القائمة
AI-driven DeFi trading signal generation with Kelly-criterion position sizing and multi-layer risk controls
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استنادا إلى تصنيف SOC المهني
| name | ave-trading |
| description | AI-driven DeFi trading signal generation with Kelly-criterion position sizing and multi-layer risk controls |
| version | 1.0.0 |
| author | Alchemist-X |
| tags | ["defi","trading","ai","signals","risk-management"] |
Generates trading signals from AVE monitoring data, sizes positions using quarter-Kelly criterion, and manages the full position lifecycle through a 7-tier review system. Applies hard service-layer risk guards (drawdown halt, exposure caps, per-trade limits) to every decision before execution.
| Capability | Description |
|---|---|
| Signal Generation | Momentum-based heuristic analysis of on-chain price data producing buy/sell direction with confidence scoring |
| Position Sizing | 1/4 Kelly criterion: quarterKelly = (edge * confidence) / (4 * odds) with edge = predictedReturn - riskPremium |
| Risk Premium Computation | Dynamic premium based on contract risk level, tax burden, and liquidity depth |
| Entry Planning | Rank candidates by monthly return, cap batch exposure at 20% of bankroll, limit to top N entries |
| Position Review | 7-tier review cascade evaluating every open position against current market prices |
| Risk Guards | Portfolio-level hard limits enforced at the service layer before any decision reaches execution |
AVE Market Pulse AVE Entry Planner
================ ==================
AvePulseCandidate[] For each candidate:
| 1. estimatePredictedReturn()
| - direction (buy/sell)
Pulse Filters - confidence (0.5 + |change| * 2, cap 0.9)
(vol > $10k, liq > $5k, - predictedReturn = |change| * confidence
no honeypots, tax < 10%) 2. computeRiskPremium()
| - base: 2%
Composite Score Sort - medium risk: +1%
log10(vol) * log10(liq) * risk - high/critical risk: +5%
| - low liquidity (<$50k): +2%
Top N candidates - tax burden: +totalTax/100
| 3. edge = predictedReturn - riskPremium
v 4. calculateAveKelly({ edge, confidence })
+------------------+ 5. Monthly return = edge / holdingPeriod
| Entry Planner | ------+
+------------------+ | AVE Position Review
| | ====================
+------------------+ |
| Position Review | ------+--- composeAveDecisions() ---+
+------------------+ |
applyRiskGuards()
|
TradeDecisionSet
Every open position is evaluated in priority order. The first matching tier determines the action.
| Tier | Basis | Action | Exit % | Confidence |
|---|---|---|---|---|
| 1 | Stop-loss breached | close | 100% | medium |
| 2 | Profit target hit | close | 100% | high |
| 3 | Edge gone negative (< -5%) | close | 100% | medium |
| 4 | Near stop-loss (within 30% of threshold) | reduce | 50% | low |
| 5 | Edge weakening (0% to -5%) | reduce | 50% | low |
| 6 | Edge positive (> +2%) | hold | 0% | medium |
| 7 | Stable hold (edge near zero) | hold | 0% | low |
Tiers 3, 4, 5, and 7 set humanReviewFlag: true for manual oversight.
