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Cryptocurrency and Blockchain Dictionary

A complete list of crypto definitions

Cryptocurrency and blockchain glossary

Commonly used terms in the world of blockchain and cryptocurrency

Accrued Liabilities

What Are Accrued Liabilities? Accrued liabilities are incurred when a business purchases goods and services on credit due to which they do not receive invoices at the time of the purchase. They are expected to pay the amounts due in the future. When a company purchases goods or services on a credit basis, its bank or cash accounts do not get affected. The balance is allocated to the trade payables account which is reflected in the balance sheet. The purchase account is debited as it does in a normal cash purchase.  Accrued liabilities may also be caused because of accrued expenses, such as pending electricity bills. This is when the business has to record the expense for the period when it was incurred rather than the accounting period in which it was paid. These transactions are usually recorded in the current liabilities section of the balance sheet and the balance is then written off once the company pays for the goods or services purchased. The transaction is recorded on the date the goods or services are received as the company has reaped the benefits at the time of the purchase, thus the transaction must be recorded at the time the goods or services are received. This is done due to the accounting method of accruals which follows the matching concept. When Are the Accrued Liabilities Written Off? Accrued liabilities are only written off once the business pays the accrued balance. It is credited from the bank or cash balance and reduces the balance in the liability’s account.  Types of Accrued Liabilities There are two types of accrued liabilities that a business can incur: Routine Accrued Liabilities These liabilities are incurred due to a company's day-to-day activities such as purchasing raw materials. These are incurred multiple times in a year and are recorded in the trade payables account or other payables account. A few examples would be raw materials bought on credit or wages accrued to employees. Non-routine Accrued Liabilities- Non-routine liabilities occur on very few occasions. These liabilities are related to the non-operating duties of the company. 

Other Important Terms

Fiat On-Ramp

What Is a Fiat On-Ramp? On-ramp refers to an exchange or another type of service where you have the ability to offer fiat money in exchange for cryptocurrency. An on-ramp essentially allows you to convert fiat money into cryptocurrencies. These platforms are typically known as exchanges, where they base the amount for the fiat-crypto transaction on the current market rates. In fact, there are three ways through which you can get cryptocurrencies as well as other blockchain assets. First, you can mine them, and this means that you can offer your computing power to a blockchain network in return for coins or tokens. Another way is to sell goods as well as services and accept cryptocurrencies as a way of compensation for your efforts or products. However, these options might not be available for just about anyone, and this is where the third way, the fiat on-ramp, will allow you to buy cryptocurrency by simply using cash. All you have to do is visit an online exchange or physical crypto ATM, and take your fiat currency and exchange it for an equivalent amount of cryptocurrency. The main reason they are called on-ramps is due to the fact that they provide you with access to the entirety of the cryptocurrency ecosystem.  Then you have cryptocurrency off-ramps, which are the opposite of on-ramps. They allow you to convert your cryptocurrency into fiat currency, although you can also get products or services. In the previous on-ramp scenario, you were a user that needed to get into the cryptocurrency ecosystem, but what if you wanted to get out of it? This is where off-ramps come into the picture. You can trade back into fiat through them, due to the fact that fiat currencies, in a lot of parts of the world, are still the primary means of conducting purchases or payments and so on.


What Is CryptoPunks? CryptoPunks is one of the most recognized NFT collectibles. Created by John Watkinson, Matt Hall, and Andy Milenius back in 2017, this collection is a set of 10,000 24x24 pixel images.  Each image represents a unique punk (alien, robot, ape, etc.) that can be purchased and owned by whoever possesses the asset on the blockchain. These punks are unique and many look like distinct celebrities. The non-fungible token world has seen significant growth over the past few years. This growth has been dominantly driven through the purchase and sale of NFTs on Ethereum which started with CryptoKitties in December 2017 and has since expanded to the millions of tokens that exist on the network today.  CryptoPunks were created with a similar purpose in mind; to show off what is possible with non-fungible tokens on Ethereum via ERC-721, just as CryptoKitties showed what you could do with ERC-20/ERC-233 reproducible tokens. In 2021, CryptoPunks and NFT market as a whole experienced a massive surge in their values. Several NFTs were sold for $1 million each. The total transaction volume in the first six months of 2021 was $2.5 billion. CryptoPunks remains one of the earliest NFTs – primarily a collection of pixelated avatars. It is currently the most sought-after NFT collection, with several NFTs being sold for millions of dollars.  Believe it or not, Larva Labs (the creator of CryptoPunks) released the collection for free – as an experiment. The two-person team behind CryptoPunks had no idea that this would go on to become the leading name in the NFT space. Back then, ERC-721, which is now a standard for NFTs, wasn’t even created. When Larva Labs released CryptoPunks, 9,000 of them were snatched by Ethereum wallet owners while others were held onto by Larva Labs.

