Ethereum issuance equation
Bitcoin block rewards are new bitcoins awarded to cryptocurrency miners for being the first to solve a complex math problem and creating a new block of verified bitcoin transactions. The miners use networks of computers to do this, and every time a new block is created it is verified by all the other competing miners. Then a new math problem is introduced and the miners start over. The block reward provides an incentive for bitcoin miners to process transactions made with the cryptocurrency.
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- The Truth About Blockchain
- What Is Ethereum 2.0 and When Will It Happen?
- What Are Automated Market Makers?
- Monetary Policy
- Mastering Bitcoin by
- Ether: The Birth of the Digital Bond
- Ethereum just activated a major change called the 'London hard fork' — here's why it's a big deal
- Research: Yes you can calculate the total supply of ether
The Truth About Blockchain
In proof of work PoW based public blockchains e. Bitcoin and the current implementation of Ethereum , the algorithm rewards participants who solve cryptographic puzzles in order to validate transactions and create new blocks i.
In PoS-based public blockchains e. Significant advantages of PoS include security, reduced risk of centralization, and energy efficiency. In general, a proof of stake algorithm looks as follows.
The process of creating and agreeing to new blocks is then done through a consensus algorithm that all current validators can participate in. From an algorithmic perspective, there are two major types: chain-based proof of stake and BFT -style proof of stake. In chain-based proof of stake , the algorithm pseudo-randomly selects a validator during each time slot eg. Note that blocks may still be chained together ; the key difference is that consensus on a block can come within one block, and does not depend on the length or size of the chain after it.
There are several fundamental results from Byzantine fault tolerance research that apply to all consensus algorithms, including traditional consensus algorithms like PBFT but also any proof of stake algorithm and, with the appropriate mathematical modeling, proof of work.
Proof of work has been rigorously analyzed by Andrew Miller and others and fits into the picture as an algorithm reliant on a synchronous network model. We can model the network as being made up of a near-infinite number of nodes, with each node representing a very small unit of computing power and having a very small probability of being able to create a block in a given period.
Proof of stake consensus fits more directly into the Byzantine fault tolerant consensus mould, as all validators have known identities stable Ethereum addresses and the network keeps track of the total size of the validator set. There are two general lines of proof of stake research, one looking at synchronous network models and one looking at partially asynchronous network models.
A line of research connecting traditional Byzantine fault tolerant consensus in partially synchronous networks to proof of stake also exists, but is more complex to explain; it will be covered in more detail in later sections.
Proof of work algorithms and chain-based proof of stake algorithms choose availability over consistency, but BFT-style consensus algorithms lean more toward consistency; Tendermint chooses consistency explicitly, and Casper uses a hybrid model that prefers availability but provides as much consistency as possible and makes both on-chain applications and clients aware of how strong the consistency guarantee is at any given time. In many early all chain-based proof of stake algorithms, including Peercoin, there are only rewards for producing blocks, and no penalties.
The result is that if all actors are narrowly economically rational, then even if there are no attackers, a blockchain may never reach consensus. This can be solved via two strategies. This changes the incentive structure thus:. Note that for this algorithm to work, the validator set needs to be determined well ahead of time. This can only be avoided if the validator selection is the same for every block on both branches, which requires the validators to be selected at a time before the fork takes place.
This has its own flaws, including requiring nodes to be frequently online to get a secure view of the blockchain, and opening up medium-range validator collusion risks ie. The second strategy is to simply punish validators for creating blocks on the wrong chain. This changes the economic calculation thus:.
The intuition here is that we can replicate the economics of proof of work inside of proof of stake. In proof of work, there is also a penalty for creating a block on the wrong chain, but this penalty is implicit in the external environment: miners have to spend extra electricity and obtain or rent extra hardware.
Here, we simply make the penalties explicit. This mechanism has the disadvantage that it imposes slightly more risk on validators although the effect should be smoothed out over time , but has the advantage that it does not require validators to be known ahead of time.
