Event-driven backtesting with bar-by-bar execution, complex order types, multiple analyzers, and custom indicators
中文简介正在准备中。当前显示原文说明。
PumpFun bonding curve math, graduation mechanics, instruction parsing, and PumpSwap migration
中文简介正在准备中。当前显示原文说明。
实测评分 未实测
查看安装方法安装前可以查看交给 AI 代理的指令内容。
PumpFun is the dominant Solana token launchpad. Understanding its bonding curve math, graduation process, and instruction formats is essential for analyzing new token launches, building trading strategies around graduation events, and parsing on-chain PumpFun activity.
PumpFun uses a virtual constant-product (CPMM) bonding curve:
k = virtualSolReserves × virtualTokenReserves
| Parameter | Value |
|---|---|
| Initial Virtual SOL | 30 SOL (30,000,000,000 lamports) |
| Initial Virtual Tokens | ~1.073B tokens (1,073,000,000,000,000 raw, 6 decimals) |
| Token Total Supply | 1B tokens (1,000,000,000,000,000 raw) |
| Real Token Reserves | ~793M tokens (793,000,000,000,000 raw) |
| Real SOL Reserves | 0 (no real SOL at launch) |
| Fee | 1% (applied externally by the program) |
Virtual vs Real: Virtual reserves define the curve shape. Real reserves track actual withdrawable funds. The difference (1.073B - 793M = 280M virtual tokens) shapes the initial price but can never be withdrawn.
price_sol_per_token = virtual_sol_reserves / virtual_token_reserves
# In human-readable units:
price = (virtual_sol / 1e9) / (virtual_token / 1e6)
# At genesis: 30 / 1,073,000,000 ≈ 2.796e-8 SOL/token
# At graduation: ~4.1e-7 SOL/token (~14.7x from launch)
def buy_tokens(v_sol: int, v_tok: int, real_tok: int, sol_in: int) -> int:
"""Calculate tokens received for a given SOL input.
Args:
v_sol: Virtual SOL reserves (lamports).
v_tok: Virtual token reserves (raw).
real_tok: Real token reserves (raw).
sol_in: SOL to spend (lamports, BEFORE 1% fee).
Returns:
Tokens received (raw units).
"""
k = v_sol * v_tok
new_v_sol = v_sol + sol_in
new_v_tok = k // new_v_sol + 1 # +1 matches on-chain rounding
tokens_out = v_tok - new_v_tok
return min(tokens_out, real_tok)
def sell_tokens(v_sol: int, v_tok: int, real_sol: int, tokens_in: int) -> int:
"""Calculate SOL received for selling tokens.
Args:
v_sol: Virtual SOL reserves (lamports).
v_tok: Virtual token reserves (raw).
real_sol: Real SOL reserves (lamports).
tokens_in: Tokens to sell (raw units).
Returns:
SOL received (lamports, BEFORE 1% fee).
"""
k = v_sol * v_tok
new_v_tok = v_tok + tokens_in
new_v_sol = k // new_v_tok
sol_out = v_sol - new_v_sol - 1 # -1 matches on-chain floor rounding
return min(sol_out, real_sol)
def buy_cost(v_sol: int, v_tok: int, tokens_wanted: int) -> int:
"""Calculate SOL needed to buy exact token amount.
Returns:
SOL cost in lamports (before fee). Returns max int if impossible.
"""
if tokens_wanted >= v_tok:
return 2**64 - 1 # impossible
k = v_sol * v_tok
new_v_tok = v_tok - tokens_wanted
new_v_sol = k // new_v_tok + 1
return new_v_sol - v_sol
The 1% fee is not part of the curve math. It's applied externally:
# Buying: fee deducted from SOL input before curve
actual_sol_to_curve = sol_input * 0.99
# Selling: fee deducted from SOL output after curve
actual_sol_received = sol_from_curve * 0.99
# Roundtrip minimum cost: ~2% from fees alone, plus price impact
market_cap_sol = (token_total_supply * virtual_sol_reserves) / virtual_token_reserves
Graduation occurs when realSolReserves reaches ~85 SOL (~$12K-14K depending on SOL price). Only ~1.4% of PumpFun tokens ever graduate.
