of [token] distribution specifically (there are reasons why it cannot be so easily used for mining) is using tasks that are socially useful but require original human-driven creative effort and talent.

For example, one can come up with a “proof of proof” currency that rewards players for coming up with mathematical proofs of certain theorems

Status: No progress, problem is largely forgotten

The main alternative approach to token distribution that has instead become popular is airdrops; typically, tokens are distributed at launch either proportionately to existing holdings of some other token, or based on some other metric (eg. as in the Handshake airdrop).

Verifying human creativity directly has not really been attempted, and with recent progress on AI the problem of creating a task that only humans can do but computers can verify may well be too difficult.

14 [sic]. Decentralized contribution metrics

Incentivizing the production of public goods is, unfortunately, not the only problem that centralization solves.

The other problem is determining, first, which public goods are worth producing in the first place and, second, determining to what extent a particular effort actually accomplished the production of the public good. This challenge deals with the latter issue.

Status: Some progress, some change in focus

More recent work on determining value of public-good contributions does not try to separate determining tasks and determining quality of completion; the reason is that in practice the two are difficult to separate.

Work done by specific teams tends to be non-fungible and subjective enough that the most reasonable approach is to look at relevance of task and quality of performance as a single package, and use the same technique to evaluate both.

Fortunately, there has been great progress on this, particularly with the discovery of quadratic funding. Quadratic funding is a mechanism where individuals can make donations to projects, and then based on the number of people who donated and how much they donated, a formula is used to calculate how much they would have donated if they were perfectly coordinated with each other (ie. took each other’s interests into account and did not fall prey to the tragedy of the commons).

The difference between amount would-have-donated and amount actually donated for any given project is given to that project as a subsidy from some central pool (see #11 for where the central pool funding could come from). Note that this mechanism focuses on satisfying the values of some community, not on satisfying some given goal regardless of whether or not anyone cares about it. Because of the complexity of values problem, this approach is likely to be much more robust to unknown unknowns.

Quadratic funding has even been tried in real life with considerable success in the recent gitcoin quadratic funding round. There has also been some incremental progress on improving quadratic funding and similar mechanisms; particularly, pairwise-bounded quadratic funding to mitigate collusion. There has also been work on specification and implementation of bribe-resistant voting technology, preventing users from proving to third parties who they voted for; this prevents many kinds of collusion and bribe attacks.