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https://github.com/theodore-song/polymarket-analyst.git
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Make historical risk gates adaptive
This commit is contained in:
Theodore Song
@@ -15,18 +15,19 @@ https://polymarket-site-eta.vercel.app/personal.html
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The site fetches live Polymarket markets, generates agent suggestions, lets you
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run frequent paper cycles, and syncs the shared arena state through Neon or
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Vercel Blob. Build 46 also installs an offline app shell and caches timestamped
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Vercel Blob. Build 47 also installs an offline app shell and caches timestamped
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market snapshots. During an outage, cycles continue locally; cached entries are
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allowed for 90 minutes, older snapshots become mark-only, and all cached data
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expires after 24 hours.
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Each agent learns bounded weights from its own v34+ trade outcomes across signal
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type, setup quality, category, side, and entry-price band. The learner shrinks
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small samples toward neutral, caps sizing changes to 0.68x-1.30x, and reserves
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type, setup quality, category, side, entry-price band, and time to resolution.
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The learner shrinks small samples toward neutral, caps sizing changes to
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0.68x-1.30x, and reserves
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15% of candidates for deterministic exploration so a stale regime cannot become
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permanent.
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Strategy 43 treats each binary stake as capable of falling to zero even when the
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Strategy 44 treats each binary stake as capable of falling to zero even when the
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18% stop cannot fill. New core positions are capped at 2.5%-4% of equity and
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aggressive positions at 3%-5%, with lower limits for near-term, extreme-price,
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reversal, and fast-moving setups. Oversized positions inherited from older
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@@ -34,10 +35,11 @@ engines are reduced to the same loss budget during live marking.
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The two-agent overlap guard counts only positions worth at least 1.25% of an
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agent's equity, so tiny profit-lock runners do not block a new material trade.
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A separate walk-forward ledger records each trade-ready signal before its future
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A separate walk-forward ledger records every confirmed signal before its future
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price is known, grades it at least 24 hours later, and combines that broad market
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calibration with each agent's personal outcomes. This expands the learning sample
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without backfilling future information into old decisions. The 24-hour horizon
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without forcing observation-only signals into portfolios or backfilling future
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information into old decisions. The 24-hour horizon
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matches the engine's minimum ordinary holding policy; stops and profit locks still
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act immediately from fresh prices.
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@@ -63,7 +65,7 @@ negative in all three chronological segments. Reversals averaged -3.69%, with a
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market-clustered 90% interval entirely below zero. Crypto and Sports were also
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negative but covered only three and five markets. The 24-hour cohort improved to
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-0.82% row mean and +1.31% market mean, with no rule robustly negative across all
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segments. Strategy 43 therefore disables reversal entries, retains their signals
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segments. Strategy 44 therefore disables reversal entries, retains their signals
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for paper grading, and evaluates adaptation at 24 hours. It does not promote any
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rule because no positive cohort passed the same robustness checks.
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@@ -73,23 +75,23 @@ segment and averaged -4.13%. Sports trends were negative in train and test and
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averaged -3.53% at 72 hours. Politics trends were the sole cohort with positive
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row-level returns in all three 72-hour segments, but its market-cluster interval
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still crossed zero; that supports a longer hold test, not a larger entry bet.
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Strategy 43 gives Politics trend positions that 72-hour observation window before
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Strategy 44 gives Politics trend positions that 72-hour observation window before
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ordinary signal exits. Stops, profit locks, settlement handling, and risk-budget
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reductions remain immediate.
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Strategy 43 also subtracts a half-cent round-trip cost when grading each live
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Strategy 44 also subtracts a half-cent round-trip cost when grading each live
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walk-forward signal. Confidence uses the largest independent matching bucket,
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not the sum of five overlapping feature buckets, and evidence from older engine
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versions is down-weighted. This prevents a handful of duplicated observations
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from authorizing larger positions or hiding a modest negative regime.
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Strategy 43 adds uncertainty-aware promotion and demotion. A matching setup must
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Strategy 44 adds uncertainty-aware promotion and demotion. A matching setup must
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accumulate at least eight effective observations and agree across at least two
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feature views before repeatable positive evidence can increase size or repeatable
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negative evidence can block a new entry. Mixed evidence stays close to neutral
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instead of being mistaken for an edge.
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Build 46 enforces the documented offline boundary end to end. Cached snapshots
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Build 47 enforces the documented offline boundary end to end. Cached snapshots
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under 90 minutes old may continue paper execution. Older snapshots remain usable
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for valuation and chart snapshots for up to 24 hours, but cannot trigger entries,
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stop-losses, gain-stops, risk rebalances, settlements, or policy exits. Network
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@@ -102,12 +104,12 @@ adaptive baselines, pending signal grades, and trade evidence remain in one stra
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lineage until the actual entry, sizing, or exit logic changes. Legacy build 40 and 41
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records are migrated into the same strategy lineage without losing evidence.
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Build 46 independently refreshes markets for matured pending signals that have
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Build 47 independently refreshes markets for matured pending signals that have
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left the current top-500 activity scan. Unavailable markets remain queued for a
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bounded retry window. This prevents activity-rank survivorship from deciding
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which wins and losses reach the adaptive calibration ledger.
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Strategy 43 coordinates high-risk exploration globally. Crypto, near-term,
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Strategy 44 coordinates high-risk exploration globally. Crypto, near-term,
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extreme-price, legacy reversal, and other gap-prone positions may be held materially by
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only one agent, while ordinary independently confirmed markets retain the
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two-agent cap. A historically blocked Sports trend can enter the exploration lane
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@@ -124,18 +126,21 @@ cohort robust. Environment variables beginning with
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`SETTLEMENT_` control its market count, concurrency, horizons, and cost. Set
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`SETTLEMENT_SUMMARY=1` for the compact report.
