On May 6th, 2017, Bitcoin hit an all-time high in transactions processed on the network in a single day: it moved 375,000 transactions which accounted for a nominal output of about $2.5b. Average fees on the Bitcoin network had climbed over a dollar for the first time a couple days prior. And they kept climbing: by early June average fees hit an eye-watering $5.66. This was quite unprecedented. In the three-year period from Jan. 1 2014 to Jan. 1 2017, per-transaction fees had never exceeded 31 cents on a weekly average. And the hits kept coming. Before 2017 was over, average fees would top out at $48 on a weekly basis. When the crypto-recession set in, transaction count collapsed and fees crept back below $1.
During the most feverish days of the Bitcoin run-up, when normal users found themselves with balances that would cost more to send than they were worth, cries for batching — the aggregation of many outputs into a single transaction — grew louder than ever. David Harding had written a blog post on the cost-savings of batching at the end of August and it was reposted to the Bitcoin subreddit on a daily basis.
The idea was simple: for entities sending many transactions at once, clustering outputs into a single transaction was more space- (and cost-) efficient, because each transaction has a fixed data overhead. David found that if you combined 10 payments into one transaction, rather than sending them individually, you could save 75% of the block space. Essentially, batching is one way to pack as many transactions as possible into the finite block space available on Bitcoin.
When fees started climbing in mid-2017, users began to scrutinize the behavior of heavy users of the Bitcoin blockchain, to determine whether they were using block space efficiently. By and large, they were not — and an informal lobbying campaign began, in which these major users — principally exchanges — were asked to start batching transactions and be good stewards of the scarce block space at their disposal. Some exchanges had been batching for years, others relented and implemented it. The question faded from view after Bitcoin’s price collapsed in Q1 2018 from roughly $19,000 to $6000, and transaction load — and hence average fee — dropped off.
But we remained curious. A common refrain, during the collapse in on-chain usage, was that transaction count was an obfuscated method of apprehending actual usage. The idea was that transactions could encode an arbitrarily large (within reason) number of payments, and so if batching had become more and more prevalent, those payments were still occurring, just under a regime of fewer transactions.
Some sites popped up to report outputs and payments per day rather than transactions, seemingly bristling at the coverage of declining transaction count. However, no one conducted an analysis of the changing relationship between transaction count and outputs or payments. We took it upon ourselves to find out.
Table Of Contents:
Introduction to batching
Bonus content: UTXO consolidation
- Introduction to batching
Bitcoin uses a UTXO model, which stands for Unspent Transaction Output. In comparison, Ripple and Ethereum use an account/balance model. In bitcoin, a user has no balances, only UTXOs that they control. If they want to transfer money to someone else, their wallet selects one or more UTXOs as inputs that in sum need to add up to the amount they want to transfer. The desired amount then goes to the recipient, which is called the output, and the difference goes back to the sender, which is called change output. Each output can carry a virtually unlimited amount of value in the form of satoshis. A satoshi is a unit representing a one-hundred-millionth of a Bitcoin. This is very similar to a physical wallet full of different denominations of bills. If you’re buying a snack for $2.50 and only have a $5, you don’t hand the cashier half of your 5 dollar bill — you give him the 5 and receive some change instead.
Unknown to some, there is no hardcoded limit to the number of transactions that can fit in a block. Instead, each transaction has a certain size in megabytes and constitutes an economic incentive for miners to include it in their block. Because miners have limited space of 2 MB to sell to transactors, larger transactions (in size, not bitcoin!) will need to pay higher fees to be included. Additionally, each transaction can have a virtually unlimited number of inputs or outputs — the record stands at transactions with 20,000 inputs and 13,107 outputs.
So each transaction has at least one input and at one output, but often more, as well as some additional boilerplate stuff. Most of that space is taken up by the input (often 60% or more, because of the signature that proves they really belong to the sender), while the output(s) account for 15–30%. In order to keep transactions as small as possible and save fees, Bitcoin users have two major choices:
Use as few inputs as possible. In order to minimize inputs, you can periodically send your smaller UTXOs to yourself in times when fees are very low, getting one large UTXO back. That is called UTXO consolidation or consolidating your inputs.