If we have a set of slashing conditions that satisfies both properties, then we can incentivize participants to send messages, and start benefiting from economic finality. Economic finality is the idea that once a block is finalized, or more generally once enough messages of certain types have been signed, then the only way that at any point in the future the canonical history will contain a conflicting block is if a large number of people are willing to burn very large amounts of money.
If a node sees that this condition has been met for a given block, then they have a very economically strong assurance that that block will always be part of the canonical history that everyone agrees on. The two approaches to finality inherit from the two solutions to the nothing at stake problem: finality by penalizing incorrectness, and finality by penalizing equivocation. Casper follows the second flavor, though it is possible that an on-chain mechanism will be added where validators can voluntarily opt-in to signing finality messages of the first flavor, thereby enabling much more efficient light clients.
Traditional byzantine fault tolerance theory posits similar safety and liveness desiderata, except with some differences. From a liveness perspective, our model is the easier one, as we do not demand a proof that the network will come to consensus, we just demand a proof that it does not get stuck. The proof of this basically boils down to the fact that faults can be exhaustively categorized into a few classes, and each one of these classes is either accountable ie. Suppose that deposits are locked for four months, and can later be withdrawn.
However, suppose that such an attack happens after six months. Then, even though the blocks can certainly be re-imported, by that time the malfeasant validators will be able to withdraw their deposits on the main chain, and so they cannot be punished. Note that this rule is different from every other consensus rule in the protocol, in that it means that nodes may come to different conclusions depending on when they saw certain messages.
This is only possible in two cases:. They can do this by asking their friends, block explorers, businesses that they interact with, etc. In practice, such a block hash may well simply come as part of the software they use to verify the blockchain; an attacker that can corrupt the checkpoint in the software can arguably just as easily corrupt the software itself, and no amount of pure cryptoeconomic verification can solve that problem.
Note that all of this is a problem only in the very limited case where a majority of previous stakeholders from some point in time collude to attack the network and create an alternate chain; most of the time we expect there will only be one canonical chain to choose from.
If UHT is used, then a successful attack chain would need to be generated secretly at the same time as the legitimate chain was being built, requiring a majority of validators to secretly collude for that long. Unlike reverts, censorship is much more difficult to prove.
However, there are a number of techniques that can be used to mitigate censorship issues. The first is censorship resistance by halting problem.
In the weaker version of this scheme, the protocol is designed to be Turing-complete in such a way that a validator cannot even tell whether or not a given transaction will lead to an undesired action without spending a large amount of processing power executing the transaction, and thus opening itself up to denial-of-service attacks.
This is what prevented the DAO soft fork. In the stronger version of the scheme, transactions can trigger guaranteed effects at some point in the near to mid-term future. Hence, a user could send multiple transactions which interact with each other and with predicted third-party information to lead to some future event, but the validators cannot possibly tell that this is going to happen until the transactions are already included and economically finalized and it is far too late to stop them; even if all future transactions are excluded, the event that validators wish to halt would still take place.
Note that in this scheme, validators could still try to prevent all transactions, or perhaps all transactions that do not come packaged with some formal proof that they do not lead to anything undesired, but this would entail forbidding a very wide class of transactions to the point of essentially breaking the entire system, which would cause validators to lose value as the price of the cryptocurrency in which their deposits are denominated would drop.
The second, described by Adam Back here , is to require transactions to be timelock-encrypted. Hence, validators will include the transactions without knowing the contents, and only later could the contents automatically be revealed, by which point once again it would be far too late to un-include the transactions.
If validators were sufficiently malicious, however, they could simply only agree to include transactions that come with a cryptographic proof eg. ZK-SNARK of what the decrypted version is; this would force users to download new client software, but an adversary could conveniently provide such client software for easy download, and in a game-theoretic model users would have the incentive to play along.
Hence, all in all this scheme is also moderately effective, though it does come at the cost of slowing interaction with the blockchain down note that the scheme must be mandatory to be effective; otherwise malicious validators could much more easily simply filter encrypted transactions without filtering the quicker unencrypted transactions. A third alternative is to include censorship detection in the fork choice rule.