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The first event-clustered run loaded 498 of the 500 highest-volume resolved
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markets. No side, price band, category, or 1-90 day holding rule passed the
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required train/test confidence checks. In particular, older YES/underdog gains
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The expanded event-clustered run loaded history for 498 of the 500 highest-volume
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resolved markets with no fetch failures. No side, price band, category, trend,
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or 1-90 day holding rule passed the required train/test confidence checks. In
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particular, older YES/underdog gains
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reversed in the recent test segment. The engine therefore does not install a
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static settlement-direction boost from this audit.
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The latest 200-resolved-market audit loaded history for 199 markets with no
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fetch failures. No positive rule passed the robustness gate. Buying NO with
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7-14 days remaining was robustly negative in pooled, train, test, and
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event-clustered results: the 14-day cohort averaged -37.33% by observation and
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-46.84% by event. Strategy 43 therefore blocks new NO entries with 21 days or
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less to resolution while continuing to record their signals for future evidence.
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The earlier 200-resolved-market audit found short-dated NO entries strongly
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negative, but the 500-market rerun did not reproduce that loss in its newer test
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segment. Strategy 44 therefore treats the result as a provisional prior instead
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of a permanent ban: NO entries with 21 days or less remain observation-only until
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the recent walk-forward calibration promotes their matching side and duration
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cohorts. Exact numeric-range contracts are excluded from new entries because a
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settlement jump can pass directly through an 18% stop; the live audit found that
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this failure mode caused the largest latest-day loss.
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Paper accounts created with a password are also saved through the backend, so a
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user can log in from another device and see the same paper portfolio, activity,
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+56
-23
@@ -341,7 +341,7 @@ footer{margin-top:34px;padding-top:22px;border-top:1px solid var(--border);color
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<nav class="topnav">
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<div class="brand">
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<div class="logo">🏆</div>
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<div><div class="brand-name">Polymarket Arena</div><div class="brand-sub">10 agents · 5 core + 5 aggressive</div><div class="build-badge">Adaptive strategy 43 · build 46</div></div>
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<div><div class="brand-name">Polymarket Arena</div><div class="brand-sub">10 agents · 5 core + 5 aggressive</div><div class="build-badge">Adaptive strategy 44 · build 47</div></div>
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</div>
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<div class="tabs" id="tabs">
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<button class="tab" data-tab="overview">Overview</button>
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@@ -363,7 +363,7 @@ footer{margin-top:34px;padding-top:22px;border-top:1px solid var(--border);color
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<div class="personal-banner" id="personalBanner">
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<b>Personal research mode.</b> This copy is for your own analysis, paper tracking, and manual trade research only. It does not pool money, onboard investors, custody funds, bypass eligibility rules, or place orders without your manual approval.
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</div>
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<div class="live-build-banner"><b>Build 46 active:</b> adaptation now grades signals after the same 24-hour minimum used by ordinary trade policy. Reversal and short-dated NO entries are disabled after independent price-history and settlement audits found repeatable net losses; Trend Endurance replaces the reversal agent. This remains paper trading; profits are not guaranteed.</div>
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<div class="live-build-banner"><b>Build 47 active:</b> exact-range contracts are excluded from agent entries because their binary settlement jumps can bypass stops. Short-dated NO signals remain observation-only until recent walk-forward evidence earns promotion, while all confirmed signals now train the adaptive ledger even when no portfolio buys them. This remains paper trading; profits are not guaranteed.</div>
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<!-- ============ OVERVIEW ============ -->
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<section class="tabpanel" data-tab="overview">
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@@ -745,7 +745,7 @@ footer{margin-top:34px;padding-top:22px;border-top:1px solid var(--border);color