Users who frequently make transfers (especially within the same block) can include an almost unlimited amount of outputs (to different people!) in the same transaction. That is called transaction batching. A typical single output transaction takes up 230 bytes, while a two output transaction only takes up 260 bytes, instead of 460 if you were to send them individually.
This is something that many casual commentators overlook when comparing Bitcoin with other payment systems — a Bitcoin transaction can aggregate thousands of individual economic transfers! It’s important to recognize this, as it is the source of a great deal of misunderstanding and mistaken analysis.
We’ve never encountered a common definition of a batched transaction — so for the purposes of this study we define it in the loosest possible sense: a transaction with three or more outputs. Commonly, batching is understood as an activity undertaken primarily by mining pools or exchanges who can trade off immediacy for efficiency. It is rare that a normal bitcoin user would have cause to batch, and indeed most wallets make it difficult to impossible to construct batched transactions. For everyday purposes, normal bitcoiners will likely not go to the additional effort of batching transactions.
We set the threshold at three for simplicity’s sake — a normal unbatched transaction will have one transactional output and one change output — but the typical major batched transaction from an exchange will have dozens if not hundreds of outputs. For this reason we are careful to provide data on various different batch sizes, so we could determine the prevalence of three-output transactions and colossal, 100-output ones.
We find it helpful to think of a Bitcoin transaction as a mail truck full of boxes. Each truck (transaction) contains boxes (outputs), each of contains some number of letters (satoshis). So when you’re looking at transaction count as a measure of the performance and economic throughput of the Bitcoin network, it’s a bit like counting mail trucks to discern how many letters are being sent on a given day, even though the number of letters can vary wildly. The truck analogy also makes it clear why many see Bitcoin as a settlement layer in the future — just as mail trucks aren’t dispatched until they’re full, some envision that the same will ultimately be the case for Bitcoin.
- A timeline
So what actually happened in the last six months? Let’s look at some data. Daily transactions on the Bitcoin network rose steadily until about May 2017, when average fees hit about $4. This precipitated the first collapse in usage. Then began a series of feedback loops over the next six months in which transaction load grew, fees grew to match, and transactions dropped off. This cycle repeated itself five times over the latter half of 2017.
more like this on coinmetrics.io
The solid red line in the above chart is fees in BTC terms (not USD) and the shaded red area is daily transaction count. You can see the cycle of transaction load precipitating higher fees which in turn cause a reduction in usage. It repeats itself five or six times before the detente in spring 2018. The most notable period was the December-January fee crisis, but fees were actually fairly typical in BTC terms — the rising BTC price in USD however meant that USD fees hit extreme figures.
In mid-November when fees hit double digits in USD terms, users began a concerted campaign to convince exchanges to be better stewards of block space. Both Segwit and batching were held up as meaningful approaches to maximize the compression of Bitcoin transactions into the finite block space available. Data on when exchanges began batching is sparse, but we collected information where it was available into a chart summarizing when exchanges began batching.
Batching adoption at selected exchanges
We’re ignoring Segwit adoption by exchanges in this analysis; as far as batching is concerned, the campaign to get exchanges to batch appears to have persuaded Bitfinex, Binance, and Shapeshift to batch. Coinbase/GDAX have stated their intention to begin batching, although they haven’t managed to integrate it yet. As far as we can tell, Gemini hasn’t mentioned batching, although we have some mixed evidence that they may have begun recently. If you know about the status of batching on Gemini or other major exchanges please get in touch.
So some exchanges have been batching all along, and some have never bothered at all. Did the subset of exchanges who flipped the switch materially affect the prevalence of batched transactions? Let’s find out.
3.1 How common is batching?
We measured the prevalence of batching in three different ways, by transaction count, by output value and by output count.
