TGE Liquidity Playbook - Market Making a New Token Launch
TL;DR
- What: A comprehensive guide to the dynamics of a Token Generation Event (TGE) — how new tokens launch, who the participants are, and how each thinks about price
- Who it's for: Market makers, exchange operators, token creators, and sophisticated investors participating in Day 1 of a new listing
- Three critical questions for MMs: (1) How does trading open? (2) What reference price do I use? (3) How fast can airdrop recipients sell?
- Core challenge: No trading history exists — every participant is operating with incomplete information
- Key takeaway: Each participant (exchange, MM, project, investor) has different incentives and different information edges. Understanding all of them is what separates good outcomes from bad ones.
Table of Contents
- What Is a TGE?
- The Participants: Who Is Involved and What Do They Want?
- Why Market Makers Are Essential at a TGE
- The MM-Exchange Relationship at a TGE
- How Each Participant Should Think About Price
- Market Scenarios (S1-S4)
- Question 1: Opening Mechanism
- Question 2: Reference Price
- Question 3: Claim Friction
- Putting It Together: The Opening Playbook
- Token Economics and Supply Dynamics
- Historical Patterns: What Usually Happens
- Risk Considerations
- Key Terminology
1. What Is a TGE?
A Token Generation Event (TGE) is the moment a new crypto token comes into existence and becomes tradeable. It's the crypto equivalent of an IPO — except it typically happens in hours instead of months, involves an airdrop instead of an underwriter, and has far less regulatory structure.
A TGE typically combines three events happening simultaneously or near-simultaneously:
- Token creation — the token smart contract is deployed on-chain
- Airdrop distribution — existing community members or protocol users can claim free tokens as a reward for early participation
- Exchange listing — the token becomes available to trade on one or more spot markets
Timeline of a Typical TGE:
T-weeks Project announces token, publishes tokenomics
T-days Listing date announced, airdrop eligibility revealed
T-hours Premarket trading may begin (OTC, prediction markets, thin venues)
T+0 Token goes live on exchange. Trading begins.
T+0-30m Airdrop claim opens. Recipients start selling.
T+1h First wave of selling subsides.
T+4-24h Price begins to stabilize. Flow becomes two-sided.
T+days Secondary market matures, other exchanges list, derivatives launch.Why TGEs Are Unique
Unlike a stock IPO where an investment bank prices shares, builds a book of institutional orders, and stabilizes the opening price — a TGE has:
- No underwriter — nobody guarantees a price or absorbs excess supply
- No lock-up enforcement — airdrop recipients can often sell immediately (unlike IPO investors who face 90-180 day lock-ups)
- No stabilization mechanism — no "greenshoe option" or stabilization agent
- Asymmetric supply — a large batch of tokens (the airdrop) hits the market at once, creating one-sided sell pressure
- 24/7 markets — no closing bell, no overnight gap to absorb news
This is why TGEs need market makers — someone has to absorb that sell pressure and provide two-sided liquidity, or the market doesn't function.
2. The Participants: Who Is Involved and What Do They Want?
A TGE involves multiple participants with different incentives, different information, and different time horizons. Understanding each one is critical.
The Token Creator (Project / Protocol)
The entity that created the token and is launching it.
| Aspect | Detail |
|---|---|
| Primary goal | Successful launch — liquid market, price discovery, positive narrative |
| Secondary goal | Price stability (not necessarily high price — volatility is worse than a lower stable price) |
| What they control | Tokenomics, airdrop design, claim timing, exchange partnerships, MM relationships |
| What they fear | Token dumps to zero on Day 1, no liquidity, negative community sentiment |
| Information edge | Knows airdrop size, vesting schedules, insider allocations, and which exchanges will list |
The project typically negotiates with market makers before the TGE to ensure Day 1 liquidity exists. They may provide tokens to the MM as "inventory" (called a token loan or market making allocation) so the MM has something to sell without buying first. In return, the MM commits to quoting the token with certain spread and depth requirements.
The Exchange (Backpack)
The venue where the token will trade.
| Aspect | Detail |
|---|---|
| Primary goal | Attract volume and users — a successful TGE listing drives signups and trading activity |
| Secondary goal | Orderly market — no crashes, no manipulation allegations, no "scam" narratives |
| What they control | Listing timing, trading rules, opening mechanism (auction vs. direct), fee structure for MMs |
| What they fear | Illiquid market embarrasses the exchange, manipulation, technical failures under load |
| Information edge | Sees all order flow in real-time, knows which MMs are committed, can monitor for manipulation |
The exchange coordinates with both the project and MMs. They decide the opening mechanism, set any trading restrictions (e.g., price bands, order size limits), and may provide MMs with special fee tiers or API access for the listing.
The Market Maker (MM / LP)
The firm providing continuous two-sided liquidity.
| Aspect | Detail |
|---|---|
| Primary goal | Capture spread while managing inventory risk |
| Secondary goal | Maintain relationship with exchange and project for future deal flow |
| What they control | Spread width, quote size, skew, when to tighten/widen |
| What they fear | Accumulating massive inventory that drops in value, adverse selection from informed sellers |
| Information edge | Sees real-time order flow, has historical data from previous TGEs, often trades on multiple venues |
MMs are the "shock absorbers" of the TGE. They buy when others are selling (absorbing airdrop supply) and sell when others are buying (capturing FOMO demand). Their profit comes from the spread, but their risk comes from holding inventory in a token that may be dropping in value.