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</section>
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<footer>
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Build 46 · Adaptive strategy 43 · Paper trading only · Live prices from Polymarket's public Gamma API · Not financial advice ·
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Build 47 · Adaptive strategy 44 · Paper trading only · Live prices from Polymarket's public Gamma API · Not financial advice ·
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<a class="market-link" href="https://github.com/theodore-song/polymarket-analyst" target="_blank" rel="noopener">Source on GitHub</a>
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</footer>
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</div>
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@@ -774,9 +774,9 @@ const POLITICS_TREND_MIN_HOLD_HOURS = 72;
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const EXIT_CONFIRM_HOURS = 6;
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const AGENTS_KEY = "pma_agents_v2";
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const SUG_KEY = "pma_suggestions_v5";
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const BUILD_VERSION = 46;
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const SUGGESTION_ENGINE_VERSION = 43;
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const PREVIOUS_STRATEGY_VERSION = 42;
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const BUILD_VERSION = 47;
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const SUGGESTION_ENGINE_VERSION = 44;
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const PREVIOUS_STRATEGY_VERSION = 43;
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const LEGACY_BUILD_STRATEGY_LINEAGE = Object.freeze({40:40,41:40});
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function normalizedStrategyVersion(value){
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const version=Number(value||0);
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@@ -1172,6 +1172,10 @@ function selectMarketsForAnalysis(markets,limit=MARKET_ANALYSIS_LIMIT){
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function timingSignal(d){if(d==null)return 0.4;if(d<1)return 0.1;if(d<=3)return 0.5;if(d<=90)return 1.0-(d-3)/87.0*0.4;return 0.35;}
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function fastSettlementRisk(m){
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const text=`${m&&m.question||""} ${m&&m.event||""}`.toLowerCase();
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const numericRange=/\b\d+(?:\.\d+)?\s*(?:%|percent)?\s*(?:-|–|—|to)\s*\d+(?:\.\d+)?\s*(?:%|percent|votes?|points?|seats?|bps|basis points?|tweets?|posts?|goals?)(?![a-z])/;
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const currencyRange=/[$€£]\d+(?:\.\d+)?\s*(?:-|–|—|to)\s*[$€£]?\d+(?:\.\d+)?/;
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const betweenRange=/\bbetween\s+[$€£]?\d+(?:\.\d+)?\s*(?:%|percent)?\s+(?:and|to)\s+[$€£]?\d+(?:\.\d+)?/;
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if(numericRange.test(text)||currencyRange.test(text)||betweenRange.test(text))return true;
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if(/\bexact score\b|\bscore:\s*\d|\bposts? \d+-\d+|\bnumber of (tweets|posts)\b/.test(text))return true;
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if(/\bvs\.?\b/.test(text))return true;
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if((m&&m.category)==="Sports"){
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@@ -1230,12 +1234,13 @@ function analyzeMarket(m,realWorldSignals={}){
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&&absNet>=MIN_LIQUIDITY_EDGE&&signal.confidence>=0.68&&evidence.score>=0.50&&m.spread<=0.018&&m.liquidity>=5000;
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const trendTradeReady=!strictTradeReady&&!catalystTradeReady&&!reversalTradeReady&&!liquidityTradeReady&&commonReady&&signal.type==="trend"
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&&absNet>=Math.max(MIN_TREND_EDGE,policy.minEdge)&&signal.confidence>=0.60&&evidence.score>=policy.minEvidence;
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const tradeReady=strictTradeReady||catalystTradeReady||reversalTradeReady||liquidityTradeReady||trendTradeReady;
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const quality=strictTradeReady?"confirmed":(catalystTradeReady?"catalyst":(reversalTradeReady?"reversal":(liquidityTradeReady?"liquid-trend":(trendTradeReady?"trend":"watch"))));
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const tradeReady=signal.type!=="reversal"&&(strictTradeReady||catalystTradeReady||liquidityTradeReady||trendTradeReady);
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const quality=signal.type==="reversal"?"reversal":(strictTradeReady?"confirmed":(catalystTradeReady?"catalyst":(liquidityTradeReady?"liquid-trend":(trendTradeReady?"trend":"watch"))));
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const side=signal.side||((Number(m.price_change_1d||0)>=0)?"YES":"NO");
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const entry=side==="YES"?p:m.no_price;
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let rationale;
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if(strictTradeReady){rationale=`Confirmed setup: ${side} has ${Math.round(signal.strength*100)} signal strength across independent time windows and a ${(absNet*100).toFixed(1)}c signal margin after friction and category uncertainty.`;}
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if(signal.type==="reversal"){rationale=`Observation only: the hourly move opposes the one-day direction, but independent audits found this reversal rule lost after costs. The signal will be graded without risking portfolio cash.`;}
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else if(strictTradeReady){rationale=`Confirmed setup: ${side} has ${Math.round(signal.strength*100)} signal strength across independent time windows and a ${(absNet*100).toFixed(1)}c signal margin after friction and category uncertainty.`;}
