Phase 1 — Edge neto real (paper.py, bayesian.py, risk/manager.py, db.py):
- Trade records now store edge_gross, edge_net, prior_prob, final_prob,
mid_price, spread_estimate, commission, family_key
- edge_net = edge_gross - SPREAD_ESTIMATE(0.02) - COMMISSION_RATE(0.02)
NOTE: both constants are heuristics, not exact Polymarket exchange costs
- Execution gate changed from edge_gross > MIN_EDGE to edge_net > regime_min_edge
Phase 2 — Market families (polymarket.py):
- market_family_key(market) groups related markets:
texas-republican-2026, fed-april-2026, openai-2026, etc.
- At most 1 trade per family per cycle; occupied_families propagated via main.py
- Family key logged on every TRADE and SKIP line
Phase 3 — GNews priority (news.py, bayesian.py, main.py):
- NewsClient.get_freshness() returns 1.0/0.75/0.40/0.10 by cache age
- gnews_priority(market, news) = uncertainty × volume_score × freshness
- Politics markets sorted by priority DESC before eval so best markets get
the 5-query/cycle GNews budget first
Phase 4 — Regime min-edge by category/horizon (bayesian.py):
- politics >60d → 0.12, 30-60d → 0.10, <30d → 0.08
- tech / crypto/finance → 0.10
- All thresholds applied to edge_net (not edge_gross)
Phase 5 — Observability (bayesian.py, main.py):
- Structured skip labels: SKIP_UNSUPPORTED, SKIP_NO_SIGNALS,
SKIP_PRIOR_EXTREME, SKIP_FAMILY, SKIP_GNEWS_PRIORITY, SKIP_EDGE_NET
- TRADE lines now include family_key, edge_gross, edge_net, regime_min, days
- schema.sql: 8 new cols on trades, 7 new cols on signals (via ALTER TABLE IF NOT EXISTS)
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- Add European football leagues (La Liga, Premier League, Bundesliga, etc.)
to _SPORTS_EXCLUSIONS so those markets are filtered before category detection
- Reorder _detect_category: check tech before crypto/finance so company-specific
markets (OpenAI IPO, NVIDIA, Apple) resolve to "tech" instead of "crypto/finance"
- Widen resolution horizon default from 60 to 90 days to surface more
markets in the 0.08–0.92 uncertainty zone
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Add _SPORTS_EXCLUSIONS list checked first in _detect_category so NBA/NFL/
MLB/NHL/tennis/golf/UFC/boxing/wrestling/tournament markets never bleed into
politics or events categories. Also removes 'super bowl' from _EVENTS_KEYWORDS
since it's now covered by the sports exclusion.
Keywords excluded: nba, nfl, mlb, nhl, basketball, football, baseball, hockey,
soccer, mvp, rookie of the, championship, super bowl, world series, playoffs,
playoff, tournament, tennis, golf, ufc, boxing, wrestler, wrestling,
slam dunk, home run, touchdown.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- polymarket.py: add keyword lists for politics (election, trump, ukraine…),
tech (AI, OpenAI, Apple, nvidia…), and events (super bowl, oscar, spacex…);
introduce _detect_category() so all four categories flow through a single
code path; filter already-expired markets (end_dt < now) in addition to
the existing future-cutoff filter; log per-category counts at startup
- bayesian.py: extend is_any_supported to include is_politics / is_tech /
is_events; use BTC as a risk-sentiment proxy for non-crypto categories
(halved weight to reflect weaker correlation); cap confidence_cap at 0.65
for macro/politics/tech/events; MIN_EDGE stays at 0.10
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
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