complete flag set to true on bonding curve accountCompleteEvent emitted (discriminator 5f72619cd42e9808)GRADUATION_THRESHOLD = 85_000_000_000 # 85 SOL in lamports
fill_pct = (real_sol_reserves / GRADUATION_THRESHOLD) * 100.0
pAMMBay6oceH9fJKBRHGP5D4bD4sWpmSwMn52FMfXEA) — native AMM, no migration fee675kPX9MHTjS2zt1qfr1NYHuzeLXfQM9H24wFSUt1Mp8) — 6 SOL feePumpSwap is a constant-product AMM with 1% fee (same as bonding curve). Key differences:
| Program/Account | Address |
|---|---|
| PumpFun Program | 6EF8rrecthR5Dkzon8Nwu78hRvfCKubJ14M5uBEwF6P |
| PumpSwap Program | pAMMBay6oceH9fJKBRHGP5D4bD4sWpmSwMn52FMfXEA |
| Fee Program | pfeeUxB6jkeY1Hxd7CsFCAjcbHA9rWtchMGdZ6VojVZ |
| Global Account | 4wTV1YmiEkRvAtNtsSGPtUrqRYQMe5SKy2uB4Jjaxnjf |
| Fee Recipient | 62qc2CNXwrYqQScmEdiZFFAnJR262PxWEuNQtxfafNgV |
| Event Authority | Ce6TQqeHC9p8KetsN6JsjHK7UTZk7nasjjnr7XxXp9F1 |
Events are Anchor-style: sha256("event:<EventName>")[0..8]
| Event | Discriminator (hex) |
|---|---|
| CreateEvent | 1b72a94ddeeb6376 |
| TradeEvent | bddb7fd34ee661ee |
| CompleteEvent | 5f72619cd42e9808 |
mint: pubkey 32 bytes
solAmount: u64 8 bytes
tokenAmount: u64 8 bytes
isBuy: bool 1 byte
user: pubkey 32 bytes
timestamp: i64 8 bytes
virtualSolReserves: u64 8 bytes
virtualTokenReserves: u64 8 bytes
realSolReserves: u64 8 bytes
realTokenReserves: u64 8 bytes
Critical: Events are in CPI inner instructions. Search for discriminators anywhere in instruction data, not just at offset 0.
Offset 0: discriminator 8 bytes
Offset 8: virtualTokenReserves u64
Offset 16: virtualSolReserves u64
Offset 24: realTokenReserves u64
Offset 32: realSolReserves u64
Offset 40: tokenTotalSupply u64
Offset 48: complete bool (1 byte)
Offset 49: creator pubkey (32 bytes)
| PDA | Seeds |
|---|---|
| Bonding Curve | ["bonding-curve", mint] |
| Bonding Curve V2 | ["bonding-curve-v2", mint] |
| Creator Vault | ["creator-vault", creator] |
| Instruction | Hex | Notes |
|---|---|---|
| buy_exact_sol_in (V2) | 38fc74089edfcd5f | Current production buy |
| sell (V2) | 33e685a4017f83ad | Current production sell |
| buy (V1/legacy) | 66063d1201daebea | Legacy, still seen occasionally |
| create | 181ec828051c0777 | Token creation |
[0..8]: discriminator
[8..16]: spendable_sol_in u64 LE (total SOL budget, fees deducted internally)
[16..24]: min_tokens_out u64 LE (slippage floor)
[0..8]: discriminator
[8..16]: amount_tokens u64 LE (tokens to sell, raw)
[16..24]: min_sol_output u64 LE (minimum SOL out, lamports)
def price_impact(v_sol: int, v_tok: int, sol_in: int) -> float:
"""Calculate price impact for a buy as a percentage."""
spot = v_sol / v_tok
tokens = buy_tokens(v_sol, v_tok, v_tok, sol_in)
if tokens == 0:
return float('inf')
exec_price = sol_in / tokens
return (exec_price / spot - 1) * 100
# Example: 1 SOL buy at genesis
# impact = price_impact(30_000_000_000, 1_073_000_000_000_000, 1_000_000_000)
# ≈ 3.3% price impact
references/bonding_curve_math.md — Complete mathematical derivations with worked examplesreferences/graduation_process.md — Graduation threshold, migration, PumpSwap mechanicsreferences/instruction_reference.md — Full instruction and event layouts for parsingscripts/curve_calculator.py — Interactive bonding curve calculator: price, impact, fill %scripts/parse_events.py — Parse PumpFun events from transaction data还没有评价。欢迎分享你的使用感受。
无需登录即可发表。欢迎分享使用感受、提问,或说明在哪些环境下无法运行。
还没有评论。来写第一条吧。
Event-driven backtesting with bar-by-bar execution, complex order types, multiple analyzers, and custom indicators
中文简介正在准备中。当前显示原文说明。
Solana token market data via Birdeye — prices, OHLCV, trades, token metadata, security checks, and trader activity
中文简介正在准备中。当前显示原文说明。
Broad crypto market data from CoinGecko covering 13,000+ tokens. Global market stats, historical price data going back years, exchange volumes, trending tokens, and category filters. Best for macro analysis and long-term historical data.
中文简介正在准备中。当前显示原文说明。
Cointegration testing for pairs trading using Engle-Granger, Johansen, and rolling stability analysis
中文简介正在准备中。当前显示原文说明。
Wallet evaluation, monitoring, and copy-trade strategy design for Solana DEX trading
中文简介正在准备中。当前显示原文说明。
Cross-asset correlation analysis including rolling correlation, hierarchical clustering, tail dependence, and regime-dependent correlation
中文简介正在准备中。当前显示原文说明。