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else if(catalystTradeReady){rationale=`Catalyst-confirmed setup: ${side} price action agrees across the required windows, recent outside coverage exists, and ${(absNet*100).toFixed(1)}c of estimated movement remains after friction. News coverage confirms activity, not direction.`;}
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else if(reversalTradeReady){rationale=`Confirmed reversal: the one-day move is reversing in the hourly window with adequate liquidity and a ${(absNet*100).toFixed(1)}c post-friction signal margin.`;}
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else if(liquidityTradeReady){rationale=`Liquid trend: ${side} is aligned across one-day and one-week windows in a tight, deep market with a ${(absNet*100).toFixed(1)}c post-friction signal margin.`;}
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@@ -1613,9 +1618,15 @@ function recentReturnDelta(p){
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return (snaps[snaps.length-1].return_pct||0)-(snaps[0].return_pct||0);
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}
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function entryBand(price){const p=Number(price||0);return p<0.25?"longshot":p<0.55?"mid":p<0.78?"favorite":"heavy-favorite";}
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function resolutionBand(days){
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const value=Number(days);
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if(!Number.isFinite(value))return "unknown";
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return value<=21?"short":(value<=90?"medium":"long");
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}
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function learningFeatures(trade){
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return [`signal:${trade.signal_type||"unknown"}`,`quality:${trade.quality||"unknown"}`,
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`category:${trade.category||"Other"}`,`side:${trade.side||"unknown"}`,`price:${entryBand(trade.entry_price)}`];
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`category:${trade.category||"Other"}`,`side:${trade.side||"unknown"}`,`price:${entryBand(trade.entry_price)}`,
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`duration:${resolutionBand(trade.days_to_resolution)}`];
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}
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function summarizeLearningBucket(bucket,shrinkage){
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const weight=Math.max(0,Number(bucket&&bucket.weight||0));
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@@ -1662,10 +1673,12 @@ function updateSignalLedger(st,markets,suggestions){
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else ledger.expired_ungraded=Number(ledger.expired_ungraded||0)+1;
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}
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const existing=new Set(stillPending.map(x=>x.key)),bucket=Math.floor(now/(6*3600000));
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for(const s of (suggestions||[]).filter(x=>x.trade_ready)){
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const observable=(suggestions||[]).filter(x=>x.trade_ready||(!x.jump_risk&&["trend","reversal"].includes(x.signal_type)&&Number(x.signal_confidence||0)>=0.56));
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for(const s of observable){
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const key=`${s.market_id}:${s.side}:${bucket}`;if(existing.has(key))continue;
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existing.add(key);stillPending.push({key,market_id:String(s.market_id),observed_at:nowIso(),side:s.side,entry_price:Number(s.entry_price),
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signal_type:s.signal_type||"unknown",quality:s.quality||"unknown",category:s.category||"Other",conviction:Number(s.conviction||0),
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days_to_resolution:s.days_to_resolution,trade_ready_at_observation:Boolean(s.trade_ready),
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strategy_version:SUGGESTION_ENGINE_VERSION,build_version:BUILD_VERSION});
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}
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ledger.pending=stillPending.slice(-SIGNAL_LEDGER_PENDING_LIMIT);
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@@ -1760,36 +1773,45 @@ function stableExploration(agentId,marketId){
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function historicalOpportunityPrior(s){
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const rows=[];
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if((s.signal_type||"")==="reversal")rows.push({feature:"reversal",score:-0.0369,samples:207,blocked:true,hardBlocked:true});
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if((s.side||"")==="NO"&&Number(s.days_to_resolution)<=21)rows.push({feature:"short-no",score:-0.3733,samples:64,blocked:true,hardBlocked:true});
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if((s.side||"")==="NO"&&Number(s.days_to_resolution)<=21)rows.push({feature:"short-no",score:-0.3733,samples:64,blocked:true,requiresPromotion:true});
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if((s.signal_type||"")==="trend"&&(s.category||"Other")==="Sports")rows.push({feature:"sports-trend",score:-0.0353,samples:162,blocked:true});
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if((s.category||"Other")==="Crypto")rows.push({feature:"crypto",score:-0.0344,samples:140,blocked:false});
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if(entryBand(s.entry_price)==="longshot")rows.push({feature:"longshot",score:-0.0327,samples:277,blocked:false});
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if((s.side||"")==="YES")rows.push({feature:"yes-side",score:-0.0190,samples:954,blocked:false});
