token-holder-analysis

代币持有者分析——集中度、分布与风险

分析谁在持有代币、所有权集中度如何，以及内部人士的持仓模式是否暗示风险。这是一项至关重要的交易前安全检查——持仓过于集中意味着少数钱包就能让价格暴跌。

快速开始

import httpx
import math

# Using Helius DAS API for holder data
HELIUS_KEY = os.getenv("HELIUS_API_KEY", "")
HELIUS = f"https://mainnet.helius-rpc.com/?api-key={HELIUS_KEY}"

# Or using SolanaTracker for holder + risk data
ST_KEY = os.getenv("SOLANATRACKER_API_KEY", "")
ST = "https://data.solanatracker.io"

# Get top holders via RPC
def get_top_holders(mint: str) -> list[dict]:
    resp = httpx.post(HELIUS, json={
        "jsonrpc": "2.0", "id": 1,
        "method": "getTokenLargestAccounts",
        "params": [mint],
    })
    return resp.json()["result"]["value"]

holders = get_top_holders("TOKEN_MINT")

数据来源

来源	提供内容	身份验证
Solana RPC (getTokenLargestAccounts)	前 20 名持有者、供应量	RPC 密钥
Helius DAS (getAsset, token accounts)	解析后的持有者数据、元数据	API 密钥
SolanaTracker (/tokens/{t}/holders/top)	前 100 名持有者、捆绑买入检测	API 密钥
Birdeye (/defi/token_security)	前 10 名持有者占比、创建者余额、冻结/铸造权限	API 密钥

集中度指标

前 N 名持有者占比

最简单的衡量方式——前 N 名持有者控制了多少比例的供应量？

def top_n_percentage(holders: list[dict], supply: int, n: int = 10) -> float:
    """Calculate percentage held by top N holders.

    Args:
        holders: Sorted list of holders (largest first).
        supply: Total token supply.
        n: Number of top holders.

    Returns:
        Percentage (0-100) held by top N.
    """
    top_n_amount = sum(int(h.get("amount", 0)) for h in holders[:n])
    return top_n_amount / supply * 100 if supply > 0 else 0

风险阈值：

• 前 10 名 < 30%：分布良好
• 前 10 名 30-50%：集中度中等
• 前 10 名 50-80%：集中度高——存在显著抛售风险
• 前 10 名 > 80%：极端——很可能由少数钱包控制

基尼系数

衡量代币分布的不平等程度（0 = 完全平等，1 = 一名持有者拥有全部代币）。

def gini_coefficient(amounts: list[float]) -> float:
    """Calculate Gini coefficient for holder distribution.

    Args:
        amounts: List of holder amounts (any order).

    Returns:
        Gini coefficient between 0 and 1.
    """
    if not amounts or all(a == 0 for a in amounts):
        return 0.0
    sorted_amounts = sorted(amounts)
    n = len(sorted_amounts)
    cumsum = sum((i + 1) * a for i, a in enumerate(sorted_amounts))
    total = sum(sorted_amounts)
    return (2 * cumsum) / (n * total) - (n + 1) / n

加密代币的解读：

• 基尼系数 < 0.6：较为罕见，分布非常均匀
• 基尼系数 0.6-0.8：成熟代币的典型水平
• 基尼系数 0.8-0.95：新代币中较常见
• 基尼系数 > 0.95：集中度极高，风险高

赫芬达尔-赫希曼指数（HHI）

衡量市场集中度——市场份额的平方和。

def hhi(amounts: list[float]) -> float:
    """Calculate HHI for holder concentration.

    Args:
        amounts: List of holder amounts.

    Returns:
        HHI value (0-10000). Higher = more concentrated.
    """
    total = sum(amounts)
    if total == 0:
        return 0.0
    shares = [a / total * 100 for a in amounts]
    return sum(s ** 2 for s in shares)

解读：

• HHI < 1500：竞争充分（集中度低）
• HHI 1500-2500：集中度中等
• HHI > 2500：集中度高

中本聪系数

控制超过 50% 供应量所需的最少持有者数量。

def nakamoto_coefficient(amounts: list[float]) -> int:
    """Calculate Nakamoto coefficient (holders needed for 51%).

    Args:
        amounts: Sorted list of holder amounts (largest first).

    Returns:
        Number of holders needed for majority control.
    """
    total = sum(amounts)
    if total == 0:
        return 0
    threshold = total * 0.51
    cumulative = 0
    for i, amount in enumerate(sorted(amounts, reverse=True)):
        cumulative += amount
        if cumulative >= threshold:
            return i + 1
    return len(amounts)

内部人士检测模式

捆绑买入检测

捆绑买入者通过原子交易捆绑包（经由 Jito）在代币上线时协调买入。检测信号：

def detect_bundler_patterns(holders: list[dict], first_buyers: list[dict]) -> dict:
    """Identify potential bundler activity.

    Args:
        holders: Current top holders.
        first_buyers: Early buyers from SolanaTracker /first-buyers endpoint.

    Returns:
        Bundler risk analysis.
    """
    early_still_holding = [
        b for b in first_buyers
        if b.get("holdingAmount", 0) > 0
    ]
    early_holder_pct = sum(
        b.get("holdingPercentage", 0) for b in early_still_holding
    )

    return {
        "early_buyers_count": len(first_buyers),
        "still_holding_count": len(early_still_holding),
        "early_holder_pct": round(early_holder_pct, 2),
        "risk": "HIGH" if early_holder_pct > 20 else
                "MODERATE" if early_holder_pct > 10 else "LOW",
    }

开发者持仓

创建者钱包的留存比例是一项风险信号：

def check_developer_risk(token_data: dict) -> dict:
    """Check developer wallet holdings and authority.

