Kunthawat Greethong
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6e78b6acb5
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[verified] Apply R1-R5 (factor formula) + real bank-sector NPL collector
(a) R1-R5 (factor-refinement, grounded in methodology-research.md):
- R1 (PEAD): EPS-growth weight raised 1.0->1.5 in build_siamchart_score / symbol_breakdown (Bernard-Thomas 1990, Livnat-Mendenhall 2006)
- R2 (momentum): 12-1 momentum factor from Yahoo price snapshot (Jegadeesh-Titman 93; lite weight 0.5)
- R3 (regime): binary bear gate -> continuous stress = negative-themes fraction, smooth LONG/SHORT shift
- R5 (dividend screen): non-dividend / cut-yield names no longer go LONG (screen-off)
- R4 (earnings-revision) deferred: no free EPS-forecast source yet (documented)
(b) bank-sector NPL collector (BOT reportID 794, financial&insurance sector):
- refactored auto_npl to expose shared _parse_sector; new bank_npl.py reuses it
- registered bank_npl FACTOR -> auto-appears in sources table (6 rows) + blends into banks theme surprise (real NPL)
- +unit tests (test_bank_npl), test_dashboard updated (6 sources)
205 tests pass; verified live API (banks surprise incl. NPL 1.07, 6 sources).
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2026-08-26 19:56:39 +07:00 |
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Kunthawat Greethong
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e7819a35dd
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[verified] All 13 SET50 themes now have real surprise (macro-proxy) — no more 'ยังไม่มีข้อมูล'
- dashboard._theme_surprises: adds macro-proxy surprise for banks/retail/telecom_it/property/healthcare/petrochem/utilities/consumer_staples/nonbank_finance/exploration from BOT macro (consumption/investment/inflation/mfg)
- dashboard.build(): creates all 13 themes with proxy reads + deterministic narrative per theme
- _mk_theme now uses THEME_LABELS_TH + THEME_FREQUENCY (not hardcoded 3)
- Verify: 13 themes w/ surprise (banks 1.0, retail 0.19, utilities -0.31, exploration 1.62); BBL modal (ธนาคาร 1.00σ, combined 0.467)
- Full suite 199 OK; fixed test_build themes=13
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2026-08-26 14:19:59 +07:00 |
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Kunthawat Greethong
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9739849f68
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[verified] Add real multi-theme dashboard (3 themes + macro + board + sources) — req #6/#8/#9/#10
- dashboard.py: RealDashboard assembles real Thai data (tourism + auto+NPL + energy TOP + macro BOT) with uniform z-score surprise per theme, per-theme thesis, sources provenance table, 49-symbol combined board
- macro_thai.py: BOT Thai Economy macro backdrop (consumption +4.9%, inflation 1.95%, unemployment 0.93%, tourists 16.2mn)
- GET /api/v1/dashboard endpoint (real data, no fixture fallback per user)
- 7 new tests; full suite 195 OK; live verified (3 theme surprise: 0.571/0.81/1.623)
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2026-08-25 20:30:14 +07:00 |
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