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if(!rows.length)return {score:0,confidence:0,multiplier:1,blocked:false,features:[]};
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if(!rows.length)return {score:0,confidence:0,multiplier:1,blocked:false,hardBlocked:false,requiresPromotion:false,features:[]};
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const score=rows.reduce((sum,row)=>sum+row.score,0)/rows.length;
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const samples=Math.max(...rows.map(row=>row.samples)),confidence=samples/(samples+200);
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return {score:+score.toFixed(4),confidence:+confidence.toFixed(3),
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multiplier:+clamp(1+score*confidence*2.5,0.82,1).toFixed(3),blocked:rows.some(row=>row.blocked),
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hardBlocked:rows.some(row=>row.hardBlocked),features:rows.map(row=>row.feature)};
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hardBlocked:rows.some(row=>row.hardBlocked),requiresPromotion:rows.some(row=>row.requiresPromotion),features:rows.map(row=>row.feature)};
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}
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function learnedOpportunity(cfg,p,s,profile=null,calibration=null){
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const model=profile||buildAdaptiveProfile(p),features=learningFeatures(s),rows=features.map(k=>model.buckets[k]).filter(Boolean);
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const independentWeight=rows.length?Math.max(...rows.map(r=>Number(r.weight||0))):0;
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const score=rows.length?rows.reduce((sum,r)=>sum+r.score,0)/rows.length:0;
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const confidence=independentWeight/(independentWeight+12),exploration=stableExploration(cfg.id,s.market_id);
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const market=calibratedOpportunity(s,calibration||{samples:0,buckets:{}});
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const calibrationModel=calibration||{samples:0,buckets:{}},market=calibratedOpportunity(s,calibrationModel);
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const historical=historicalOpportunityPrior(s);
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const historicalProofMet=!historical.requiresPromotion||["side:NO","duration:short"].every(key=>{
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const row=calibrationModel.buckets&&calibrationModel.buckets[key];
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return Number(row&&row.weight||0)>=8&&Number(row&&row.lower_bound||0)>0.003;
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});
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const positiveRows=rows.filter(r=>Number(r.weight||0)>=6&&Number(r.lower_bound||0)>0.005);
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const negativeRows=rows.filter(r=>Number(r.weight||0)>=6&&Number(r.upper_bound||0)<-0.01);
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const personalPromoted=positiveRows.length>=2&&negativeRows.length===0;
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const personalBlocked=negativeRows.length>=2&&positiveRows.length===0;
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const personalEvidence=personalPromoted?positiveRows.reduce((sum,r)=>sum+Number(r.lower_bound||0),0)/positiveRows.length
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:(personalBlocked?negativeRows.reduce((sum,r)=>sum+Number(r.upper_bound||0),0)/negativeRows.length:score*0.10);
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const blockedBy=historical.blocked?"historical":(personalBlocked?"personal":(!market.allowed?"walk-forward":null));
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const blocked=Boolean(blockedBy)&&(historical.hardBlocked||!exploration);
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let blockedBy=null,blocked=false;
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if(historical.hardBlocked){blockedBy="historical";blocked=true;}
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else if(historical.requiresPromotion&&!historicalProofMet){blockedBy="historical";blocked=true;}
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else if(historical.blocked&&!historical.requiresPromotion&&!exploration){blockedBy="historical";blocked=true;}
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else if(personalBlocked&&!exploration){blockedBy="personal";blocked=true;}
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else if(!market.allowed&&!exploration){blockedBy="walk-forward";blocked=true;}
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return {score:+score.toFixed(4),confidence:+confidence.toFixed(3),market_score:market.score,market_confidence:market.confidence,
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personal_state:personalPromoted?"promoted":(personalBlocked?"demoted":"observing"),market_state:market.state,
|
||||
historical_score:historical.score,historical_confidence:historical.confidence,historical_features:historical.features,
|
||||
historical_requires_promotion:Boolean(historical.requiresPromotion),historical_proof_met:Boolean(historicalProofMet),
|
||||
multiplier:+clamp((1+personalEvidence*2.4)*market.multiplier*historical.multiplier,0.65,1.30).toFixed(3),
|
||||
exploration,allowed:!blocked,blocked_by:blocked?blockedBy:null,features};
|
||||
}
|
||||
@@ -2231,6 +2253,7 @@ function openPositions(p,cfg,rankedSugs,focus,decision,avoidMarketIds,peerStats=
|
||||
learning_state:learning.personal_state,market_learning_state:learning.market_state,
|
||||
historical_prior_score:learning.historical_score,historical_prior_confidence:learning.historical_confidence,
|
||||
historical_prior_features:learning.historical_features,learning_block_reason:learning.blocked_by,
|
||||
historical_requires_promotion:learning.historical_requires_promotion,
|
||||