Black Swan Event

What Is A Black Swan Event? A black swan is an event that is characterized by its extreme rarity and severe impact. The term was first coined by Nassim Nicholas Taleb, a writer who is also a finance professor and former Wall Street trader.  In his 2007 book, Taleb talks about the idea of a black swan event: an event that is impossible to predict but has catastrophic consequences. According to him, these events are extremely rare and unpredictable, which is why it is important for people to always expect their possibilities and plan accordingly. A black swan, according to Taleb, is an event that is so uncommon that even the probability of its occurrence is unknown. There are three major components of the incident: When it does happen, it has disastrous consequences. It can be explained with hindsight only.  Observers are keen to explain it after its occurrence and speculate as to how it could have been predicted before it happened. The Black Swan Theory, also known as the Theory of Black Swan Events, can be linked directly to a Latin phrase used by the Roman poet Juvenal in the 2nd century, when he characterized something as a "black swan event" as “in terris nigroque simillima cygno rara avis” This Latin phrase means "an unusual bird in the lands that looks a lot like a black swan." It was formerly assumed that black swans did not exist when this proverb was coined. A black swan occurrence in the financial (& cryptocurrency) markets is very unfavorable, resulting in broad devastation and famously unpredictable consequences. The Global Financial Crisis of 2008, which was caused by the unexpected, catastrophic fall of what had formerly been a flourishing property market, is the most famous example of a black swan occurrence in the world of finance. Lenders in the United States had drastically loosened their requirements for eligibility for mortgages, mostly as a consequence of the federal government's pressure. People with bad or no credit were accepted for mortgages on properties that were, to put it bluntly, well above their financial means. Subprime mortgages soon grew into a large, bloated bubble that was about to explode. Lending behemoths, like Lehman Brothers, began to crumble and fail as payment dates passed and mortgages began to default in droves. The US government was compelled to authorize the Troubled Asset Relief Program (TARP) — a roughly $1 trillion program aimed at bailing out big banks and restoring liquidity in the economy. To avoid a repeat of the 2008 crisis, governments throughout the globe tightened laws for financial institutions, making it more difficult for them to take on certain types of (and amounts of) debt. At present, the world is experiencing and recovering from one of the most spectacular examples of a black swan occurrence. The new coronavirus, also known as COVID-19, satisfies all of Taleb's requirements for this event. The pandemic struck without warning, and it rapidly became clear that no country was equipped to cope with it. Every day, we learned (still learning) a bit more about the worldwide pandemic's devastating impacts, which include record-breaking unemployment rates, stock market crashes, ever-increasing death tolls, and so on. No one knows when a black swan event occurs, just as many people can’t predict seeing a black swan amongst a flock of white ones.

Byzantine Generals’ Problem

What Is the Byzantine Generals' Problem? The Byzantine Generals' Problem is a thought experiment that deals with a key question of computer science: is it possible to form a consensus in a computer network composed of independent, geographically distributed nodes? The problem was proposed in 1982 by researchers from the SRI International Research Institute.  It goes as follows: there are a number of Byzantine generals besieging a city. They can only communicate via sending messengers to each other. The generals must agree on a common plan of action: whether to attack the city or retreat. However, some of the generals are traitorous and actively working against the forming of a consensus; their number and identities are unknown. The question posed by the problem is what decision-making algorithm the generals should use to devise a common plan — regardless of the traitors’ interference — and whether such an algorithm exists at all. According to the researchers’ own analysis, such a system is indeed feasible, but the number of loyal generals must strictly exceed two-thirds. For example, in a situation with three generals, one of which is traitorous, the loyal ones can never guarantee that they will be able to reach a consensus. This problem is highly relevant for cryptocurrencies as they are, in essence, distributed computer systems: they are composed of transaction-processing nodes that are independent of each other and any central authority and can only communicate remotely. They are the “generals” that need to reach a consensus about which transactions have taken place and when. Nodes have the potential to supply faulty data about transactions either by choice or by accident, and their information must be sorted out. Bitcoin (BTC) and other cryptocurrencies solve this problem via technical solutions such as the proof-of-work and proof-of-stake algorithms. See Byzantine Fault Tolerance (BFT).


What Is Change? Bitcoin (BTC) and many other cryptocurrencies are based on the so-called unspent transaction outputs (UTXO) model.  In the UTXO model, transactions are made up of inputs and outputs: when a user wants to send coins to someone, they feed inputs to the network. The latter, after processing the transaction, produces outputs that can be later used as inputs for new transactions. Perhaps counterintuitively, the balance of a Bitcoin address is not actually a certain number of coins that are stored on it, but rather a collection of yet-unspent outputs from previous transactions. When you send Bitcoin, you can only send them in a whole output, and the rest are sent back as change. As an example: user A has a Bitcoin address with a single unspent output of 0.5 BTC and wants to send 0.3 BTC to user B. They cannot split their UTXO of 0.5 coins; instead, they have to send the full amount to the network as the sole input of the new transaction. The network then destroys that input and creates three new outputs that add up to the same amount: 0.3 BTC to be sent to user B, a certain small fee to be sent to the miner who helps process the transaction and 0.2 BTC, minus the miner fee, to be sent back to user A. In this example, the last output of ~0.2 BTC is the change that user A receives as a new UTXO which can be later used as an input to initiate a new transaction.

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