Degenesis: How to source memes to trade, perform DD, and size your bets
The parallels between shitcoin sniping and pre-seed VC investing (Part 3/3)
Table of Contents
Introduction
In part 1 of my series, we covered what meme coin sniping is, while in part 2 we got to the starting line to trade them. After a month-long delay, the meme coin market has settled down a bit, but I still wanted to cover some self-defensive intuition when it comes to meme coin trading and sniping. Note that the content here is relevant only as of June 2024. The landscape and meta might be significantly different by the time you are reading this.
In the last part of this series, I will go over an example basic trading strategy, a basic due diligence check list, and some additional tools. Specifically, this article will discuss:
How to look for opportunities by identifying your sweet spot and using filters
How to perform due diligence on holder distribution, burned liquidity, mint and freeze authorities, top trader leaderboard, starting liquidity, graph health, and social media
Some additional tools and platforms that can help you—SolSniffer, Solscan, sniper bots, and transfer trackers
How to size your bets based on your available capital and the Kelly criterion
A few common tactics for executing trades—dollar-cost averaging, closing halves, and opening reversal positions
This is also where we will cover some additional similarities between pre-seed VC investing and shitcoin sniping. We will see that:
In meme sourcing, Pump.fun is like the Y-Combinator of meme coins
Memes have their own “market size” similar to different market verticals
It’s a good idea to reserve a portion of capital for follow-on or reversal investments
One key difference from pre-seed VC investing is that cycles play out in a matter of hours to days, meaning that you can recycle your meme coin capital quickly.
Once again, meme coin trading is very risky. Nothing I write is financial advice, nor do I advocate for participation in meme trading. There are plenty of interesting things in web3 beyond shitcoins. Let’s wrap this up so we can talk about other things in future articles.
Meme Coin Life Cycle and Where to Play
The first step to sniping is to determine how early you want to play. As mentioned in part 1, the definition of “sniping” has become somewhat loose, and you can choose to trade at various points in a meme coin’s typical life cycle. Below is an example of a successful meme coin life cycle.
Example life cycle of a typical short-term successful meme coin launched from Pump.fun. Not to scale, ignores and smooths out spot volatility, for conceptual visualization only:
Here’s a textbook example of a recent token that hit several million $ FDV at peak from Dexscreener (excluding the pre-launch part):
It would take too long to dive into why the curve often looks this way, but for most meme traders (non-algorithmic), there are five good entry points throughout the life cycle.
Two entry points pre-launch:
At token creation
After a token crashes upon achieveing king of the hill on Pump.fun
Three entry points upon DEX listing:
At DEX listing
At reversal
At breakout
In part 2, we only covered how to start trading from DEX listing onwards, so we will only discuss how to uncover newly listed meme coins with potential, how to perform due diligence, and how to size your bets. For the sake of brevity and because Pump.fun itself is a whole other ball game, we will only briefly mention the platform and not dive into pre-launch (before a token hits DEX) meme trading strategies and tactics in this article.
Meme Sourcing
The common way for meme sourcing is through the use of filters on platforms like Dexscreener. To snipe the newest memes being listed on DEX, you need only sort Dexscreener by new tokens for the ecosystem you are playing in, upon which you can then immediately dive into due diligence.
Screenshot for locating filters on Dexscreener:
To source meme coins that may trend towards reversals or breakouts, you would look at more specific filters. An example set of filters to look for breakouts may be the following on Dexscreener:
Liquidity: Min $20K
Pair age: ≤ 3 hours
24H txns: 2000+
24H buys: 1000+
24H volume: $300K+
5m txns: 50+
5m buys: 25+
Here, you are looking for memes that have decent liquidity, volume, transaction count, buy pressure, and are still relatively young. You would want to play around with the filter ranges to observe trends for the day and where you might want to play. The filters provided above are an example and may not be useful for isolating possible breakouts in the meta when you are reading this.