| Parameter | Default | Env Variable | Description |
|---|---|---|---|
| Drawdown stop | 30% | DRAWDOWN_STOP_PCT | Halt all trading if portfolio drawdown exceeds threshold |
| Per-position stop-loss | 30% | POSITION_STOP_LOSS_PCT | Close position if unrealized loss exceeds threshold |
| Max total exposure | 80% | MAX_TOTAL_EXPOSURE_PCT | Cap total deployed capital as % of bankroll |
| Max per-trade size | 15% | MAX_TRADE_PCT | Cap any single trade as % of bankroll |
| Max open positions | 22 | MAX_POSITIONS | Hard limit on concurrent positions |
| Min trade size | $5 | MIN_TRADE_USD | Floor for trade notional |
| Liquidity cap | 5% of pair TVL | -- | Max trade size relative to pair liquidity |
| Parameter | Default | Description |
|---|---|---|
| Kelly fraction | 1/4 (quarter Kelly) | Conservative sizing to limit variance |
| Base risk premium | 2% | Minimum hurdle subtracted from predicted return |
| Minimum edge | 0.5% | Entries below this edge are skipped |
| Holding period | 1 month | Assumed holding period for monthly return calculation |
| Max new entries per batch | 4 | Limit on new positions opened per cycle |
| Batch cap | 20% of bankroll | Total capital allocated across all new entries in one cycle |
import { planAveEntries } from "services/orchestrator/src/runtime/ave-entry-planner.js";
const plans = planAveEntries(
filteredCandidates,
{
bankrollUsd: 10_000,
existingPositions: ["0x...abc-ethereum"],
},
{
maxNewEntries: 4,
batchCapPct: 0.2,
stopLossPct: 0.3,
minEdge: 0.005,
}
);
// plans: AveEntryPlan[] sorted by monthly return, batch-capped
import { reviewAvePositions } from "services/orchestrator/src/review/ave-position-review.js";
const reviews = reviewAvePositions(
currentPositions,
currentPriceMap, // Map<tokenId, priceUsd>
{
stopLossPct: 0.3,
targetProfitPct: 0.5, // optional
}
);
for (const review of reviews) {
// review.action: "hold" | "reduce" | "close"
// review.basis: "stop-loss-breached" | "profit-target-hit" | ...
// review.decision: TradeDecision (ready for execution)
}
import { runAveDirectPipeline } from "services/orchestrator/src/runtime/ave-direct-runtime.js";
const result = await runAveDirectPipeline(
{
runId: crypto.randomUUID(),
mode: "full",
bankrollUsd: 10_000,
totalEquityUsd: 10_000,
positions: [],
openPositionCount: 0,
},
orchestratorConfig
);
// result.decisionSet: TradeDecisionSet with all decisions
// result.entryPlans: new positions planned
// result.positionReviews: existing position evaluations
{
"tokenAddress": "0x6982508...a011",
"chain": "ethereum",
"tokenId": "0x6982508...a011-ethereum",
"tokenSymbol": "PEPE",
"direction": "buy",
"sizeUsd": 142.50,
"confidence": 0.67,
"predictedReturn": 0.057,
"riskPremium": 0.02,
"edge": 0.037,
"fullKellyPct": 0.02479,
"quarterKellyPct": 0.00620,
"monthlyReturn": 0.037,
"holdingPeriodMonths": 1,
"currentPriceUsd": 0.00001234,
"liquidityUsd": 18500000,
"riskLevel": "low",
"confidenceBucket": "medium-high"
}
{
"run_id": "a1b2c3d4-...",
"runtime": "ave-direct-runtime",
"generated_at_utc": "2026-04-13T12:00:00.000Z",
"bankroll_usd": 10000,
"mode": "full",
"decisions": [
{
"action": "open",
"event_slug": "ethereum",
"market_slug": "0x698...a011-ethereum",
"token_id": "0x698...a011-ethereum",
"token_symbol": "PEPE",
"side": "BUY",
"notional_usd": 142.50,
"order_type": "FOK",
"ai_prob": 0.67,
"market_prob": 0.50,
"edge": 0.037,
"confidence": "medium-high",
"thesis_md": "**PEPE** on ethereum: Price $0.000012, 24h change +8.50%. Direction: BUY with 67.0% confidence. Edge: 3.70%. Quarter Kelly size: $142.50.",
"sources": [
{
"title": "AVE token data for PEPE",
"url": "https://ave.ai/token/0x698...a011-ethereum",
"retrieved_at_utc": "2026-04-13T12:00:00.000Z"
}
],
"full_kelly_pct": 0.02479,
"quarter_kelly_pct": 0.00620,
"liquidity_cap_usd": 925000,
"stop_loss_pct": 0.3,
"resolution_track_required": false
}
],
"artifacts": []
}
The trading skill consumes every monitoring output (price, volume, liquidity, risk assessment) and transforms it through a quantitative pipeline: momentum estimation, dynamic risk premium, Kelly sizing, 7-tier position review, decision composition with deduplication, and portfolio-level risk guards. Every TradeDecision carries a full audit trail including thesis markdown, source URLs, and Kelly fractions.