Batching accounts for roughly 12% of all transactions, 40% of all outputs, and 30–60% of all raw BTC output value. Not bad.
3.2 Have batched transactions become more common over time?
From the chart in 3.1, we can already see a small, but steady uptrend in all three metrics, but we want to dig a little deeper. So we first looked at the relationship of payments (all outputs that actually pay someone, so total outputs minus change outputs) and transactions.
More at transactionfee.info/charts
The first thing that becomes obvious is that the popular narrative — that the drop in transactions was caused by an increase in batching — is not the case; payments dropped by roughly the same proportion as well.
Dividing payment count by transaction count gives us some insight into the relationship between the two.
In our analysis we want to zoom into the time frame between November 2017 and today, and we can see that payments per transactions have actually been rallying, from 1.5 payments per transaction in early 2017 to almost two today.
3.3 What are popular batch sizes?
In this next part, we will look at batch sizes to see which are most popular. To determine which transactions were batched, we downloaded a dataset of all transactions on the Bitcoin network between November 2017 and May 2018from Blockchair.
We picked that period because the fee crisis really got started in mid-November, and with it, the demands for exchanges to batch. So we wanted to capture the effect of exchanges starting to batch. Naturally a bigger sample would have been more instructive, but we were constrained in our resources, so we began with the six month sample.
We grouped transactions into “batched” and “unbatched” groups with batched transactions being those with three or more outputs.
We then divided batched transactions into roughly equal groups on the basis of how much total output in BTC they had accounted for in the six-month period. We didn’t select the batch sizes manually — we picked batch sizes that would split the sample into equal parts on the basis of transaction value. Here’s what we ended up with:
All of the batch buckets have just about the same fraction of total BTC output over the period, but they account for radically different transaction and output counts over the period. Notice that there were only 183,108 “extra large” batches (with 41 or more outputs) in the six-month period, but between them there were 23m outputs and 30m BTC worth of value transmitted.
Note that output value in this context refers to the raw or unadjusted figure — it would have been prohibitively difficult for us to adjust output for change or mixers, so we’re using the “naive” estimate.
Let’s look at how many transactions various batch sizes accounted for in the sample period:
Batched transactions steadily increased relative to unbatched ones, although the biggest fraction is the small batch with between 3 and 5 outputs. The story for output counts is a bit more illuminating. Even though batched transactions are a relatively small fraction of overall transaction count, they contain a meaningful number of overall outputs. Let’s see how it breaks down:
Lastly, let’s look at output value. Here we see that batched transactions represent a significant fraction of value transmitted on Bitcoin.
As we can see, even though batched transactions make up an average of only 12% of all transactions, they move between 30%-60% of all Bitcoins, at peak times even 70%. We think this is quite remarkable. Keep in mind, however that the ‘total output’ figure has not been altered to account for change outputs, mixers, or self-churn; that is, it is the raw and unadjusted figure. The total output value is therefore not an ideal approximation of economic volume on the Bitcoin network.
3.4 Has transaction count become an unreliable measure of Bitcoin’s usage because of batching?
Yes. We strongly encourage any analysts, investors, journalists, and developers to look past mere transaction count from now on. The default measure of Bitcoin’s performance should be “payments per day” rather than transaction count. This also makes Bitcoin more comparable with other UTXO chains. They generally have significantly variable payments-per-transaction ratios, so just using payments standardizes that. (Stay tuned: Coinmetrics will be rolling out tools to facilitate this very soon.)
More generally, we think that the economic value transmitted on the network is its most fundamental characteristic. Both the naive and the adjusted figures deserve to be considered. Adjusting raw output value is still more art than science, and best practices are still being developed. Again, Coinmetrics is actively developing open-source tools to make these adjustments available.
We started by revisiting the past year in Bitcoin and showed that while the mempool was congested, the community started looking for ways to use the blockspace more efficiently. Attention quickly fell on batching, the practice of combining multiple outputs into a single transaction, for heavy users. We showed how batching works on a technical level and when different exchanges started implementing the technique.