To look for reversal entry points, you would set the filter to look for high volume but high sell pressure to identify tokens that have already crashed. You can then perform due diligence on them and see which ones may have reversal potential. Overall, memes have a life cycle on the order of hours to days. Most breakouts that hit a $1 million FDV will happen within hours of DEX listing, while the big home runs that go up to a few million FDV or even beyond $10 million FDV happen within a few days, if not within the first 24 hours.
Due Diligence Checklist
Once you spot some tokens that pique your interest, it’s time to do some due diligence (DD). Unfortunately, since late March, scammers have proliferated exponentially and become increasingly sophisticated. This is part of the reason meme coin activity died down in June, in addition to macroeconomic headwinds. Even still, here’s a list of basics to look at. I will explain what each of these means:
Whether the token came from Pump.fun
Whether liquidity has been burned, and if mint and freeze authority are disabled
Health of the holder distribution
Top trader PnL health
Trader red flag votes
Social media links and presence
Whether the curve looks suspicious
The below example illustrates a meme coin that passes basic DD (which does not imply the token will do well, merely that it is less likely to be a scam). I have highlighted the parts in the UI that correspond to the checklist:
Pump Combinator?
Pump.fun is a launchpad for meme coins that went viral in the beginning of March, 2024. This platform allows meme creators to seek investors for their coins before they get listed on DEX. The listing process (called the bonding curve) is automatic. Once enough coins have been bought with Solana, the smart contract automatically lists the coin on DEX and seeds it with the invested Solana as liquidity to facilitate trading. The process is rife with flaws and exploits, but it is still more transparent than the typical process of meme coin listing, where creators simply send tokens to investor wallets (real or fake) and directly register tokens onto DEX whenever they feel ready.
In general, tokens coming to DEX from Pump.fun are slightly safer than those that are not due to the platform’s “fair launch” process, which shows who is buying in pre-launch, automatically burns the seeded liquidity that supports the token, and typically has a slightly larger pool of participants by the time the token hits DEX. You can identify tokens from Pump.fun by the presence of the word “pump” at the end of a token’s address. Since June, the addresses of all Pump.fun launched tokens have been appended with “pump,” making them easy to identify. Many of the massive market cap meme coins you have seen since March have come from Pump.fun, for example michi, DADDY TATE, MOTHER IGGY, ZACK MORRIS, Shark Cat, BILLY, TEH EPIK DUCK, Hawk Tuah etc just to name a few that have persisted.
Example coin address with the pump suffix:
Make no mistake, Pump.fun has its serious share of scams—many of which are automated or extremely sophisticated—but in the wild west that is shitcoin sniping, we find in it one more parallel to VC investing. Pump.fun is to meme coins what Y-Combinator is to startups, in that they both have a great relative track record of launching successful projects, and having the badge can often attract a premium.
Burned Liquidity and Token Authorities
This leads us to the second item on the DD list. You must ensure that the liquidity pool tokens, which the token creator received when they seeded the liquidity pool with SOL, ETH, etc., have been burned. This ensures that there is no way for the creator to remove liquidity from the market directly and rug pull you. I won’t dive into how automated market making (AMM) works here, but here’s a good primer. You can check for burned liquidity on Dexscreener by looking for a locked symbol beside the liquidity information of a token. The absence of a locked symbol would mean the liquidity is not locked or burned.
Screenshot on checking burned liquidity on Dexscreener:
You should then check to ensure that the token creator does not have the authority to make additional tokens or the ability to freeze other people’s token accounts from trading the token. These are referred to as mint and freeze authorities. If the creator can create more of the same meme coin, they can easily manipulate the market and dilute its value. The dangers of freeze authority are also significant; with that authority, they can prevent other people from transferring the token once it gets to a sufficiently high price.
Unfortunately, there is no direct way to check these authorities through Dexscreener. One way is to use a tool like SolSniffer which can examine these based on the token address. Alternatively, you can use a sniper bot platform like Photon which automatically performs these checks for you when viewing a token’s information.
