/token-economics

name: token-economics
description: Token supply dynamics, vesting analysis, inflation modeling, and valuation frameworks for crypto tokens

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