Today, around 12% of all transactions on the Bitcoin network are batched, and these account for about 40% of all outputs and between 30–60% of all transactional value. The fact such that a small set of transactions carries so much economic weight makes us hopeful that Bitcoin still has a lot of room to scale on the base layer, especially if usage trends continue.
Lastly, it’s worth noting that the increase in batching on the Bitcoin network may not be entirely due to deliberate action by exchanges, but rather a function of its recessionary behavior in the last few months. Since batching is generally done by large industrial players like exchanges, mixers, payment processors, and mining pools, and unbatched transactions are generally made by normal individuals, the batched/unbatched ratio is also a strong proxy for how much average users are using Bitcoin. Since the collapse in price, it is quite possible that individual usage of Bitcoin decreased while “industrial” usage remained strong. This is speculation, but one explanation for what happened.
Alternatively, the industrial players appear to be taking their role as stewards of the scarce block space more seriously. This is a significant boon to the network, and a nontrivial development in its history. If a culture of parsimony can be encouraged, Bitcoin will be able to compress more data into its block space and everyday users will continue to be able to run nodes for the foreseeable future. We view this as a very positive development. Members of the Bitcoin community that lobbied exchanges to add support for Segwit and batching should be proud of themselves.
- Bonus content: UTXO consolidation
Remember that we said that a second way to systematically save transaction fees in the Bitcoin network was to consolidate your UTXOs when fees were low? Looking at the relationship between input count and output count allows us to spot such consolidation phases quite well.
Typically, inputs and outputs move together. When the network is stressed, they decouple. If you look at the above chart carefully, you’ll notice that when transactions are elevated (and block space is at a premium), outputs outpace inputs — look at the gaps in May and December 2017. However, prolonged activity always results in fragmented UTXO sets and wallets full of dust, which need to be consolidated. For this, users often wait until pressure on the network has decreased and fees are lower. Thus, after transactions decrease, inputs become more common than outputs. You can see this clearly in February/March 2017.
Here we’ve taken the ratio of inputs to outputs (which have been smoothed on a trailing 7 day basis). When the ratio is higher, there are more inputs than outputs on that day, and vice versa. You can clearly see the spam attack in summer 2015 in which thousands (possibly millions) of outputs were created and then consolidated. Once the ratio spikes upwards, that’s consolidation. The spike in February 2018 after the six weeks of high fees in December 2017 was the most pronounced sigh of relief in Bitcoin’s history; the largest ever departure from the in/out ratio norm. There were a huge number of UTXOs to be consolidated.
It’s also interesting to note where inputs and outputs cluster. Here we have histograms of transactions with large numbers of inputs or outputs. Unsurprisingly, round numbers are common which shows that exchanges don’t publish a transaction every, say, two minutes, but instead wait for 100 or 200 outputs to queue up and then publish their transaction. Curiously, 200-input transactions were more popular than 100-input transactions in the period.
We ran into more curiosities when researching this piece, but we’ll leave those for another time.
Future work on batching might focus on:
Determining batched transactions as a portion of (adjusted) economic rather than raw volume
Looking at the behavior of specific exchanges with regards to batching
Investigating how much space and fees could be saved if major exchanges were batching transactions
Lastly, we encourage everyone to run their transactions through the service at transactionfee.info
to assess the efficiency of their transactions and determine whether exchanges are being good stewards of the block space.
Antoine Le Calvez has created a series of live-updated charts to track batching and batch sizes, which you can find here.
We’d like to thank 0xB10C for their generous assistance with datasets and advice, the people at Blockchair for providing the core datasets, and David A. Harding for writing the initial piece and answering our questions.
The blockchain community
is not left out when it comes to the use of jargon and phrases. The use of words that look strange to those who are not involved in crypto is totally inevitable. It’s definitely going to be difficult for anyone not in this space to understand words like “ERC20, ICO or gas. So in order to help such people out, we have made a list of the most common cryptocurrency terms and definitions. Please sit back and enjoy your ride.