Here’s an example screenshot from SolSniffer to check if mint and freeze authorities are disabled:
Here’s another example screenshot from Photon which checks quite a few things mentioned in the DD list:
Holder Distribution
When it comes to token distribution, you want to ensure the top holders will not be able to have an outsized impact on the token price. It’s typically a red flag to see any holder with above 5% of the token supply, and it’s also very dangerous to have the top 10 holders hold beyond 30% of a young token. Additionally, the more holders there are for the token, the more likely there is real buy-in from the public into the meme. It is important to note that Dexscreener’s holders list does not automatically identify the DEX pool—i.e., it is quite normal for Raydium (the DEX) to hold a significant share through its AMM, and this should not alarm you. To check this, you should click on the token address listed on Dexscreener, which will bring you to Solscan. From there, you can check the most up-to-date holder distribution and exclude Raydium’s holdings from your evaluation of the distribution health.
Here’s an example screenshot of how to check holder distribution on Solscan, the DEX pool (Raydium) is highlighted, its account is listed as “Raydium Authority”:
It is worth noting that scammers have gotten very sophisticated in masking distribution health. In addition to a quick check like this, it is also worth using SolSniffer to see if there are tokens stored in hidden wallets. For example, a token creator may actually have kept 30% for themselves or their team but spread this over hundreds of wallets to mask their holdings. After the token becomes sufficiently valuable, they would dump all their spread-out holdings at once. TTF Bot can also be used to check whether the token creator has transferred tokens to other wallets in an attempt to hide holdings.
If the token is a Pump.fun token, they have an inbuilt utility that can help you map wallet transfers. You can access it by copying the token address and appending it to the Pump.fun URL (e.g., pump.fun/[paste token address here without these brackets]), then clicking the bubble map.
Example screenshot of how to access the bubble map utility on Pump.fun:
Example screenshot of a bubble map showing transfers between wallets, although in this case, the transfers are from Raydium’s token pool which only means the top holders bought their tokens on DEX:
Top Trader PnL Health
A natural thing to check after holder distribution is the top trader PnL (Profit and Loss) health. The principle here is that if a token has really blown up, top trader PnLs should roughly correspond in order of magnitude to the growth of the token. That is, if a token has supposedly grown by 10X since listing, then there should be top traders who have made close to 10X from their investments. The same applies for 100X, 1000X, etc. Whenever you see a top trader with an empty “bought” field but with PnL, it typically means they bought the token pre-launch, had airdrops, or was its creator.
Here’s an example screenshot of a healthy top trader PnL check. We see that several traders have made ~10X on their investments when the token has grown by approximately 15X since listing, and various other traders also seem to have made a healthy multiple of between 3-5X:
If a token has supposedly “blown up” yet no one has made money, then you are probably the money they are trying to make. We will see a scam example at the end of this section.
Other Checks
Dexscreener’s sentiment votes can be useful as a quick check. The ratio between red flag votes and rocket votes should be very low for a non-scam token, yet not excessively low depending on how long the token has been listed. For example, if a token has only been listed for 5 minutes yet there are 1000 rocket votes vs. 5 red flag votes, then this is highly suspicious and might have been vote-manipulated by bots. The presence of social media can also help uncover additional information about the token but does not remotely guarantee that the token is not a scam.
You may occasionally come across tokens that are listed as “Community Takeover” (CTO for short). This typically means that the original creator of the token has left the project (often by rugging or scamming the people who bought in), but the community has decided to take over running and marketing the token. Back in March and April, finding good CTO projects was an excellent way of finding high potential reversals, but since May, many staged and fake CTOs have emerged, and this is no longer a good indicator for possible reversal.
Example screenshot of sentiment check and social media links of a CTO token on Dexscreener:
Lastly, if the curve looks too good to be true, then it probably is. Sophisticated scammers often use an army of maker bots to facilitate their trades these days, but the way the bots are designed tends to produce unrealistic curves that are either too smooth or flat. If you see this, then pay attention to the other DD items, as it could be very likely that it is a scam.
