token-economics

Token Economics

Tokenomics — the study of token supply dynamics, distribution, and value accrual — is one of the most important factors in crypto asset analysis. Supply changes directly affect price: new tokens entering circulation create selling pressure, while burns and locks reduce it. Understanding these dynamics lets you estimate dilution risk, identify overvalued or undervalued tokens, and anticipate price-moving unlock events.

Why Tokenomics Matters

Price is a function of demand and supply. In crypto, supply is programmable and constantly changing:

• A token inflating at 50%/year needs 50% demand growth just to maintain price
• A large unlock releasing 10% of circulating supply in one day often causes 5-20% drawdowns
• Tokens with >80% of supply locked have extreme dilution risk ahead
• Protocols that burn fees can become net deflationary, creating structural price support

Key Supply Concepts

Total Supply vs Circulating Supply

total_supply      = maximum tokens that will ever exist (or current total minted)
circulating_supply = tokens currently available for trading
locked_supply     = total_supply - circulating_supply
circulating_pct   = circulating_supply / total_supply * 100

Market Cap vs Fully Diluted Valuation

market_cap = price * circulating_supply
fdv        = price * total_supply
fdv_mcap_ratio = fdv / market_cap

The FDV/MCap ratio measures future dilution risk:

FDV/MCap	Dilution Risk	Interpretation
1.0-1.5	Low	Most supply already circulating
1.5-3.0	Moderate	Significant supply still locked
3.0-5.0	High	Majority of supply not yet released
>5.0	Very High	Token will face massive dilution

Net Inflation Rate

annual_new_tokens = emissions + vesting_unlocks + rewards
annual_burned     = fee_burns + buyback_burns
net_new_tokens    = annual_new_tokens - annual_burned
net_inflation_rate = net_new_tokens / circulating_supply * 100  # percent per year

Supply Dynamics

Inflationary Pressure (tokens entering circulation)

• Emissions: Block rewards, liquidity mining, staking rewards
• Vesting unlocks: Team, investor, and advisor tokens unlocking on schedule
• Unlock events: Large one-time releases (cliff expirations)
• Treasury spending: DAO or foundation distributing tokens

Deflationary Pressure (tokens leaving circulation)

• Fee burns: Protocol burns a portion of transaction fees (like EIP-1559)
• Buyback and burn: Protocol uses revenue to buy and permanently destroy tokens
• Staking locks: Tokens locked in staking (temporarily removed from circulation)
• Lost tokens: Permanently inaccessible tokens (lost keys, burn addresses)

Selling Pressure Estimation

daily_emissions_usd = daily_new_tokens * token_price
percent_sold = 0.50  # assume 50% of new tokens are sold (conservative)
daily_sell_pressure = daily_emissions_usd * percent_sold
sell_pressure_ratio = daily_sell_pressure / daily_volume
# > 0.05 (5%) = significant selling pressure
# > 0.10 (10%) = heavy selling pressure

Vesting and Unlock Schedules

Key Concepts

• Cliff: Period before any tokens unlock (typically 6-12 months)
• Linear vesting: Constant rate of unlock after cliff (monthly or daily)
• Stepped vesting: Periodic unlocks at set intervals (quarterly)
• TGE unlock: Percentage released at Token Generation Event

Analyzing Unlock Impact

unlock_amount_tokens = 10_000_000
avg_daily_volume_tokens = 5_000_000
unlock_volume_ratio = unlock_amount_tokens / avg_daily_volume_tokens

# Impact assessment:
# < 1x daily volume: minor impact
# 1-5x daily volume: moderate impact, expect 2-5% drawdown
# 5-10x daily volume: major impact, expect 5-15% drawdown
# > 10x daily volume: severe impact, expect 10-30% drawdown

Tracking Sources

• CoinGecko / CoinMarketCap: Basic supply data
• Token Terminal: Revenue and valuation metrics
• Token Unlocks (token.unlocks.app): Detailed unlock schedules
• Project documentation: Whitepapers, tokenomics pages
• On-chain: Vesting contract state, treasury balances

Token Distribution Analysis

Typical Allocation Ranges

Category	Typical Range	Red Flag
Team/Founders	15-25%	>30%
Investors (Seed+Series)	10-30%	>40%
Community/Ecosystem	20-40%	<15%
Treasury/DAO	10-20%	<5%
Public Sale	5-20%	<2%
Advisors	2-5%	>10%

Distribution Red Flags

• >50% insider allocation (team + investors): Insiders control price
• Short vesting (<1 year): Quick dump risk
• No cliff: Immediate selling from day one
• Large single wallets: Concentration risk (use token-holder-analysis skill)
• Unlabeled large allocations: Hidden insider holdings