Cryptocurrency Terms And Definitions
One can categorize these terms into various parts. First of all, we will deal with general cryptocurrency terms and definitions.
Blockchains are distributed ledgers which are secured by cryptography. Everyone has access to read the information on every blockchain which means they are essentially public databases but the data update can only be done by the data owners. In the case of blockchains, data doesn’t remain on a single centralized server, they are copied across hundreds of thousands of computers worldwide. Projects such as Ethereum, Vechain, EOS etc. fall under this class of technology. Mining:
The means of trying to ‘solve’ the next available block. One needs huge amounts of computer processing power to carry this out effectively. There is always a reward for doing this. Mining rig:
A specially designed computer that processes proof-of-work blockchains such as Ethereum. They consist of multiple high-end graphic processors (GPUs) so as to maximize their processing power. Node:
This is a computer that has a copy of the blockchain and is working to keep it in a good shape. PoW:
The full meaning of this is Proof-of-work. The Ethereum network currently makes use of this algorithm. PoS:
Its full meaning is Proof-of-stake. It is the proposed future algorithm for Ethereum. Those that own ETH will be able to lock up all or a portion of their ether for a given amount of time in order to ‘vote’ and generate network consensus instead of mining in its current form. Stakeholders will get rewards in form of ETH by doing so. Fork:
This takes places when a certain blockchain splits into two different chains. This usually happens in the crypto space when new ‘governance rules’ are infused into the blockchain’s code. Software wallet:
A crypto-currency storage that exists purely on a computer as software files. You can generate these kinds of wallets for free from diverse sources. MyEtherWallet (MEW) is one of the most popular sources around. Hardware wallet:
A device that one can securely keep cryptocurrency. People often say that these wallets are the most secure way to store cryptocurrency. Examples of the most common hardware wallet models around are Ledger Nano S and Trezor. Cold storage:
This is a way of moving your cryptocurrency from an online wallet to an offline one, as a means of safekeeping them from hack. There are a lot of ways to carry this out. Some methods that are commonly used include:
· Using a hardware wallet to store your cryptocurrency.
· By printing out the QR code of a software wallet and keeping it somewhere which is safe.
· You can also move the files of a software wallet onto an external storage device such as USB drive and keeping it somewhere safe.
Trading Related Cryptocurrency Terms And Definitions Exchange:
These are websites where people trade (buy and sell) their cryptocurrencies. Some of the popular crypto exchanges we have around include Binance
, Poloniex, Bittrex etc. Market order / market buy / market sell:
A sale or purchase which is made on an exchange at the current price. A market buy acquires the cheapest Bitcoin available on the order book while a market sell fills up the most high-priced buy order on the books. Limit order / limit buy / limit sell:
These are orders which are placed by traders to buy or sell a cryptocurrency when the price reaches a certain amount. They are pretty much like ‘for-sale’ signs you see on goods. Sell wall / buy wall:
Cryptocurrency traders are able to see the current limit buy and sell points using a depth chart. The chart’s graphical representation is very much like a wall. FIAT:
Refer to a government-issued currency. An example is the US dollar. Whale:
A person who owns huge amounts of cryptocurrency. Margin trading:
This is an act of increasing the intensity of a trade by using your existing coins. It is very risky for an inexperienced trader to partake in this. Stay safe!! Going long:
This is a margin trade that gives profit if the price goes up. Going short:
It is a margin trade that gives profit if the price goes down. Bullish:
Being optimistic that the price of cryptocurrency is going to increase. Bearish:
This is an expectation that the price of cryptocurrency is going to decrease. ATH:
This simply means All-Time-High. This is the highest point that has been reached by a particular coin or token. Take for instance, Bitcoin’s ATH is about $20,000 and this was achieved around December 2017 and January 2018. Altcoin:
A word used to qualify other cryptocurrencies which is not Bitcoin. Examples of altcoins are Ripple, NEO, EOS, Vechain, Electroneum etc. Tokens:
These are ‘currency’ of projects which are hosted on the ethereum network. They raise money by issuing their own tokens to the general public. Tokens have a significant use in the project's ecosystem. Examples of tokens are Enjin Coin (ENJ), Zilliqa (ZIL), OmiseGO (OMG), Augur (REP) etc. ICO:
The full meaning is Initial Coin Offering. This is synonymous to an IPO in the non-crypto world. Startups give out their own token in exchange for Bitcoin or ether. Shilling / pumping:
An act of advertising another cryptocurrency. It is mostly done in a way that tricks as many people as possible into believing that a coin or token will get to a higher price in the future. Market Cap:
This is the total value of a cryptocurrency. To calculate this, one has to multiply the total supply of coins by the current market price. You can get a run-down of several cryptocurrency projects on Coinmarketcap
. Stable coin:
This is a cryptocurrency which has an extremely low volatility. You can use a stable coin to trade against the overall crypto market. Arbitrage:
A situation where a trader takes advantage of a difference in the price of the same coin / token on two different exchanges. FOMO:
Simply means Fear Of Missing Out. That overwhelming feeling that one needs to get on board when there is a massive rise in the price of a commodity. This is also applicable in the crypto space. FUD:
Fear, Uncertainty, and Doubt. It is a baseless negativity which is spread intentionally by someone or a group of people who want the price of cryptocurrency to decrease. FUDster:
A person who spreads FUD. Pump And Dump:
This happens when an altcoin gets a ton of attention, leading to a massive increase in price, and likewise followed by a big price crash of that altcoin. ROI:
Return on Investment. The percentage profit a trader makes on an initial investment (i.e. A 100% ROI simply indicates that a trader doubled his money). TA:
Trend Analysis or Technical Analysis. A way of examining current coin charts so as to make predictions for the next market movement.
Next, we will be moving on to crytocurrency terms and definitions
that are ethereum related. Dapp:
Decentralized Application. It is an application that uses a decentralized peer-to-peer network like Ethereum smart contract as its back-end code. Bagholder:
A person who still holds on to a particular altcoin despite having a pump and dump crash. Smart contract:
This is a code that is deployed onto the Ethereum blockchain, it often helps with the direct interaction of how money flows from one point to another. The Flippening:
A future event showing the capacity of Ethereum’s market cap (or some other cryptocurrency) surpassing Bitcoin’s market cap, making Ethereum the most ‘valuable’ crypto-currency. Gas:
It is a measurement of the amount of processing needed by the ethereum network to execute a transaction. More complex transactions like deploying a smart contract onto the network requires more gas than sending ether from one wallet to another which is obviously a simpler operation. Gas price:
This is the amount of ether an initiator of a transaction is willing to spend for each gas unit on a transaction. The higher the gas price, then the faster the processing of the transaction. Wei:
It is the smallest denomination of ether. Gwei:
This is a denomination of ether (ETH). Gwei is the unit for measuring gas prices. 1 Ether = 1,000,000,000 Gwei (109). MEW:
MyEtherWallet is a site where users can generate ethereum wallets for free.
We also have a handful of cryptocurrency terms and definitions that are memes. See some of them below; Hodl:
People use this word when signifying that a person is keeping his coins / tokens for a long period of time. A couple of years back, someone on a Bitcoin forum made a post with a typo HODL in place of HOLD. Ever since then, this term has become one of the most popularly used term in crypto. Mooning:
In crypto, this term comes to play when the price of cryptocurrencies move up astronomically. Lambo:
This is highly synonymous with crypto. You can't leave out this word when discussing about cryptocurrency terms and definitions. This is the car we’re all goona buy when crypto makes us rich. This is gentlemen:
People use this phrase when pointing out positive things that are currently taking place in the cryptosphere.
Now that you are conversant with some of the commonly used cryptocurrency terms and definitions, you can now go out there and showcase your new crypto vocabulary to the world.
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