The Airdrop Recipient
Community members who earned free tokens through early protocol usage.
| Aspect | Detail |
|---|---|
| Primary goal | Maximize value extracted from free tokens |
| Secondary goal | Some will hold long-term (believers), most want to sell some or all |
| What they control | When to claim, when to sell, how much to sell |
| What they fear | Selling too early (price moons after they sell) or too late (price dumps to near zero) |
| Information edge | Knows their own allocation size, may have community intelligence on total airdrop size |
Airdrop recipients are the primary source of sell pressure at a TGE. Their behavior is driven by the "free money" effect — they received tokens for free, so any price above zero is profit. This creates a natural floor of sell pressure that doesn't exist in a normal market.
The Sophisticated Investor / Trader
Funds, desks, and experienced traders who are buying the token on Day 1 as a speculative position.
| Aspect | Detail |
|---|---|
| Primary goal | Buy at a good price, profit from price appreciation |
| Secondary goal | Position sizing — get meaningful exposure without moving the market |
| What they control | Entry timing, position size, whether to buy Day 1 or wait |
| What they fear | Buying the top, catching a falling knife, getting front-run by faster traders |
| Information edge | Market structure knowledge, cross-venue data, historical TGE pattern analysis |
The Retail Buyer
Individual investors buying the token on Day 1, often driven by excitement and social media.
| Aspect | Detail |
|---|---|
| Primary goal | "Get in early" on a new token |
| Secondary goal | Avoid being the exit liquidity for insiders |
| What they control | Whether to buy now or wait |
| What they fear | Missing the pump (FOMO) or buying the top |
| Information edge | Minimal — often the last to know and the least informed participant |
How the Incentives Interact
PROJECT
(wants stable,
liquid market)
│
┌───────────┼───────────┐
│ │ │
EXCHANGE │ MMs
(wants volume, │ (want spread,
orderly market)│ manage risk)
│ │ │
└───────────┼───────────┘
│
┌─────────┴─────────┐
│ │
AIRDROP BUYERS
RECIPIENTS (want good entry,
(want to sell) don't want to be
exit liquidity)The fundamental tension: airdrop recipients want to sell, buyers want to buy cheap, and the MM is in the middle trying to profit from the spread while surviving the sell wave. The project and exchange both want this process to happen smoothly.
3. Why Market Makers Are Essential at a TGE
Without a Market Maker
Imagine a TGE with no designated market maker:
Order book at T+5m (no MM):
Asks (sellers):
$2.00 (50 tokens) ← airdrop seller
$1.80 (200 tokens) ← airdrop seller
$1.50 (500 tokens) ← airdrop seller
$1.20 (1000 tokens) ← desperate seller
Bids (buyers):
$0.50 (100 tokens) ← opportunistic buyer
$0.30 (200 tokens) ← lowball offer
Spread: $0.70 (58%!)
Problems:
- Enormous spread — nobody gets a fair price
- No price discovery — is fair value $0.50 or $1.50?
- Sellers can't sell without massive slippage
- Buyers can't buy without massive slippage
- Looks "dead" to observers → negative narrativeWith a Market Maker
Order book at T+5m (with MM):
Asks (sellers):
$2.00 (50 tokens) ← airdrop seller
$1.80 (200 tokens) ← airdrop seller
$1.22 (5000 tokens) ← MM ask
$1.20 (1000 tokens) ← airdrop seller
Bids (buyers):
$1.18 (5000 tokens) ← MM bid
$0.50 (100 tokens) ← opportunistic buyer
$0.30 (200 tokens) ← lowball offer
Spread: $0.04 (3.3%)
Benefits:
- Tight spread — reasonable prices for everyone
- Price discovery centered around $1.20
- Sellers can sell immediately at ~$1.18
- Buyers can buy immediately at ~$1.22
- Market looks active and liquid → positive narrativeThe MM transforms an illiquid, chaotic order book into a functioning market.
What the MM Provides
- Price discovery — by continuously quoting, the MM establishes where fair value is
- Immediacy — anyone can trade immediately at the MM's quotes
- Depth — the MM provides size, so large orders don't move the price as much
- Stability — the MM absorbs temporary supply/demand imbalances
- Narrative — a liquid market with tight spreads looks healthy and attracts more participants
What It Costs the MM
- Inventory risk — buying airdrop supply that may drop in value
- Adverse selection — being on the wrong side vs. informed sellers
- Capital cost — tying up significant capital in a high-risk, uncertain asset
- Operational risk — systems must work flawlessly on the most chaotic day possible
This is why MM relationships are negotiated in advance, and why MMs receive special arrangements (token loans, fee discounts, rebates) for TGE market making.
4. The MM-Exchange Relationship at a TGE
What the MM Needs from the Exchange
Before agreeing to make a market on a new token, the MM asks the exchange a series of questions. The document you saw — with its three "questions" — is essentially the MM's pre-launch information request to the exchange.