    Args:
        token_data: Token info from SolanaTracker or Birdeye.

    Returns:
        Developer risk assessment.
    """
    risk = token_data.get("risk", {})
    flags = []

    # Check creator balance (from Birdeye security endpoint)
    creator_balance = token_data.get("creatorBalance", 0)
    if creator_balance > 10:
        flags.append(f"Creator holds {creator_balance:.1f}% of supply")

    # Check mint authority
    if token_data.get("mintAuthority") or token_data.get("ownerAddress"):
        flags.append("Mint authority NOT renounced — supply can increase")

    # Check freeze authority
    if token_data.get("freezeAuthority") or token_data.get("freezeable"):
        flags.append("Freeze authority enabled — tokens can be frozen")

    return {
        "flags": flags,
        "risk_level": "HIGH" if len(flags) >= 2 else
                      "MODERATE" if len(flags) == 1 else "LOW",
    }

狙击手检测

狙击手会在代币创建后的最初几秒/区块内买入：

def analyze_sniper_concentration(first_buyers: list[dict], total_supply: float) -> dict:
    """Analyze sniper impact on holder distribution.

    Args:
        first_buyers: First buyers data from SolanaTracker.
        total_supply: Total token supply.

    Returns:
        Sniper concentration analysis.
    """
    # Snipers typically buy in first 10 seconds
    snipers = first_buyers[:10]  # first N buyers are potential snipers
    sniper_holding = sum(b.get("holdingAmount", 0) for b in snipers)
    sniper_pct = sniper_holding / total_supply * 100 if total_supply > 0 else 0

    return {
        "sniper_count": len(snipers),
        "sniper_holding_pct": round(sniper_pct, 2),
        "sniper_still_holding": sum(1 for s in snipers if s.get("holdingAmount", 0) > 0),
        "risk": "HIGH" if sniper_pct > 15 else
                "MODERATE" if sniper_pct > 5 else "LOW",
    }

完整分析流程

def full_holder_analysis(mint: str) -> dict:
    """Run complete holder analysis for a token.

    Combines RPC, SolanaTracker, and computed metrics.
    """
    # 1. Get supply and top holders via RPC
    supply_result = rpc_call("getTokenSupply", [mint])
    total_supply = int(supply_result["result"]["value"]["amount"])

    holders = get_top_holders(mint)
    amounts = [int(h["amount"]) for h in holders]

    # 2. Compute concentration metrics
    metrics = {
        "total_supply": total_supply,
        "holder_count": len(holders),
        "top_1_pct": top_n_percentage(holders, total_supply, 1),
        "top_5_pct": top_n_percentage(holders, total_supply, 5),
        "top_10_pct": top_n_percentage(holders, total_supply, 10),
        "top_20_pct": top_n_percentage(holders, total_supply, 20),
        "gini": round(gini_coefficient(amounts), 4),
        "hhi": round(hhi(amounts), 1),
        "nakamoto": nakamoto_coefficient(amounts),
    }

    # 3. Risk classification
    t10 = metrics["top_10_pct"]
    if t10 > 80:
        metrics["risk"] = "EXTREME"
    elif t10 > 50:
        metrics["risk"] = "HIGH"
    elif t10 > 30:
        metrics["risk"] = "MODERATE"
    else:
        metrics["risk"] = "LOW"

    return metrics

风险分类汇总

指标	低风险	中等	高	极高
前 10 名占比	<30%	30-50%	50-80%	>80%
基尼系数	<0.7	0.7-0.85	0.85-0.95	>0.95
HHI	<1500	1500-2500	2500-5000	>5000
中本聪系数	>10	5-10	2-4	1
铸造权限	已放弃	—	有效	有效 + 开发者占比高
冻结权限	已禁用	—	已启用	已启用 + 流动性低

已知排除项

计算持有者集中度时，应排除以下地址；它们属于程序/资金池，并非个人持有者：

• DEX 资金池地址（Raydium、Orca、Meteora 资金池）
• 代币程序金库
• 跨链桥托管账户
• 已知销毁地址

KNOWN_PROGRAMS = {
    "5Q544fKrFoe6tsEbD7S8EmxGTJYAKtTVhAW5Q5pge4j1",  # Raydium authority
    "GThUX1Atko4tqhN2NaiTazWSeFWMuiUvfFnyJyUghFMJ",  # Orca authority
    # Add more as needed
}

def filter_real_holders(holders: list[dict]) -> list[dict]:
    """Remove known program/pool accounts from holder list."""
    return [h for h in holders if h.get("address") not in KNOWN_PROGRAMS]

文件

参考资料

• references/concentration_metrics.md — 基尼系数、HHI、中本聪系数的数学公式与推导
• references/insider_patterns.md — 捆绑买入、狙击手和开发者检测方法
• references/data_sources.md — 如何从各 API 数据源获取持有者数据

脚本

• scripts/analyze_holders.py — 完整持有者分析：获取持有者、计算指标、生成风险报告
• scripts/concentration_scanner.py — 扫描多个代币的集中度风险