token-economics Checked

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 |