Meme Market Size
The last thing to consider before placing a bet is the meme “market size”. Very few memes ever go beyond $2 or $3 million FDV (Fully Diluted Valuation), and the more obscure the meme is, the less likely this is to happen. This is not to say that obscure memes cannot make it big, but it is less likely. Meme traders, by necessity and environmental pressure, are more “up to date” and plugged into the meme meta. This means that obscure memes can trend up early from serious meme traders thinking they will blow up. Once it hits several hundred K or $1 million FDV, the overall concept of the meme must be at least somewhat familiar or relatable to less serious traders and the general public for it to go any higher. A recent example of this was the beef between Ansem (arguably the top Solana influencer) and the controversial Andrew Tate. The resulting coins—Daddy Ansem and Daddy Tate—have completely different magnitudes of success at peak, partially because Andrew Tate is known beyond crypto circles (for better or worse).
This brings us to another parallel with VC investing: memes have their respective market sizes, much like different verticals in regular investing. The more widely recognizable the meme is, the larger the potential market. That said, this does not always hold true; there are obscure, niche, or completely new concepts that have hit a home run at some point. Some examples from the past 3 months include findmeonsol, Slerf, and THOG.
The reason I put this as the last thing on the list is because there is no real way to size this, and it all comes down to intuition, how closely you follow meme culture meta/lore/evolution, and what news sources you use. It’s time-consuming and distracting to optimize your news feeds and information sources specifically for this (as mentioned in part 1) unless you are doing this full time—which I really do not recommend.
Example Scam
Here is an example of a scam meme coin that does not pass the DD checklist we went through above. Notice that this token was directly listed on DEX (not launched from Pump.fun), its liquidity is not locked nor burned, it has a poor red flag to rocket ratio, its curve is very flat with little to no volatility, and that despite its supposed 4 million % growth, no trader has made more than 3-4X.
Unsurprisingly, this is what happened to this token after a bit more time. In this instance because the initial liquidity was neither locked nor burned, the scammer simply removed the liquidity pool and sold whatever holdings they had resulting in a 99.9% crash within seconds:
Here comes the hard part—practice going through this entire DD list within 1 minute of identifying a potentially good bet! If you really identified a breakout, every minute could make or break your PnL. Now that we’ve covered DD basics, let’s examine how we can size our bets.
Sizing Your Bets
Armed with the basic DD list, you should now have some intuition on identifying scams. This not only helps with bet picking but also gives you a clearer picture of the market state—as many tokens that seemingly have succeeded may, in fact, be scams. It is crucial to have a decent picture of the market state whenever you trade, as this informs your risks, expected value calculations, and how you size your bets.
The Kelly Criterion
We use the Kelly criterion for bet sizing; those who studied economics, finance, or probability are likely already familiar with it. In probability theory, the Kelly criterion is a formula to maximize your wealth over time if the expected returns are known. Counterintuitively, purely pursuing expected value does not achieve this. For those interested in the math, here’s a neat YouTube video that walks through the derivation of the Kelly criterion. In this section, we will walk through how to apply this formula.
There are two versions of the Kelly criterion, one for investing and one for gambling. In the case of meme coin trading, the gambling formula would be more accurate because, unlike traditional investing, you are likely to lose your entire investment when a meme coin fails rather than only lose partial value.
Here is the gambling version of the Kelly criterion formula reproduced from Wikipedia:
where:
𝑓∗ is the fraction of the current bankroll (the total amount of money you are dedicating to meme coin trading in this case) to wager.
𝑝 is the probability of a win.
𝑞 is the probability of a loss, where 𝑞=1−𝑝
𝑏 is the proportion of the bet gained with a win. E.g., if betting $10 on a 2-to-1 odds bet (upon win you are returned $30, winning you $20), then 𝑏=$20/$10=2.0
Gathering Data
You would estimate 𝑝 (probability of a win) and 𝑏 (proportion of bet gained with a win) using the filters and DD list we went through earlier. For example, here’s a process you can use if you wanted to size your bets for sniping new DEX listings:
Filter by new tokens created in the last 24 hours and note down how many were created (probably between ~1500-3000).
Filter for tokens you consider a success (whether this is 5X, 10X, 100X, etc., based on your own aims).