The idea is simple. If all nodes follow this strategy, then eventually a minority chain would automatically coalesce that includes the transactions, and all honest online nodes would follow it. The main weakness of such a scheme is that offline nodes would still follow the majority branch, and if the censorship is temporary and they log back on after the censorship ends then they would end up on a different branch from online nodes.
Hence, this scheme should be viewed more as a tool to facilitate automated emergency coordination on a hard fork than something that would play an active role in day-to-day fork choice. In any chain-based proof of stake algorithm, there is a need for some mechanism which randomly selects which validator out of the currently active validator set can make the next block. In non-chain-based algorithms randomness is also often needed for different reasons. For example:. There are several main strategies for solving problems like 3.
The first is to use schemes based on secret sharing or deterministic threshold signatures and have validators collaboratively generate the random value. The second is to use cryptoeconomic schemes where validators commit to information ie. There are two theoretical attack vectors against this:. Hence, all in all, many known solutions to stake grinding exist; the problem is more like differential cryptanalysis than the halting problem - an annoyance that proof of stake designers eventually understood and now know how to overcome, not a fundamental and inescapable flaw.
In this case, there now exist two incompatible finalized histories, creating a split of the blockchain, that full nodes would be willing to accept, and so it is up to the community to coordinate out of band to focus on one of the branches and ignore the other s. This coordination could take place on social media, through private channels between block explorer providers, businesses and exchanges, various online discussion forms, and the like.
Once there is consensus on which chain is real, users ie. In this case, blocks would never finalize. If no blocks are finalized for some long period of time eg. In case 2 , the fork would once again be coordinated via social consensus and possibly via market consensus ie. One can imagine an implementation of 1 where nodes automatically accept a switch to a new validator set if they do not see a new block being committed for a long enough time, which would reduce the need for social coordination but at the cost of requiring those nodes that do not wish to rely on social coordination to remain constantly online.
In either case, a solution can be designed where attackers take a large hit to their deposits. This could range from a mild censorship attack which only censors to interfere with a few specific applications eg.
There are two sub-cases. Here, we can program validators to refuse to finalize or build on blocks that they subjectively believe are clearly censoring transactions, which turns this kind of attack into a more standard liveness attack. Here, the attacker can freely block any transactions they wish to block and refuse to build on any blocks that do contain such transactions.
There are two lines of defense. First, because Ethereum is Turing-complete it is naturally somewhat resistant to censorship as censoring transactions that have a certain effect is in some ways similar to solving the halting problem. This resistance is not perfect , and there are ways to improve it.
The most interesting approach is to add in-protocol features where transactions can automatically schedule future events, as it would be extremely difficult to try to foresee what the result of executing scheduled events and the events resulting from those scheduled events would be ahead of time.
The most effective way to do this would be for nodes to repeatedly send a transaction to schedule depositing their ether and then cancel the deposit at the last moment.
Hence, the recovery techniques described above will only be used in very extreme circumstances; in fact, advocates of proof of work also generally express willingness to use social coordination in similar circumstances by, for example, changing the proof of work algorithm. Hence, it is not even clear that the need for social coordination in proof of stake is larger than it is in proof of work. In reality, we expect the amount of social coordination required to be near-zero, as attackers will realize that it is not in their benefit to burn such large amounts of money to simply take a blockchain offline for one or two days.
This is an argument that many have raised, perhaps best explained by Paul Sztorc in this article. Locking up X ether in a deposit is not free; it entails a sacrifice of optionality for the ether holder. I also lose some freedom to change my token allocations away from ether within that timeframe; I could simulate selling ether by shorting an amount equivalent to the deposit on an exchange, but this itself carries costs including exchange fees and paying interest.
The answer is no, for both reasons 2 and 3 above. Let us start with 3 first. The above included a large amount of simplified modeling, however it serves to show how multiple factors stack up heavily in favor of PoS in such a way that PoS gets more bang for its buck in terms of security. The meta-argument for why this perhaps suspiciously multifactorial argument leans so heavily in favor of PoS is simple: in PoW, we are working directly with the laws of physics.
What Is Ethereum 2.0 and When Will It Happen?