| Question | Why the MM Asks It |
|---|---|
| Opening mechanism (auction or direct?) | Determines whether the MM can see flow before committing capital |
| Reference price (strong, weak, none?) | Determines how wide to quote and how much uncertainty to price in |
| Claim friction (instant, delayed, vesting?) | Determines the sell pressure timeline — the #1 driver of inventory risk |
| Fee structure | What rebates does the MM receive for providing liquidity? |
| API access | Will the MM have priority API endpoints, higher rate limits? |
| Token loan | Will the project or exchange lend the MM tokens to sell? (So the MM has inventory on both sides) |
| Other MMs | How many other market makers will be quoting? (Competition affects spread capture) |
| Listing venue exclusivity | Is this the only exchange listing, or are others listing simultaneously? |
What the Exchange Needs from the MM
| Requirement | Why the Exchange Asks It |
|---|---|
| Spread commitment | Maximum allowable spread (e.g., 2% within first hour, 1% by Day 2) |
| Depth commitment | Minimum order size per side (e.g., $50K notional within 1% of mid) |
| Uptime commitment | Must quote X% of the time during first 24 hours |
| Backstop agreement | Will the MM backstop liquidations if needed? |
| Reporting | Will the MM share data on flow quality, toxicity, etc.? |
The Deal
The typical MM deal for a TGE looks something like:
Exchange / Project provides:
- Token loan: 500,000 tokens (for MM to sell)
- MM fee tier: 0 bps maker, 2 bps taker (or negative maker)
- Priority API access
- Advance notice of listing details
- Agreed communication channel for real-time coordination
MM commits to:
- Quote from T+0 (or within first few minutes)
- Max spread: 3% at open, 1.5% by T+1h, 1% by end of Day 1
- Min depth: $25K per side at open, $100K per side by T+1h
- 95%+ uptime in first 24 hours
- Report on Day 1 metricsThe specifics vary enormously. A high-profile TGE might have 3-5 competing MMs. A smaller listing might have one designated MM. Some projects pay the MM directly (cash or tokens); others rely on the exchange's MM incentive program.
5. How Each Participant Should Think About Price
There Is No "Right Price" at a TGE
This is the most important concept to internalize. At a TGE, there is no fundamental value in the traditional sense. The token just came into existence. It has no earnings, no cash flows, and its utility is speculative. The "right price" is whatever the market discovers through the interaction of all participants.
Every participant should think about price through their own lens:
The Market Maker's View: Price Is a Risk Management Problem
The MM doesn't care whether the token is worth $1 or $10 — they care about managing the spread between what they buy and sell. Their view of "price" is:
"What is the price right now, and which direction is it going in the next 5 minutes?"| MM Question | How They Think About It |
|---|---|
| Where to center quotes? | Use reference price (if any) as a starting point, then let market flow move the mid |
| How wide should the spread be? | Wide enough to cover the risk of being wrong, narrow enough to capture flow |
| Which side am I more worried about? | If sell pressure is heavy → widen bids. If buy pressure is heavy → widen asks |
| When to tighten? | Only after confidence in the current price level grows (T+15m minimum) |
| What's my max inventory? | Define a hard limit in advance. If hit, pull quotes entirely |
The MM's price view is short-term and relative. They're not trying to predict where the token trades in a month — they're trying to not lose money in the next 10 minutes.
Key metric: Inventory P&L vs. Spread Revenue. If the MM is capturing $5K in spread per hour but losing $20K in inventory depreciation, they're underwater. The price view must constantly weigh: "Am I accumulating inventory that's losing value faster than I'm earning spread?"
The Exchange's View: Price Is a Market Quality Metric
The exchange doesn't trade the token — they facilitate trading. Their view of "price" is:
"Is price discovery happening in an orderly way?"| Exchange Question | How They Think About It |
|---|---|
| Is the spread reasonable? | Tight spreads = good UX. Wide spreads = market looks broken |
| Is there depth? | Can a $10K order execute without moving price 5%? If not, liquidity is thin |
| Are there price dislocations? | Is the Backpack price wildly different from other venues? If so, something is wrong |
| Is there manipulation? | Wash trading? Spoofing? Layering? These undermine trust |
| Is the price "sticky"? | Does price bounce around 5% every minute, or is it stabilizing? |
The exchange wants price to converge to a consensus level that reflects genuine supply and demand. They don't want the price to be "high" or "low" — they want it to be fair and stable, because that's what makes their market trustworthy.
What the exchange monitors:
- Spread: Should be tightening over time (3% → 1% → 0.5%)
- Depth: Should be growing over time as MMs gain confidence
- Volatility: Should be decreasing over time
- Volume: Should show organic, two-sided flow (not just MM ↔ MM)
- Price consistency: Should be converging with other venues (if the token lists elsewhere)
The Token Creator's View: Price Is a Narrative and Treasury Problem
The project cares about price for two reasons: narrative (community perception) and treasury (their token holdings are valued at this price).
"Is the price at a level that supports a positive narrative and doesn't
destroy the project's treasury value?"| Project Question | How They Think About It |
|---|---|
| Is the price above the "community expectation"? | If airdrop recipients expected $X and it opened at $0.5X, the narrative is negative |
| Is the token dumping? | A -80% Day 1 candle is catastrophic for community morale |
| What's the FDV? | Fully Diluted Valuation = price × total supply. If too high, sophisticated investors won't touch it. If too low, the project looks like a failure |
| Are we losing treasury value? | The project holds tokens in its treasury. Price drops directly reduce their runway |
| Can we deploy tokens for partnerships/grants at this price? | If the token is at $0.01, a 1M token grant is worth $10K — not useful for partnerships |
The project's dilemma: They want a high price (good narrative, treasury value) but they also know that an artificially high price will crash — which is worse than opening lower and appreciating over time. The best outcome for the project is a moderate opening price followed by gradual appreciation, not a pump-and-dump.
What smart projects do:
- Design tokenomics with gradual unlock schedules (vesting) to avoid Day 1 dumping
- Set airdrop allocations at a level that balances community reward with sell pressure
- Communicate realistic expectations about Day 1 price to the community
- Arrange sufficient MM support so the market doesn't look dead
- Potentially implement claim delays or linear vesting to smooth sell pressure
The Sophisticated Investor's View: Price Is a Supply/Demand Equation
The professional investor/fund thinks about price in terms of circulating supply, demand catalysts, and comparable valuations.