Perform DD to exclude scams from your consideration.
Run steps 1-3 six hours apart each day for 2 to 3 days.
Note down the number of non-scam successful meme coins observed.
Note down the average growth at peak of the non-scam successes observed.
Approximate 𝑝, which would be the number of non-scam successes observed in each 24-hour period divided by the total number of new tokens (minus the number of scams) in each 24-hour period.
Approximate 𝑏, which would be the average growth of the non-scam successes observed divided by the growth you might miss out on due to entry delay minus 1.
To put some dummy numbers, after some sampling, you may find that the market state when you start trading has in a given 24-hour period:
On average, 1600 new token listings on Solana
~60% of new token listings seem to be scams which you manage to filter out through DD
Maybe 20 non-scam tokens make it above 1000%, averaging at 15000% at peak
You observe that you are typically unable to buy in before a token has already reached 150% growth due to your DD speed or other execution delays
In this case, your 𝑝 would be:
𝑝 = 20 / ((1 - 0.6) * 1600) = 0.03125 meaning ~3% success rate
However, the number of scams is an estimate, and it is nearly impossible to catch all of them (especially very sophisticated ones) even with our DD list. It would be best to add a margin to your filtered scam estimate by decreasing it from 60% to maybe 50% and assume that some scams will slip through and affect you. An example adjusted 𝑝 would be:
𝑝 = 20 / ((1 - 0.5) * 1600) = 0.025 meaning a 2.5% success rate
Your 𝑏, on the other hand would be:
𝑏 = (average expected growth of success / entry delay growth) - 1 = (15000% / 150%)-1 = 99
Yet, similar to the DD risk, there’s also an execution risk when it comes to odds. Specifically, you may not always exit at the peak due to fear, uncertainty, and doubt (FUD), mistakes, or other factors. As such, you likely need to discount your average expected growth of success to approximate an average expected growth at exit. Based on your own trial and error, you might observe that you capture no more than 2/3 of the max value on average. In this case, your adjusted 𝑏 would be:
𝑏 = (average expected growth at exit / entry delay growth) - 1 = (2 / 3 * 15000% / 150%)-1 = 65.7
We can now calculate our bet size for each new token snipe:
𝑓∗ = 𝑝 - 𝑞 / 𝑏 = 0.025 - (1 - 0.025) / 65.7 = 0.01015
What this means is that based on the hypothetical market state above, for each new token, you should not deploy more than 1% of your capital dedicated to meme coin trading. You can run through similar exercises for reversal and breakout trading by using different filters to sample data. The caveat to this is that depending on the size of your bankroll, you may not be able to deploy 1% on a new token due to FDV limitations.
Caveats
Let us suppose you are an apex degen, and you somehow have a $100K bankroll to snipe meme coins. 1% of your bankroll would mean $1K bets, but many new tokens start out with a market cap of $10K or less. Putting in $1K would net you almost (but not quite due to AMM) 10% of the distribution. Such an action would disincentivize others from buying into the token because you have just tanked the holder distribution health of the meme. So in practice, for bet sizing, you are limited to whichever one is lower in dollar value between your fraction of capital to bet vs. the capital needed to hold 5% of the token’s market cap during entry.
If somehow your Kelly criterion fraction comes out negative, it means it is not profitable to participate. You would either have to improve your DD process to increase the success rate or lower your entry delay to improve your odds.
With the above hypothetical market state, you can see that at constant 65.7:1 odds, you should not participate at all if the success rate is below 1.5%:
An example 3D curve representing the optimal Kelly bet size (vertical axis) as a function of success rate and odds reproduced from Wikipedia:
Another caveat to consider is your effective bankroll. If you are deploying your meme coin bankroll across several different entry points (pre-launch, DEX listing, reversal), you may need to consider them as separate bankrolls during your deployment. Specifically, you might want to keep parts of your overall capital for follow-on bets.