learning_multiplier:learning.multiplier,learning_exploration:learning.exploration,learning_allowed:learning.allowed});
|
||||
}).filter(s=>{
|
||||
if(!s.learning_allowed)return reject(s.learning_block_reason==="historical"?"historical_prior":"learning");
|
||||
@@ -2291,6 +2314,7 @@ function openPositions(p,cfg,rankedSugs,focus,decision,avoidMarketIds,peerStats=
|
||||
learning_score:s.learning_score,learning_confidence:s.learning_confidence,market_learning_score:s.market_learning_score,market_learning_confidence:s.market_learning_confidence,
|
||||
learning_state:s.learning_state,market_learning_state:s.market_learning_state,
|
||||
historical_prior_score:s.historical_prior_score,historical_prior_confidence:s.historical_prior_confidence,historical_prior_features:s.historical_prior_features,
|
||||
historical_requires_promotion:Boolean(s.historical_requires_promotion),
|
||||
learning_multiplier:s.learning_multiplier,learning_exploration:s.learning_exploration,
|
||||
risk_budget_pct:+(riskBudgetPct*100).toFixed(2),
|
||||
peak_price:+entry.toFixed(4),gain_stops:{},stop_losses:{}});
|
||||
@@ -2677,7 +2701,7 @@ function decisionSummary(p){
|
||||
const blockerRows=Object.entries(d.rejectionCounts||{}).filter(([,count])=>count>0).sort((a,b)=>b[1]-a[1]);
|
||||
const blockers=blockerRows.length?` Blocks: ${blockerRows.slice(0,4).map(([key,count])=>`${blockerLabels[key]||key} ${count}`).join(", ")}.`:"";
|
||||
const learning=d.learning?` Learning: ${d.learning.samples} completed trades retained with older strategies down-weighted, ${(d.learning.global_score*100).toFixed(2)}% shrunk expectancy; ${d.learning.current_samples||0} completed under adaptive strategy ${SUGGESTION_ENGINE_VERSION}${d.learning.best?`; strongest ${d.learning.best.feature.replace(":"," ")}`:""}${d.learning.worst?`; weakest ${d.learning.worst.feature.replace(":"," ")}`:""}.`:"";
|
||||
const calibration=d.marketLearning?` Walk-forward calibration: ${d.marketLearning.samples||0} net-of-cost signals graded after ${SIGNAL_EVAL_HOURS} hours (${d.marketLearning.current_samples||0} under adaptive strategy ${SUGGESTION_ENGINE_VERSION}), ${d.marketLearning.pending||0} awaiting a future price${d.marketLearning.expired_ungraded?`, ${d.marketLearning.expired_ungraded} expired ungraded`:""}; ${d.marketLearning.promoted_buckets||0} feature cohorts promoted and ${d.marketLearning.demoted_buckets||0} demoted. Matured markets are repriced even after leaving the active scan. Confidence counts independent outcomes once and uncertainty gates sizing. Historical prior: reversal and NO entries with 21 days or less are disabled; sports trends require the fixed exploration lane; crypto, longshots, and YES entries are sized down. Politics trends receive 72 hours before ordinary signal exits.`:"";
|
||||
const calibration=d.marketLearning?` Walk-forward calibration: ${d.marketLearning.samples||0} net-of-cost signals graded after ${SIGNAL_EVAL_HOURS} hours (${d.marketLearning.current_samples||0} under adaptive strategy ${SUGGESTION_ENGINE_VERSION}), ${d.marketLearning.pending||0} awaiting a future price${d.marketLearning.expired_ungraded?`, ${d.marketLearning.expired_ungraded} expired ungraded`:""}; ${d.marketLearning.promoted_buckets||0} feature cohorts promoted and ${d.marketLearning.demoted_buckets||0} demoted. Matured markets are repriced even after leaving the active scan, and confirmed observation-only signals also train the ledger. Confidence counts independent outcomes once and uncertainty gates sizing. Historical prior: reversal remains disabled; short-dated NO requires recent promotion; sports trends require the fixed exploration lane; exact-range contracts are excluded; crypto, longshots, and YES entries are sized down. Politics trends receive 72 hours before ordinary signal exits.`:"";
|
||||
return `${d.mode} mode: ${d.reason}${emotion} Limits now: ${d.maxNew} new trade${d.maxNew===1?"":"s"}, max ${(d.maxFrac*100).toFixed(1)}% per position${d.minConv?`, conviction ${d.minConv}+`:""}.${learning}${calibration}${exposure}${allocation}${candidates}${blockers}`;
|
||||
}
|
||||
function renderAgentBrief(cfg,p,st){
|
||||
@@ -4271,7 +4295,7 @@ window.PMA_ENGINE_DIAGNOSTICS=Object.freeze({
|
||||
staleCacheIsMarkOnly:true,strategyEvidenceSurvivesBuilds:true,signalEvaluationHours:SIGNAL_EVAL_HOURS,signalRetryHours:SIGNAL_LEDGER_RETRY_HOURS,
|
||||
signalDueFetchLimit:SIGNAL_LEDGER_DUE_FETCH_LIMIT,survivorshipSafeSignalGrading:true,
|
||||
signalRoundTripCostCents:SIGNAL_ROUND_TRIP_COST*100,independentConfidence:true,uncertaintyGatedCalibration:true,
|
||||
historicalPrior:"reversal and short-dated NO entries disabled; sports trends blocked outside exploration; crypto, longshots, and YES sized down"}),
|
||||
historicalPrior:"reversal disabled; short-dated NO requires recent promotion; exact ranges excluded; sports trends blocked outside exploration; crypto, longshots, and YES sized down"}),
|
||||
});
|
||||
function runEngineSelfTest(){
|
||||
const market=(overrides={})=>Object.assign({
|
||||
@@ -4284,6 +4308,8 @@ function runEngineSelfTest(){
|
||||
const trend=analyzeMarket(market(),news);
|
||||
const noSignal=analyzeMarket(market({price_change_1h:0,price_change_1d:0.002,price_change_1w:-0.002}),news);
|
||||
const reversal=analyzeMarket(market({price_change_1h:-0.01,price_change_1d:0.07,price_change_1w:0.02}),news);
|
||||
const intervalContract=analyzeMarket(market({id:"range-test",question:"Will Count Binface win 20–30% of votes?"}),news);
|
||||
const ordinaryDatedContract=analyzeMarket(market({id:"dated-test",question:"Will the policy pass on 2026-08-22?"}),news);
|
||||
const targets=window.PMA_ENGINE_DIAGNOSTICS.gainStopTargets(0.82);
|
||||
const hoursAgo=h=>new Date(Date.now()-h*3600000).toISOString();
|
||||
const conflict={trade_ready:true,side:"NO",net_edge:-0.03,conviction:72};
|
||||
@@ -4321,6 +4347,9 @@ function runEngineSelfTest(){
|
||||
const earlyLedgerState={signal_ledger:{pending:[{key:"ledger-early",market_id:"ledger-early",observed_at:hoursAgo(13),side:"YES",entry_price:0.40,
|
||||
signal_type:"trend",quality:"confirmed",category:"Politics"}],outcomes:[]}};