"What should this token be worth relative to comparable tokens,
and where is the price going to be in 1 week / 1 month / 6 months?"| Investor Question | How They Think About It |
|---|---|
| Circulating supply | How many tokens are actually tradeable today? (Not total supply — circulating supply) |
| FDV vs. market cap | FDV = price × total supply. Market cap = price × circulating supply. A $10B FDV with $100M circulating market cap means massive future dilution |
| Unlock schedule | When do team/investor/ecosystem tokens unlock? Each unlock = new sell pressure |
| Comparable valuation | Similar protocols trade at what FDV? If competitors are at $500M FDV and this opens at $5B, it's likely overvalued |
| Demand catalysts | What drives buying? Exchange listings, partnerships, product launches, ecosystem growth |
| Sell pressure analysis | How much of the airdrop will be sold vs. held? Historical TGE data suggests 40-70% of airdrops are sold within 48 hours |
The sophisticated investor's edge: They do this analysis before the TGE and set target entry prices. They don't buy at any price — they wait for the price to reach their target. This is why sophisticated investors often buy after the initial dump, not at the open.
Sophisticated Investor's Price Framework:
1. Estimate circulating supply at TGE
Example: 100M tokens circulating out of 1B total
2. Estimate reasonable FDV based on comparables
Example: Similar protocols at $500M-$1B FDV
3. Calculate target price range
If FDV = $500M, total supply = 1B → price = $0.50
If FDV = $1B, total supply = 1B → price = $1.00
Target range: $0.50 - $1.00
4. Estimate Day 1 supply pressure
If 60% of airdrop sells → heavy supply
If premarket price is $1.50 → overvalued vs. target
Strategy: Wait for price to drop into target range
5. Set orders
Bid at $0.60 (below target for margin of safety)
Full position at $0.50
Stop loss at $0.30 (if thesis is wrong)The Airdrop Recipient's View: Price Is "Free Money Math"
Airdrop recipients think about price differently because their cost basis is effectively zero.
"How much can I get for these tokens I received for free?"| Recipient Question | How They Think About It |
|---|---|
| What's my allocation worth right now? | At current price × my tokens = $X. Is that enough to bother selling? |
| Will it go higher? | If I think it will, I should hold. If I think this is the peak, sell now |
| What are others doing? | If everyone is selling, price will drop. If most are holding, price may rise |
| Claim and sell, or claim and hold? | The decision tree: sell 100% now, sell 50% now and hold 50%, or hold 100% |
The game theory of airdrops:
If everyone holds → price stays up or rises → everyone benefits
If everyone sells → price crashes → first sellers get the best price
If you hold while others sell → you lose relative to sellers
This is a prisoner's dilemma. The dominant strategy for individuals
is to sell early, which is why TGE sell pressure is heavy.Most airdrop recipients fall into three categories:
- Immediate sellers (~40-50%) — claim and sell as fast as possible
- Partial sellers (~20-30%) — sell some, hold some
- Holders (~20-30%) — claim and hold, either by conviction or inertia
6. Market Scenarios (S1-S4)
The playbook defines four possible market scenarios for the first minutes/hours of trading. The MM's job is to detect which scenario is unfolding and adjust accordingly:
| Scenario | Name | What's Happening | Signals | MM Response |
|---|---|---|---|---|
| S1 | Dump | Heavy sell pressure, price dropping. Airdrop recipients aggressively selling | Taker flow 70%+ sell, price dropping >1%/min, ask side thin | Widen spreads, shift bid-heavy (buy at discount), reduce size |
| S2 | Ghost | Very low volume, erratic price action, no clear direction | <$10K volume in first 5m, large spread between trades, price random walks | Trade very light, wide spreads, wait for information |
| S3 | Pump | Price shooting up, strong buy pressure, FOMO-driven buying | Taker flow 70%+ buy, price rising >1%/min, bid side swept | Shift ask-heavy (sell into rally), be cautious of reversal |
| S4 | Balanced | Relatively normal two-sided flow. Price finding equilibrium | 40-60% buy/sell split, price oscillating within band, depth building | Tighten spreads gradually, increase size |
Scenario Detection Flow:
T+0: Open with wide spreads, observe
│
├─ Heavy sell flow, price dropping fast ──────→ S1 (Dump)
│ Most common at TGEs (~40-50% of launches)
│
├─ Almost no trades, thin book ───────────────→ S2 (Ghost)
│ Common when claim is delayed (~15-20%)
│
├─ Strong buy flow, price spiking up ─────────→ S3 (Pump)
│ Less common, usually driven by hype (~15-20%)
│
└─ Balanced buy/sell, price stable-ish ───────→ S4 (Balanced)
Best case scenario (~15-25%)Scenario Transitions
Scenarios aren't static — they evolve. Common transitions:
S2 (Ghost) ──→ S1 (Dump) When claim opens and sell wave arrives
S3 (Pump) ──→ S1 (Dump) When FOMO exhausts, profit-taking begins
S1 (Dump) ──→ S4 (Balanced) When sell pressure exhausts, buyers step in
S2 (Ghost) ──→ S3 (Pump) When a single large buyer enters thin market
S4 (Balanced) ──→ S1 (Dump) When a large unlock or delayed claim arrivesThe key insight: you won't know which scenario you're in until trading begins, and the scenario can change at any moment. The three questions below help the MM narrow the probabilities and prepare for transitions.