Distribution Quality Score

def distribution_score(team_pct: float, investor_pct: float,
                       community_pct: float, cliff_months: int,
                       vesting_months: int) -> str:
    """Rate token distribution quality."""
    score = 0
    insider_pct = team_pct + investor_pct

    if insider_pct < 30: score += 3
    elif insider_pct < 50: score += 1

    if community_pct > 30: score += 2
    elif community_pct > 20: score += 1

    if cliff_months >= 12: score += 2
    elif cliff_months >= 6: score += 1

    if vesting_months >= 36: score += 2
    elif vesting_months >= 24: score += 1

    if score >= 8: return "Excellent"
    if score >= 6: return "Good"
    if score >= 4: return "Moderate"
    return "Poor"

Valuation Frameworks

Revenue-Based Metrics

# Price-to-Earnings (for fee-generating protocols)
pe_ratio = fdv / annualized_net_revenue

# Price-to-Sales
ps_ratio = fdv / annualized_total_volume

# Price-to-Fees
pf_ratio = fdv / annualized_protocol_fees

# Revenue Multiple (adjusted for token value accrual)
rev_multiple = fdv / (annualized_fees * fee_share_to_token_holders)

Typical ranges (crypto, highly variable):

• P/E: 10x-100x+ (DeFi protocols)
• P/S: 0.5x-50x
• P/F: 20x-500x

Network Value Metrics

# Network Value to Transactions (NVT)
nvt = market_cap / daily_transaction_volume_usd
# High NVT (>100): potentially overvalued or store-of-value
# Low NVT (<20): potentially undervalued or high activity

# Market Value to Realized Value (MVRV)
# realized_value = sum of each token at its last-moved price
mvrv = market_cap / realized_value
# MVRV > 3.0: historically overvalued zone
# MVRV < 1.0: historically undervalued zone

Comparable Analysis

def comparable_analysis(target: dict, peers: list[dict]) -> dict:
    """Compare target token metrics against peer group.

    Each dict has: name, fdv, revenue, tvl, users
    Returns premium/discount percentages.
    """
    peer_fdv_rev = [p["fdv"] / p["revenue"] for p in peers if p["revenue"] > 0]
    peer_fdv_tvl = [p["fdv"] / p["tvl"] for p in peers if p["tvl"] > 0]

    avg_fdv_rev = sum(peer_fdv_rev) / len(peer_fdv_rev) if peer_fdv_rev else 0
    avg_fdv_tvl = sum(peer_fdv_tvl) / len(peer_fdv_tvl) if peer_fdv_tvl else 0

    target_fdv_rev = target["fdv"] / target["revenue"] if target["revenue"] > 0 else 0
    target_fdv_tvl = target["fdv"] / target["tvl"] if target["tvl"] > 0 else 0

    return {
        "fdv_rev_premium": (target_fdv_rev / avg_fdv_rev - 1) * 100 if avg_fdv_rev else None,
        "fdv_tvl_premium": (target_fdv_tvl / avg_fdv_tvl - 1) * 100 if avg_fdv_tvl else None,
    }

Token Value Accrual Mechanisms

Mechanism	Description	Valuation Impact
Fee sharing	Holders receive protocol revenue	Direct cash flow, use DCF
Governance	Voting rights on protocol	Hard to value, often overpriced
Utility	Required for protocol use	Demand scales with usage
Buyback & burn	Protocol buys and burns	Reduces supply, structural bid
Staking rewards	Yield from staking	Inflationary if from emissions
veToken model	Lock for boosted rewards + governance	Reduces circulating supply

PumpFun Token Economics

PumpFun tokens on Solana have simplified tokenomics:

• Fixed supply: 1,000,000,000 tokens (1 billion)
• No vesting: All tokens available immediately at launch
• No team allocation: 100% available on bonding curve
• Bonding curve pricing: Price determined by curve math, not supply changes
• Post-graduation: After bonding curve completes, supply is fully liquid on Raydium
• No inflation: No emissions, no staking rewards, no additional minting

Analysis focus for PumpFun tokens shifts from supply dynamics to:

• Holder concentration (use token-holder-analysis)
• Volume sustainability
• Liquidity depth (use liquidity-analysis)
• Dev wallet behavior

Integration with Other Skills

Skill	Integration
defillama-api	Fetch TVL, revenue, fees for valuation metrics
token-holder-analysis	Analyze holder concentration and whale behavior
coingecko-api	Fetch supply data, market cap, FDV
liquidity-analysis	Assess trading liquidity relative to supply
risk-management	Supply dilution as risk factor
position-sizing	Adjust size for dilution risk

Files

References

• references/supply_analysis.md — Circulating supply tracking, inflation modeling, unlock analysis, burn mechanics
• references/valuation_frameworks.md — Revenue-based valuation, NVT, MVRV, comparable analysis, value accrual

Scripts

• scripts/tokenomics_analyzer.py — Fetch and analyze token supply metrics from CoinGecko, calculate dilution risk and basic valuations
• scripts/supply_modeler.py — Project token supply over 12 months given emission and burn parameters, scenario analysis