|
||||
updateSignalLedger(earlyLedgerState,[market({id:"ledger-early",yes_price:0.50,no_price:0.50})],[]);
|
||||
const observationLedgerState={signal_ledger:defaultSignalLedger()};
|
||||
updateSignalLedger(observationLedgerState,[],[{market_id:"observation-only",side:"YES",entry_price:0.42,signal_type:"trend",quality:"watch",
|
||||
signal_confidence:0.62,trade_ready:false,jump_risk:false,category:"Politics",days_to_resolution:45}]);
|
||||
const dueFetchLedger={pending:[
|
||||
{key:"known",market_id:"known-active",observed_at:hoursAgo(25)},
|
||||
{key:"outside-a",market_id:"outside-active-scan",observed_at:hoursAgo(26)},
|
||||
@@ -4332,12 +4361,14 @@ function runEngineSelfTest(){
|
||||
const expiredLedgerState={signal_ledger:{pending:[{key:"expired",market_id:"never-returned",observed_at:hoursAgo(169),side:"YES",entry_price:0.4}],outcomes:[]}};
|
||||
updateSignalLedger(expiredLedgerState,[],[]);
|
||||
const calibrationCandidate={signal_type:"trend",quality:"confirmed",category:"Politics",side:"YES",entry_price:0.42};
|
||||
const calibrationFromReturns=returns=>buildSignalCalibration({pending:[],outcomes:returns.map(ret=>Object.assign({},calibrationCandidate,
|
||||
const calibrationFromReturns=(returns,candidate=calibrationCandidate)=>buildSignalCalibration({pending:[],outcomes:returns.map(ret=>Object.assign({},candidate,
|
||||
{strategy_version:SUGGESTION_ENGINE_VERSION,return:ret,evaluated_at:closedAt}))});
|
||||
const singleCalibration=calibratedOpportunity(calibrationCandidate,calibrationFromReturns([0.10]));
|
||||
const stablePositiveCalibration=calibratedOpportunity(calibrationCandidate,calibrationFromReturns(Array(24).fill(0.12)));
|
||||
const stableNegativeCalibration=calibratedOpportunity(calibrationCandidate,calibrationFromReturns(Array(24).fill(-0.12)));
|
||||
const noisyCalibration=calibratedOpportunity(calibrationCandidate,calibrationFromReturns(Array.from({length:24},(_,i)=>i%2?0.12:-0.12)));
|
||||
const promotedShortNoCandidate={market_id:"short-no-promoted",signal_type:"trend",quality:"confirmed",category:"Politics",side:"NO",entry_price:0.58,days_to_resolution:14};
|
||||
const promotedShortNo=learnedOpportunity(AGENTS[0],defaultPortfolio(),promotedShortNoCandidate,null,calibrationFromReturns(Array(24).fill(0.12),promotedShortNoCandidate));
|
||||
const legacyBuildCalibration=buildSignalCalibration({pending:[],outcomes:[Object.assign({},calibrationCandidate,
|
||||
{strategy_version:PREVIOUS_STRATEGY_VERSION,return:0.10,evaluated_at:closedAt})]});
|
||||
const currentStrategyCalibration=buildSignalCalibration({pending:[],outcomes:[Object.assign({},calibrationCandidate,
|
||||
@@ -4396,11 +4427,11 @@ function runEngineSelfTest(){
|
||||
delete executableBook.positions[0].price_status;
|
||||
markToMarket(executableBook,{"offline-mark":market({id:"offline-mark",yes_price:0.8,no_price:0.2})},AGENTS[0],{policyExits:true,executeTrades:true});
|
||||
const buildMigrationState=defaultState();
|
||||
buildMigrationState.engine_version=45;buildMigrationState.strategy_version=SUGGESTION_ENGINE_VERSION;
|
||||
buildMigrationState.engine_version=46;buildMigrationState.strategy_version=SUGGESTION_ENGINE_VERSION;
|
||||
buildMigrationState.agents.value.engine_baseline={version:SUGGESTION_ENGINE_VERSION,started_at:hoursAgo(2),equity:9876.54};
|
||||
reconcileStateVersions(buildMigrationState);
|
||||
const strategyMigrationState=defaultState();
|
||||
strategyMigrationState.engine_version=45;strategyMigrationState.strategy_version=PREVIOUS_STRATEGY_VERSION;
|
||||
strategyMigrationState.engine_version=46;strategyMigrationState.strategy_version=PREVIOUS_STRATEGY_VERSION;
|
||||
strategyMigrationState.agents.value.cash=9876.54;
|
||||
strategyMigrationState.agents.value.engine_baseline={version:PREVIOUS_STRATEGY_VERSION,started_at:hoursAgo(2),equity:10000};
|
||||
reconcileStateVersions(strategyMigrationState);
|
||||
@@ -4420,7 +4451,9 @@ function runEngineSelfTest(){
|
||||
historicalPriorBlocksSportsTrend:!priorSportsTrend.allowed&&priorSportsTrend.blocked_by==="historical",
|
||||
historicalPriorAllowsPoliticsTrend:!priorPoliticsTrend.blocked,
|
||||
blocksShortDatedNo:!shortNoPrior.allowed&&shortNoPrior.blocked_by==="historical",
|
||||
recentProofCanUnlockShortDatedNo:promotedShortNo.allowed&&promotedShortNo.market_state==="promoted",
|
||||
allowsLongDatedNo:!longNoPrior.blocked,
|
||||
observesConfirmedSignalsWithoutTrading:observationLedgerState.signal_ledger.pending.length===1&&observationLedgerState.signal_ledger.pending[0].trade_ready_at_observation===false,
|
||||
ledgerMaturesWithoutLookahead:ledgerState.signal_ledger.pending.length===0&&ledgerState.signal_ledger.outcomes.length===1&&ledgerState.signal_ledger.outcomes[0].return===0.2375,
|
||||
holdsSignalsUntilPolicyHorizon:earlyLedgerState.signal_ledger.pending.length===1&&earlyLedgerState.signal_ledger.outcomes.length===0,
|
||||
fetchesMaturedMarketsOutsideActiveScan:dueFetchIds.length===1&&dueFetchIds[0]==="outside-active-scan",
|
||||
@@ -4440,7 +4473,7 @@ function runEngineSelfTest(){
|
||||
noisyEvidenceStaysNeutral:noisyCalibration.state==="observing"&&noisyCalibration.multiplier>=0.99&&noisyCalibration.multiplier<=1.01,
|
||||
blocksConfirmedLosingRegime:!lossOpportunity.allowed,containmentMode:lossDecision.mode,containmentMaxNew:lossDecision.maxNew,
|
||||
legacyLossDoesNotFreezeCurrentEngine:legacyLossDecision.mode!=="Loss Regime Containment"},
|
||||
riskBudget:{core:coreRiskBudget,aggressiveGap:aggressiveGapBudget,boundedStake:boundedStakeForRisk(10000,1000,riskCfg,{entry_price:0.82,days_to_resolution:5,price_change_1d:0.06}),
|
||||
riskBudget:{core:coreRiskBudget,aggressiveGap:aggressiveGapBudget,blocksExactRange:intervalContract.jump_risk&&!intervalContract.trade_ready,preservesOrdinaryDatedContract:!ordinaryDatedContract.jump_risk,boundedStake:boundedStakeForRisk(10000,1000,riskCfg,{entry_price:0.82,days_to_resolution:5,price_change_1d:0.06}),
|
||||
legacyNormalizedValue:riskPos.value,equityPreserved:+equity(riskBook).toFixed(2),capsBinaryGap:aggressiveGapBudget===0.03&&riskPos.value<=300.01},