7. Question 1: Opening Mechanism
How does trading actually start — is there an order collection period (call auction) or does trading go live immediately?
Option A: Call Auction
In a call auction, orders are collected for a period (e.g., 5-10 minutes) before any matching occurs. A single clearing price is computed that maximizes matched volume, and all orders execute at that price simultaneously. (See Auction Mechanisms for a full explanation.)
Call Auction Timeline:
T-10m Auction opens. Orders accepted, no matching.
T-5m Indicative price published (updates in real-time).
T-0m Auction closes. Clearing price calculated. Orders fill.
T+0 Continuous trading begins.MM implications:
| Phase | MM Action |
|---|---|
| Auction start | Submit wide two-sided quotes (both bids and asks) |
| Mid-auction | Observe indicative price and order imbalance, adjust skew |
| Final minutes | Lock in position (some auctions freeze changes near close) |
| After match | Transition to continuous quoting, informed by clearing price |
Advantages for the MM:
- Can see aggregated demand/supply before committing real capital
- Indicative price reduces first-trade volatility
- Time to form a hypothesis about which scenario (S1-S4) is likely
Risks:
- Other MMs also see the same flow data — less information edge
- If heavy sell-side stacking is visible, the MM may need to widen bids defensively
Why this is unlikely at a TGE: A call auction requires both buy and sell orders in the collection phase. But at a TGE, airdrop recipients need to claim their tokens first before they can place sell orders. If the claim process hasn't happened yet at auction start, there's no natural sell-side supply — only buy orders from speculators and the MM's own quotes. This makes a call auction mechanically difficult for the initial open.
Option B: Direct Open (Most Likely)
Trading begins immediately at the listing time. The first trade sets the opening price. No order collection period.
Direct Open Timeline:
T-1m MM stages orders but doesn't submit them yet
T+0 Trading goes live. MM submits wide quotes.
T+0-60s OBSERVATION PHASE — first trades will be erratic, don't react
T+1m Deploy initial liquidity based on observed flow
T+5m Adjust strategy based on emerging scenarioMM implications:
| Phase | MM Action |
|---|---|
| T-1m | Orders prepared, not live |
| T+0 | Go live with wide spreads (2-3%) |
| T+0 to T+60s | Observe only — first trades will be erratic |
| T+1m onward | Begin deploying liquidity, identify scenario |
Advantages:
- Faster to react if well-prepared
- First mover can capture wide early spreads
Risks:
- First trades may gap wildly — someone submitting a market order into a thin book can move price 50%+
- No visibility into aggregated flow — quoting blind
- Higher volatility in the first 60 seconds
Summary
| Mechanism | Spread at Open | Size at Open | When to Tighten |
|---|---|---|---|
| Call Auction | Moderate (1.5-2%) | Moderate | After clearing price known |
| Direct Open | Wide (2-3%) | Small | After T+60s observation |
8. Question 2: Reference Price
A reference price is a starting point — a number the MM can center their quotes around. In normal market making, this comes from other exchanges (Binance price, Coinbase price, etc.). At a TGE, that luxury doesn't exist.
Why Reference Price Matters
Without a reference price, the MM faces a fundamental question: "Where should my mid-price be?"
If BTC is trading at $100,000 on Binance, an MM on Backpack knows to center quotes around $100,000. But if TOKEN_XYZ has never traded before, the MM has no idea if fair value is $0.50 or $5.00. Quoting too high means nobody buys (MM is stuck with inventory). Quoting too low means the MM sells too cheap and gets run over by the opening rally.
Strong Reference (Not Typical at TGE)
A strong reference means a liquid premarket with reliable depth — for example, a token that's been trading on a well-known premarket platform with millions in daily volume and real depth.
| Factor | Setting |
|---|---|
| Initial spread | Moderate (1-1.5%) around reference |
| Initial size | Moderate |
| Scenario detection speed | Fast — less noise in price signal |
This is rare at a TGE. Most premarket activity is thin and unreliable.
Weak Reference (Most Common)
A weak reference means a premarket price exists but the market is thin, has low volume, and could be easily manipulated. Someone could move the premarket price 30% with a $10K order. This is the typical situation at most TGEs.
| Factor | Setting |
|---|---|
| Initial spread | Wide (2-3%) centered loosely around reference |
| Price alarm bands | Allow ±20-30% from reference before flagging |
| Trust level | Use as loose anchor, not hard target |
How to use a weak reference:
- Note the premarket price but don't anchor tightly to it
- Set initial quotes ±15-20% around it (wide band)
- Watch for gap at open:
- Gap up >15% from reference → S3 (Pump) likely, shift ask-heavy
- Gap down >15% from reference → S1 (Dump) likely, shift bid-heavy
- Within ±10% → Likely S4 (Balanced), continue observing
- Ignore premarket depth — too thin to be meaningful
- Trust Backpack's own flow data over premarket reference after T+5m
No Reference
No premarket exists at all. True price discovery happens entirely at the exchange open.
| Factor | Setting |
|---|---|
| Initial spread | Very wide (3-5%) |
| Initial size | Minimal |
| Observation phase | Extended (T+0 to T+2m before acting) |
Without any anchor, the MM is completely blind. The strategy is to deploy minimal capital, observe the first trades, and let the market tell you where fair value is. This is the riskiest scenario for MMs because they can misjudge fair value by a wide margin.