Follow-on Bets
When it comes to dividing up your capital for different strategies, we see another similarity to VC pre-seed investing: you may want to reserve a portion of your capital for follow-on investments into good projects that you have already invested in. This can be especially true for reversal and breakout trading entry points. There are two typical situations where follow-on investments can be a good idea:
When a reversal position you opened starts turning into a breakout with high certainty
When an investment experiences a local minima or temporary drop
The same bet sizing strategy could apply, only the success rate and odds are modified for follow-ons. You would want to evaluate ahead of time whether you want to consider follow-ons for tokens once they have made it to 2 or 3X growth or only for the ones that have managed to hit 10X, etc. For example, if you find that in the current market state, around 30% of tokens that achieve 10-11X growth can make it to 100X eventually, then after factoring in entry delays, your Kelly criterion fraction might come out to be about 18%. In this case, the 18% can likely take up a higher dollar value because, by this time, the market cap of the token has likely already grown quite big and a larger bet size wouldn’t significantly impact distribution health. With this in mind, you might decide to reserve 30-50% of your total capital specifically for follow-on investments to lower your risks.
Tactical Execution
Now that we have covered the DD list and how to size bets, here is some tactical execution advice that combines two different entry points (Listing and Reversal):
Deploy bets on new tokens that have been listed on DEX.
Close half your position when the token 2Xs since your entry.
Dollar-cost average (DCA) top-up if the token crashes but you see strong possibilities of a reversal.
Opening Positions
As we saw from our odds calculations earlier, entry delay can have a significant impact. The way to minimize entry delay is to be able to perform DD quickly (whether manually or if you find a way to automate the process) and possibly use a sniper bot such as Photon, which we mentioned earlier, to reduce transaction delays and failure rates. If you are opening micropositions using sniper bots, be aware that the transaction fees (usually 1% and 0.01 SOL minimum) and network bribery fees can have a drastic impact on your odds and multiples.
Another tactical advice is not to get attached to memes and do not pick sides when opening positions. There are times when you see concepts that have great potential, and sometimes they may represent opposing viewpoints or camps (e.g., Trump vs. Biden, Tate vs. Ansem). When these happen, it will typically work to your benefit to bet on both at the same time, just exiting at different points depending on how it plays out.
Recycling Costs
A common exit strategy is to recycle costs by closing half your position once it has doubled since your entry. You can then leave the remaining until it achieves breakout. Given how fast memes go through their lifecycle, you can significantly extend your bankroll if you can consistently recycle costs.
Cost recycling requires discipline and consistency; otherwise, it will just end up messing up your strategy and odds. Upon taking back your cost basis, you need to steel yourself not to give in to FOMO if momentum continues or accelerates. Topping up when the token is trending up after you have recycled your cost just increases your average entry price or dilutes your holdings. Conversely, if you decide to practice recycling but do not do it consistently, you will have a tougher time dealing with FUD and FOMO. Naturally, you would want to reevaluate your bet sizes and take recycling into consideration.
DCA Reversal Top-ups
I recommend adding tokens you have a position in to a watchlist on Dexscreener. After you have recycled costs, move on to the next token, but you can quickly check your previous investments. There are often situations where, after a quick initial rise, the token price crashes to a local minimum below your initial entry price. Due to CTO, social media activity, or some other conviction, you think it will reverse in a few hours. This is when you might consider putting in a reversal position. I typically do this in batch format, examining multiple crashed tokens that I followed a few hours prior and evaluating whether any of them have reversal potential for a follow-up bet.
Lastly, a reminder on something quite obvious: when topping up your position during a temporary slump, dollar-cost average it out. This also ensures you can stop the remainder of your top-ups if the outlook on the token or momentum drastically changes.
Conclusion
Once again, nothing I write is financial advice, nor do I advocate meme trading. The recent overall market slump means that meme coin activity has died down a bit in June, but 100-1000X returns still happen every few days. In fact, the token we used as an example in this article—Bobby—achieved 100X at peak (since DEX listing) over the course of 19 hours as I wrote this (too bad I was too busy to bet).