Liquidity Pools and Liquidity Providers. Constant Product Formula. Automated Market Maker Variations. By Cryptopedia Staff. They allow digital assets to be traded in a permissionless and automatic way by using liquidity pools rather than a traditional market of buyers and sellers. AMM users supply liquidity pools with crypto tokens, whose prices are determined by a constant mathematical formula. Liquidity pools can be optimized for different purposes, and are proving to be an important instrument in the DeFi ecosystem.
What Are Automated Market Makers?
I know ETH deflation is consensus right now. I'll operationalize 'medium term' time horizon as These dates are mostly arbitrary, but I'll use them to make my predictions falsifiable and because gives adequate time for Proof of Stake to have completed and staking markets to have matured. Also, as I wrote this I used the term 'inflationary' to mean 'total supply is increasing' and 'deflationary' to mean 'total supply is decreasing. This thread is built on the back of two recent pieces. Specifically, my key point is that gas markets reflect what investors are willing to pay to transact. Gas prices are a function of the opportunity cost of not transacting. Concretely, if ETH goes up 10x and settles at a new price, gas prices may not settle at 10x. Ultimately, the gas price represents purchasing power you give up to transact, whether priced in ETH or USD or whatever. The key part is the discussion of the monetary policy, so I'll link to it but you can just read the content in these photos for the relevant sections.
Home » Guides » Blockchain Startups. Ameer Rosic. To a beginner, the entire concept of Ethereum and Ethereum token can get very confusing very fast. The idea that ethereum not only has its own currency Ether but also has tokens on top of that which can act as currency themselves, can be a little mind-boggling. If you would like an intensive walkthrough of Ethereum please check out our dedicated blockchain courses on ethereum.
Mastering Bitcoin by
Are you looking for a higher-risk investment to round out your investment portfolio? Cryptocurrency might be a good investment option for you. The cryptocurrency market is dominated by two major players: Ethereum and Bitcoin. Bitcoin is the most popular cryptocurrency in the world, while Ethereum is the second. For many investors that are considering jumping into the world of cryptocurrencies, the first thing they do is compare Ethereum vs.
Ether: The Birth of the Digital Bond
This is a crucial point among proponents of sound monetary systems and sovereign money, since controlling the supply is essential to the soundness of money. Anyone hit by high inflation, that is insufficient control of the supply, is a witness of the opposite. There has been some debate about the ether supply in the last few years. The debate often boils down to questions such as: Is the current ether supply known with sufficient precision? Is the future supply known? And, can users audit the Ethereum supply? Thanks to research done by BitMEX Research, it now seems possible to calculate the total supply of ether with precision.
Ethereum just activated a major change called the 'London hard fork' — here's why it's a big deal
In proof of work PoW based public blockchains e. Bitcoin and the current implementation of Ethereum , the algorithm rewards participants who solve cryptographic puzzles in order to validate transactions and create new blocks i. In PoS-based public blockchains e.
Research: Yes you can calculate the total supply of ether
Blockchain promises to solve this problem. The technology behind bitcoin, blockchain is an open, distributed ledger that records transactions safely, permanently, and very efficiently. For instance, while the transfer of a share of stock can now take up to a week, with blockchain it could happen in seconds. Blockchain could slash the cost of transactions and eliminate intermediaries like lawyers and bankers, and that could transform the economy. In this article the authors describe the path that blockchain is likely to follow and explain how firms should think about investments in it.
Similar to shares, the ETPs can be bought and sold whenever the stock exchange is open as prices are quoted throughout the day. The ETPs can be purchased through tax efficient wrappers. Why networks use airdrops, how they compare to hard forks, and how CoinShares will treat them. We continue to closely monitor the developments in the Ethereum protocol. We have received a number of investor inquiries as to our policy with respect to ETH.
A bonding curve is a mathematical curve that defines the relationship between the price and the supply of a given asset. A bonding curve is a mathematical concept used to describe the relationship between price and the supply of an asset. The basis of the bonding curve is the idea that when a person purchases an asset that is available in a limited quantity like Bitcoin , then each subsequent buyer will have to pay slightly more for it. The reason for this increase in price is that the number of available asset units decreases with each one that is acquired.