Summary
| Reference Strength | Initial Spread | Trust Duration | Scenario Detection |
|---|---|---|---|
| Strong | 1-1.5% | Trust from T+0 | Fast |
| Weak | 2-3% | Distrust, verify with exchange flow | Moderate |
| None | 3-5% | N/A — pure discovery | Slow |
9. Question 3: Claim Friction
This is arguably the most important question for predicting the sell pressure timeline. Claim friction = how quickly can airdrop recipients get their tokens into a sellable state on the exchange?
The term "friction" captures everything between "airdrop announced" and "tokens sold on exchange" — the claim process, blockchain confirmation times, exchange deposit times, and any vesting/lockup restrictions.
Instant Claim, No Restrictions
Airdrop recipients can claim immediately at TGE. No vesting, no cooldown, no transfer lock. Tokens hit wallets and can be deposited to the exchange and sold instantly.
What to expect:
Sell Pressure Timeline (Instant Claim):
T+0 to T+5m Prepared sellers (10-15% of Day 1 volume)
These people had sell orders ready before TGE.
Often the most sophisticated — project insiders,
KOLs, people who knew the exact listing time.
T+5m to T+15m Quick claimers (20-25%)
Claimed fast, deposited to exchange, selling now.
Mix of sophisticated and regular users.
T+15m to T+30m Second wave (20-25%)
Slower claimers arriving. CEX deposits clearing.
More regular users, less sophisticated.
T+30m to T+60m Tail sellers (15-20%)
Late claimers, people who took time to decide.
Some panic sellers triggered by seeing price action.
T+1h+ Residual (remaining %)
Trickle of remaining sellers over hours/days.
People who didn't check, held then decided to sell.MM implications:
| Factor | Setting |
|---|---|
| Sell pressure timing | Front-loaded — heaviest T+0 to T+30m |
| First hour intensity | Very high (50-70% of Day 1 selling) |
| S1 (Dump) probability | Elevated |
| Initial stance | Wider spreads, prepared for heavy one-sided flow |
Delayed Claim (30-60 min After TGE, or Technical Issues)
The airdrop claim opens after spot trading has already begun. This creates two distinct phases with very different dynamics:
Phase 1 (Pre-Claim): T+0 to claim open
- Who's trading: MMs vs. MMs + small initial supply
- Likely scenario: S2 (Ghost) or S3 (Pump)
- Volume: Low, potentially erratic
- Risk: Price can pump far above "fair value" with tiny volume
because there's no sell-side supply from airdrop
Phase 2 (Post-Claim): Claim opens onward
- Sell wave arrives 5-10 minutes after claim opens
- Scenario likely shifts to S1 (Dump) or S4 (Balanced)
- This is a MAJOR transition point — be prepared
- If price pumped in Phase 1, the correction can be violentMM implications:
| Factor | Setting |
|---|---|
| Pre-claim trading | Light position, wide spreads, be wary of fake pump |
| Key checkpoint | Claim open time — expect a scenario shift |
| Post-claim adjustment | Watch for sell wave 5-10 min after claim opens |
| Dangerous trap | Don't get caught long from Phase 1 pump when Phase 2 dump arrives |
The critical insight: the claim opening time is as important as the trading opening time. The MM must treat it as a second "market open" event.
Vested / Linear Unlock
Some projects design their airdrop with vesting — recipients get tokens gradually over weeks or months rather than all at once. This dramatically changes the dynamics:
Vesting Example:
Total airdrop: 100M tokens
Day 1 unlock: 25% (25M tokens claimable)
Linear vest: Remaining 75M over 6 months
Impact on Day 1:
- Sell pressure reduced by 75% vs. instant claim
- S4 (Balanced) much more likely
- MM can quote tighter from the start
- Price more likely to reflect genuine demand vs. supplySummary
| Claim Type | Day 1 Sell Pressure | S1 Probability | MM Initial Spread |
|---|---|---|---|
| Instant, no restrictions | Very high (50-70% of airdrop may sell) | High | Wide (2-3%) |
| Delayed (30-60 min) | High, but two-phased | Moderate-High | Wide, then adjust at claim |
| Vested (25% Day 1) | Moderate | Moderate | Moderate (1.5-2%) |
| Fully vested (linear over months) | Low | Low | Tighter (1-1.5%) |
10. Putting It Together: The Opening Playbook
Given the most likely conditions at a TGE on Backpack — direct open, weak reference, instant claim — here is the combined playbook:
Pre-Open (T-5m to T+0)
Checklist:
☐ Note premarket reference price (if any)
☐ Set initial quotes ±15-20% around reference
☐ Stage orders but don't submit until T+0
☐ Confirm claim status (instant? delayed? issues?)