|
||||
offline:{fresh:offlineCachePolicy(30*60000),staleEntry:offlineCachePolicy(3*3600000),expired:offlineCachePolicy(25*3600000),
|
||||
staleMarkUpdatesValue:markOnlyBook.positions.length===1&&markOnlyBook.positions[0].value===800,
|
||||
|
||||
@@ -74,6 +74,19 @@ function priceBand(price) {
|
||||
return "heavy-favorite";
|
||||
}
|
||||
|
||||
function confirmedTrendAt(points, target, current) {
|
||||
const dayPoint = atOrBefore(points, target - DAY), weekPoint = atOrBefore(points, target - 7 * DAY);
|
||||
if (!dayPoint || !weekPoint || target - DAY - dayPoint.t > 36 * 3600 || target - 7 * DAY - weekPoint.t > 36 * 3600) return null;
|
||||
const dayMove = current.p - dayPoint.p, weekMove = current.p - weekPoint.p;
|
||||
const daySign = Math.sign(dayMove), weekSign = Math.sign(weekMove);
|
||||
const confirmed = daySign && daySign === weekSign && Math.abs(dayMove) >= 0.006 && Math.abs(weekMove) >= 0.012
|
||||
&& Math.abs(dayMove) <= 0.08 && Math.abs(weekMove) <= 0.18;
|
||||
if (!confirmed) return null;
|
||||
return { side: daySign > 0 ? "YES" : "NO", dayMove, weekMove,
|
||||
strong: Math.abs(dayMove) >= 0.015 && Math.abs(weekMove) >= 0.03,
|
||||
moderate: Math.abs(dayMove) <= 0.03 && Math.abs(weekMove) <= 0.10 };
|
||||
}
|
||||
|
||||
async function fetchResolvedMarkets(limit) {
|
||||
const raw = [], seen = new Set(), pageSize = 100;
|
||||
for (let offset = 0; raw.length < limit && offset < limit * 3; offset += pageSize) {
|
||||
@@ -105,12 +118,15 @@ function evaluateMarket(market, points) {
|
||||
const maximumStaleness = Math.max(36 * 3600, horizonDays * DAY * 0.15);
|
||||
if (!point || target - point.t > maximumStaleness || point.p <= 0.03 || point.p >= 0.97) continue;
|
||||
const yesEntry = point.p, noEntry = 1 - point.p, favoriteSide = yesEntry >= noEntry ? "YES" : "NO";
|
||||
const winningSide = market.finalYes ? "YES" : "NO";
|
||||
const winningSide = market.finalYes ? "YES" : "NO", trend = confirmedTrendAt(points, target, point);
|
||||
for (const side of ["YES", "NO"]) {
|
||||
const entry = side === "YES" ? yesEntry : noEntry, final = side === winningSide ? 1 : 0;
|
||||
const netReturn = final / entry - 1 - (COST_CENTS / 100) / entry;
|
||||
rows.push({ marketId: market.id, eventId: market.eventId, question: market.question, category: market.category, closedAt: market.closedAt,
|
||||
horizonDays, side, favorite: side === favoriteSide, winner: side === winningSide,
|
||||
trend: Boolean(trend && trend.side === side), trendSide: trend?.side || null,
|
||||
dayMove: trend?.dayMove || 0, weekMove: trend?.weekMove || 0,
|
||||
strongTrend: Boolean(trend?.strong), moderateTrend: Boolean(trend?.moderate),
|
||||
entry, band: priceBand(entry), netReturn });
|
||||
}
|
||||
}
|
||||
@@ -152,9 +168,17 @@ const RULES = [
|
||||
{ name: "buy_underdog", test: (row) => !row.favorite },
|
||||
{ name: "buy_yes", test: (row) => row.side === "YES" },
|
||||
{ name: "buy_no", test: (row) => row.side === "NO" },
|
||||
{ name: "follow_trend", test: (row) => row.trend },
|
||||
{ name: "follow_trend_yes", test: (row) => row.trend && row.side === "YES" },
|
||||
{ name: "follow_trend_no", test: (row) => row.trend && row.side === "NO" },
|
||||
{ name: "follow_trend_favorite", test: (row) => row.trend && row.favorite },
|
||||
{ name: "follow_trend_underdog", test: (row) => row.trend && !row.favorite },
|
||||
{ name: "follow_strong_trend", test: (row) => row.trend && row.strongTrend },
|
||||
{ name: "follow_moderate_trend", test: (row) => row.trend && row.moderateTrend },
|
||||
...["Politics", "Sports", "Crypto", "Economy", "Pop Culture", "Other"].flatMap((category) => [
|
||||
{ name: `buy_favorite_${category.toLowerCase().replace(/\s+/g, "_")}`, test: (row) => row.favorite && row.category === category },
|
||||
{ name: `buy_underdog_${category.toLowerCase().replace(/\s+/g, "_")}`, test: (row) => !row.favorite && row.category === category },
|
||||
{ name: `follow_trend_${category.toLowerCase().replace(/\s+/g, "_")}`, test: (row) => row.trend && row.category === category },
|
||||
]),
|
||||
];
|
||||
|
||||
@@ -202,7 +226,7 @@ const report = {
|
||||
methodology: { horizonDays: HORIZON_DAYS, estimatedRoundTripCostCents: COST_CENTS,
|
||||
historyFidelityMinutes: 1440,
|
||||
clusterUnit: "event",
|
||||
note: "Each rule uses a daily price timestamp at or before the decision horizon and a subsequently published binary settlement. Confidence bounds cluster related markets by event. Markets are selected by resolved volume, so results still carry historical-selection and execution-model limitations." },
|
||||
note: "Each rule uses only daily prices available at or before the decision horizon and a subsequently published binary settlement. Trend replays require aligned one-day and one-week direction under the production move bounds. Confidence bounds cluster related markets by event. Markets are selected by resolved volume, so results still carry historical-selection and execution-model limitations." },
|
||||
horizons: Object.fromEntries(HORIZON_DAYS.map((horizon) => {
|
||||
const horizonRows = rows.filter((row) => row.horizonDays === horizon);
|
||||
return [horizon, { observations: horizonRows.length / 2, chronological: chronologicalEvaluation(horizonRows) }];
|
||||
@@ -225,6 +249,12 @@ const summary = {
|
||||
favoriteTest: compactStats(value.chronological.test.buy_favorite),
|
||||
underdog: compactStats(value.chronological.train.buy_underdog),
|
||||
underdogTest: compactStats(value.chronological.test.buy_underdog),
|
||||
yes: compactStats(value.chronological.train.buy_yes),
|
||||
yesTest: compactStats(value.chronological.test.buy_yes),
|
||||
no: compactStats(value.chronological.train.buy_no),
|
||||
noTest: compactStats(value.chronological.test.buy_no),
|
||||
trend: compactStats(value.chronological.train.follow_trend),
|
||||
trendTest: compactStats(value.chronological.test.follow_trend),
|
||||
robustRules: compactRules(value.chronological.robustRules),
|
||||
}])),
|
||||
};
|
||||
|
||||
Reference in New Issue
Block a user