I think there will still be some upward trends in crypto leading up to the US election and into early 2025. However, the meme landscape has seen a drastic increase in the number of sophisticated scammers and scam tokens. If you want to try this out, definitely be aware and skeptical. For those who made it this far, thank you for reading my very first series of articles.
For my next article, I will write about AI and agentic markets. To get notified, please subscribe to my Substack and follow me on Twitter.
Thank you to Kevin Zhang and Sheng Ho for helping review!
Glossary of Terms
Token: Interchangeable term with coin, cryptocurrency, cryptoasset, etc.
Blockchain network: A distributed ledger network. Different networks have different ecosystems and utilities. Some of the biggest ones right now are the BTC, ETH, and Solana networks. I won’t be going into the differences between L1s vs L2s, or EVMs, SVMs, etc.
CA: Coin address, an immutable string that represents the actual token itself on the blockchain network. The true representation of a coin’s identity.
Web3: Web 3.0, a catch-all term for a vision of the next iteration of the internet that can be trustless, permissionless, and decentralized.
Ecosystem: The platforms, exchanges, decentralized apps, systems, tokens, and community around a given blockchain network.
DeFi: Decentralized finance, financial systems and technologies built on top of blockchains. Often, any vaguely finance-related activity in the world of web3 falls under this umbrella.
CEX: Centralized exchange, businesses that help people trade cryptoassets, such as Coinbase, Binance, and FTX. All traditional finance businesses are “centralized”.
DEX: Decentralized exchange, a platform that facilitates peer-to-peer (P2P) transactions of crypto assets on a blockchain.
Swap: Used interchangeably with the verb “exchange”. Swapping or exchanging one token for another.
Pair: Refers to a trading pair listing of two tokens, typically the newly listed token and the native token of the blockchain. Basically, a “listing” on an exchange.
Custodial: Someone else manages your actual cryptocurrencies for you. If you don’t know anything about having a private key for your cryptoassets, then you’ve likely been using custodial crypto accounts.
Wallet: A non-custodial cryptocurrency wallet where you can manage and use your cryptocurrencies directly.
Dev: Short for developer, the person or team that actually created a cryptoasset.
ICO: Initial coin offering, the first time the cryptocurrency is offered for sale to someone besides the developer. The cryptocurrency may or may not be freely available to trade.
IDO: Initial DEX offering, the first time a cryptocurrency gets listed on a DEX and is freely available to trade by holders and anyone who wishes to swap it.
Gas fee/network fee: The cost to perform a cryptocurrency transaction as dictated by the blockchain network that the transaction happens on.
PnL: Profit and loss.
Rug: Short for rug pull, a generic term for an exit scam where the developer for a coin or web3 project disappears and cashes out through several different methods like liquidity pulls, fake projects, pump and dump, or simply disappearing with investor money.
Jeet: Someone who sells no matter what, sells for barely any profit, or panic sells.
Whales: Individuals or entities that hold a lot of cryptocurrency.
Makers: People who buy or sell a token, not to be confused with market makers in a traditional finance sense. DEXes use automated market making algorithms rather than order books.
Apes: Degenerates who trade memes, have high risk tolerance, and usually negative PnL.
Blue chip coins: The largest and most established cryptocurrencies that have large market caps, volume, and often history.
Stablecoins: Cryptocurrencies that are pegged to fiat currencies either by collateral, algorithms, or both. Theoretically the most stable and least volatile cryptocurrencies available. Most of the time, they are pegged to the USD (e.g., USDT, USDC, DAI).
Altcoins: Any cryptocurrency that is not BTC. There is overlap with blue chips and meme coins, and sometimes it simply refers to any coin that is not a blue chip token.
Meme coins/Shitcoins: Tokens that have inherently zero utility, the most volatile of any cryptocurrency asset class.
Liquidity pool (LP): On the most basic level, community/dev-funded blue chip tokens or stablecoins that actually back an asset and give it tradable value. In actuality, much more nuanced.
Burned: When certain tokens are permanently deleted and irretrievable.
Burned LP: Tokens that are permanently locked into the liquidity pool and not retrievable by whoever supplied that liquidity in the first place.