☐ Set monitoring alerts for S1/S2/S3/S4 triggers
☐ Define max inventory limit (e.g., "I won't hold more than $200K notional")
☐ Prepare contingency: if claim is delayed, switch to "light mode"
☐ Confirm API connectivity and rate limits
☐ Check if other MMs are onlineOpening Phase (T+0 to T+60s)
| Action | Detail |
|---|---|
| Go live | Submit wide quotes (2-3% spread) |
| Size | Small — minimal capital at risk |
| Observe | Watch first trades, don't react to noise |
| Don't do | Chase price, tighten spread, or add size |
Detection Phase (T+1m to T+5m)
| Signal | Interpretation | Response |
|---|---|---|
| Heavy sell flow, price dropping >15% from open | S1 (Dump) | Widen bids further, shift bid-heavy to accumulate at discount |
| Very few trades, erratic price | S2 (Ghost) | Stay wide, trade minimal, wait |
| Strong buy flow, price rising >15% from open | S3 (Pump) | Shift ask-heavy, sell into rally cautiously |
| Balanced flow, price within ±10% | S4 (Balanced) | Begin tightening spreads cautiously |
Stabilization Phase (T+5m to T+30m)
As the market reveals itself:
- Gradually tighten spreads (2-3% → 1.5% → 1% as confidence grows)
- Increase size on both sides
- Shift from "survival mode" to "normal market making"
- Watch for sell wave timing (claim-dependent)
- Re-evaluate scenario every 5 minutes
- Monitor inventory — are you accumulating more than expected?Normalization (T+30m to T+1h+)
If claim was instant:
- Bulk of sell pressure should be subsiding
- Flow becoming more two-sided
- Can approach normal market making parameters
If claim was delayed:
- Watch for sell wave at claim open + 5-10 min
- Be ready for scenario shift (S2/S3 → S1/S4)
- This is the most dangerous transition pointQuick Reference
| Phase | Time | Spread | Size | Focus |
|---|---|---|---|---|
| Open | T+0 to T+60s | 2-3% | Minimal | Observe, don't react |
| Detect | T+1m to T+5m | 2-3% | Small | Identify scenario |
| Adjust | T+5m to T+15m | 1.5-2% | Growing | Trade the scenario |
| Stabilize | T+15m to T+30m | 1-1.5% | Moderate | Converge to normal |
| Normalize | T+30m+ | Target spread | Full size | Standard MM operations |
11. Token Economics and Supply Dynamics
Understanding the token's supply structure is critical for all participants. The price at any moment is a function of circulating supply (how many tokens are actually tradeable) and demand (how many people want to buy and at what price).
Total Supply vs. Circulating Supply
Total Supply: 1,000,000,000 tokens (1B)
Breakdown:
├─ Airdrop: 15% (150M tokens) — claimable at TGE
├─ Team: 20% (200M tokens) — locked 1 year, then 3 year vest
├─ Investors: 15% (150M tokens) — locked 6 months, then 2 year vest
├─ Ecosystem: 25% (250M tokens) — DAO treasury, released over time
├─ Liquidity: 5% (50M tokens) — provided to MMs and exchanges
└─ Foundation: 20% (200M tokens) — reserved for future use
Circulating Supply at TGE: ~200M (airdrop + liquidity provision)
= 20% of total supply
Circulating Supply at 1 year: ~450M
= 45% of total supply (team begins unlocking)
Circulating Supply at 3 years: ~1B
= 100% of total supplyWhy This Matters for Price
Day 1:
Price: $1.00
Circulating supply: 200M tokens
Market Cap: $200M (price × circulating supply)
FDV: $1B (price × total supply)
FDV/Market Cap ratio: 5x
This means: for every $1 of circulating tokens,
there's $4 of locked tokens that will unlock over time.
What this tells a sophisticated investor:
"At $1.00, I'm buying at a $1B FDV. If comparable projects
trade at $500M FDV, this is overvalued by 2x even before
considering the 80% of supply still to unlock."The Unlock Schedule Problem
Every future unlock event is potential sell pressure. Sophisticated investors map these out:
FDV: $1B at current price
Month 0 (TGE): Airdrop unlocks → 150M tokens → heavy sell pressure
Month 6: Investor unlock → 150M begins vesting → sell pressure
Month 12: Team unlock → 200M begins vesting → sell pressure
Months 1-36: Ecosystem emissions → gradual → ongoing sell pressure
For the price to stay at $1.00:
New demand must absorb ALL of this new supply.
If demand stays flat, price must drop proportionally.This is why many TGE tokens experience a pattern of:
- Opening price → initial high
- Airdrop sell pressure → Day 1 dump
- Brief stabilization → weeks 1-4
- Investor unlock → next sell-off
- Team unlock → next sell-off
- Repeat until fully vested
FDV as a Valuation Framework
Fully Diluted Valuation (FDV) is the most common framework sophisticated investors use to evaluate TGE tokens:
FDV = Price × Total Supply
Comparison Framework:
If Project A (similar scope, similar traction) has FDV of $500M
And Project B (this TGE) opens at FDV of $2B
→ Project B is "expensive" relative to comparable
Sophisticated investors will:
1. Not buy at open
2. Wait for price to drop to comparable FDV range
3. Set bids at target FDV / total supply = target price| Metric | What It Tells You |
|---|---|
| Market Cap (price × circulating) | What the tradeable market is worth today |
| FDV (price × total supply) | What the market implies the entire project is worth |
| FDV / Market Cap ratio | How much future dilution exists (>2x means heavy future unlock pressure) |
| FDV vs. comparables | Whether the token is cheap or expensive vs. similar projects |
12. Historical Patterns: What Usually Happens
While every TGE is different, historical data from major crypto airdrops reveals patterns:
Common Day 1 Patterns
Pattern 1: "The Dump" (Most Common, ~40-50% of TGEs)
Price action: Opens high, sells off 30-60% in first hour
Cause: Airdrop recipients sell aggressively
Example: Token opens at $1.00, drops to $0.40-$0.70 by hour 2
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Pattern 2: "The V-Recovery" (~15-20% of TGEs)
Price action: Initial dump, then strong recovery
Cause: Sell pressure exhausts, smart money buys the dip
Example: Opens at $1.00, drops to $0.50, recovers to $0.80
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Pattern 3: "The Pump and Dump" (~10-15% of TGEs)
Price action: Initial pump on hype/FOMO, then violent reversal
Cause: FOMO buying exhausts, airdrop sellers arrive late
Example: Opens at $1.00, pumps to $1.50, then crashes to $0.30
Price │ ████
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Pattern 4: "Steady State" (Rare, ~10-15% of TGEs)
Price action: Opens and stays relatively stable
Cause: Well-designed tokenomics, vesting, balanced demand/supply
Example: Opens at $1.00, trades $0.85-$1.15 range for first day
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└──────────────────────────────────── TimeHistorical Airdrop Data Points
| Metric | Typical Range |
|---|---|
| Day 1 sell-through (% of airdrop sold) | 40-70% |
| Peak-to-trough on Day 1 | -30% to -70% |
| Time to reach Day 1 low | 30 min to 4 hours |
| Recovery rate (% that return to open price within 7 days) | ~20-30% |
| Percentage that trade below Day 1 open price after 30 days | ~60-70% |
Key insight for all participants: The majority of TGE tokens trade below their opening price within 30 days. This suggests that the market systematically overprices tokens at launch (driven by hype and FOMO), and the "true" value is discovered over weeks as sell pressure plays out and fundamentals are evaluated.
13. Risk Considerations
For Market Makers
Inventory Risk Is Amplified
At a TGE, flow is predominantly one-directional (sell). The MM will accumulate long inventory from buying airdrop supply. If the token continues to drop, the MM takes inventory losses that dwarf any spread revenue.
Example:
MM buys 100,000 tokens in first 30 min (absorbing sell pressure)
Average buy price: $1.00
Price at T+1h: $0.60
Inventory loss: 100,000 × ($1.00 - $0.60) = $40,000
Spread captured: maybe $2,000-$5,000
Net: Large loss despite providing liquidityMitigation: Stay small early, widen bids to buy at deeper discounts, define a hard inventory limit, and don't try to catch a falling knife.
Adverse Selection Is Extreme
The first sellers at a TGE are often the most informed — project insiders, early investors, people who've been planning their exit for months. Their selling is a strong signal that the current price may be too high. The MM is on the wrong side of this information asymmetry by definition.
Scenario Misidentification
Misreading the scenario is costly:
- Thinking S4 (Balanced) when it's actually S1 (Dump) → accumulate inventory that drops in value
- Thinking S1 (Dump) when it's actually S3 (Pump) → miss the rally, get squeezed on short inventory
- Thinking S2 (Ghost) when it's about to become S1 → not prepared for sell wave
Mitigation: Re-evaluate the scenario frequently (every 5 minutes in the first hour), and don't commit heavily until the scenario is clear.
For the Exchange
- Matching engine load — TGEs can generate 10-100x normal order rate. System must handle the spike
- Market surveillance — watch for manipulation (wash trading, spoofing, layering)
- MM coordination — if the designated MM goes down, the market becomes illiquid instantly
- Reputation risk — a "failed" TGE (illiquid, crashed, manipulated) reflects poorly on the exchange
For the Token Creator
- Airdrop design risk — too generous = massive sell pressure. Too stingy = community anger
- Listing venue risk — listing on a single exchange creates concentration risk
- Communication risk — overpromising on price expectations backfires when reality hits
- Treasury risk — the project's own token holdings lose value if price dumps
For Investors
- FOMO risk — buying at the open is historically a losing strategy for most TGEs
- Liquidity risk — Day 1 spreads are wide, meaning large orders face significant slippage
- Information asymmetry — you know less than the project, the MMs, and the exchange
- Unlock risk — even if Day 1 goes well, future unlocks create ongoing sell pressure
Technical Risks (All Participants)
- Claim infrastructure may fail or lag, shifting sell pressure timing unexpectedly
- Exchange matching engine under heavy load at listing — potential latency spikes
- Blockchain congestion can delay deposits/withdrawals
- Price feeds from premarket may be stale or wrong
- API rate limits may be hit during high-activity period
14. Key Terminology
| Term | Meaning |
|---|---|
| TGE | Token Generation Event — when a new token launches and becomes tradeable |
| MM / LP | Market Maker / Liquidity Provider — firm quoting both buy and sell sides |
| Airdrop | Free token distribution to existing community members or protocol users |
| Claim | The process of airdrop recipients collecting their tokens on-chain |
| Claim friction | All barriers between "airdrop announced" and "tokens sold" — claim delays, blockchain time, exchange deposit time |
| Premarket | Informal/thin trading before the official exchange listing |
| Spread | Difference between best bid (highest buy) and best ask (lowest sell) |
| Skew | Adjusting bid/ask asymmetrically based on inventory or market view |
| Reference price | A baseline price the MM uses to anchor their initial quotes |
| Scenario detection | Identifying which market regime (S1-S4) is currently unfolding |
| Bid-heavy | More aggressive on bids (more willing to buy) — used when MM wants to accumulate |
| Ask-heavy | More aggressive on asks (more willing to sell) — used when MM wants to reduce inventory |
| FDV | Fully Diluted Valuation — price × total token supply (including locked tokens) |
| Market Cap | Price × circulating supply (only tradeable tokens) |
| Circulating supply | Tokens that are currently unlocked and tradeable |
| Vesting | Gradual token unlock over time (e.g., 25% per quarter over 1 year) |
| Token loan | Tokens lent to the MM by the project so the MM has inventory to sell from Day 1 |
| Backstop | MM's agreement to absorb positions during extreme conditions (liquidations, crashes) |
| Adverse selection | Being traded against by someone with better information (informed flow) |
| Exit liquidity | The person who buys at the top and absorbs losses as the price drops — what nobody wants to be |