geometrybase
48b89552fe
Request: - Use the analyst skill to digest downloaded IPO archive data and start building an analysis model. Changes: - Add ipo_score_v0 as the first transparent stage-safe scoring rule set. - Add build_analysis_dataset.py to derive model features, scores, decision bands, and empirical D1 calibration from SQLite. - Generate analysis_model_v0_dataset.csv with 293 scored IPO rows and archived source paths. - Add a model calibration report documenting coverage, T0/T1 bucket performance, usage, and known gaps. - Record the initial model entry in the rule change log and document the command in README. Verification: - Ran py_compile for scripts/build_analysis_dataset.py. - Regenerated the analysis dataset and report with as-of 2026-06-15T13:00:00Z. - Checked CSV row count, source path coverage, and repo-relative path hygiene. - Ran git diff --cached --check. Next useful context: - v0 should be treated as a transparent baseline, with T1 high-score calibration strongest and middle buckets still non-monotonic. - T2 is excluded until a reliable grey-market source is approved.
151 lines
4.3 KiB
YAML
151 lines
4.3 KiB
YAML
version: ipo_score_v0
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effective_date: 2026-06-15
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status: initial_baseline
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owner_skill: analyst
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purpose: >
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Build the first transparent Hong Kong IPO subscription scoring model from
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archived project data. The model is a rules-plus-calibration baseline, not a
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black-box predictor. It separates T0 prospectus information from T1 allotment
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information so later facts do not leak into earlier decisions.
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targets:
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primary: D1 return versus IPO offer price
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secondary:
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- D5 return versus IPO offer price
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- D20 return versus IPO offer price
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- D60 return versus IPO offer price
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stage_policy:
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T0_prospectus:
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allowed_inputs:
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- offer_price_hkd
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- gross_proceeds_hkd_m
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- funds_raised_hkd_m
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- min_subscription_amount_hkd
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- public_offer_pct_initial
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- over_allotment_offer_shares
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forbidden_inputs:
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- allotment_results
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- public_oversubscription_times
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- international_oversubscription_times
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- post_listing_price_performance
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T1_allotment:
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allowed_inputs:
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- all_T0_inputs
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- public_oversubscription_times
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- international_oversubscription_times
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- valid_applications
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- successful_applications
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- final_hk_offer_shares
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- hk_offer_shares_initial
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forbidden_inputs:
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- grey_market_result
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- post_listing_price_performance
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T2_grey_market:
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status: disabled_until_reliable_source_exists
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note: >
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T2 is excluded from v0 because no reproducible, redistribution-safe
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grey-market data source has been approved.
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score_components:
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T0_prospectus:
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offer_size_hkd_m:
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source: gross_proceeds_hkd_m, falling back to funds_raised_hkd_m
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points:
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missing: 0
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lt_300: -2
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gte_300_lt_800: 1
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gte_800_lt_2000: 4
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gte_2000_lt_5000: 3
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gte_5000: 2
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public_offer_pct_initial:
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points:
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missing: 0
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lte_0_05: 3
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gt_0_05_lte_0_10: 1
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gt_0_10: -1
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min_subscription_amount_hkd:
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points:
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missing: -1
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lt_3500: -1
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gte_3500_lt_10000: 2
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gte_10000: 1
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offer_price_hkd:
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points:
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missing: 0
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lt_1: -2
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gte_1_lt_5: 0
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gte_5_lt_30: 1
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gte_30_lt_100: 2
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gte_100: 1
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over_allotment:
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points:
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present: 1
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missing_or_zero: 0
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T1_allotment:
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public_oversubscription_times:
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points:
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missing: 0
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lt_10: -4
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gte_10_lt_100: -2
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gte_100_lt_1000: 6
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gte_1000_lt_5000: 13
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gte_5000: 15
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international_oversubscription_times:
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points:
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missing: 0
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lt_1: -2
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gte_1_lt_3: -1
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gte_3_lt_10: 1
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gte_10_lt_30: 6
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gte_30: 8
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valid_applications:
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points:
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missing: 0
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lt_10000: -2
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gte_50000_lt_100000: 1
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gte_100000_lt_200000: 3
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gte_200000: 5
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application_success_rate:
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definition: successful_applications / valid_applications
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points:
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missing: 0
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lte_0_10: 4
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gt_0_10_lte_0_30: 2
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gt_0_80: -2
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hk_offer_reallocation_multiple:
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definition: final_hk_offer_shares / hk_offer_shares_initial
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points:
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missing: 0
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gte_2_lt_3: 2
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gte_3: 4
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decision_bands:
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T0_prospectus:
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t0_score_lt_1: weak_or_avoid
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t0_score_1_to_4: neutral
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t0_score_5_to_7: positive_watch
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t0_score_gte_8: strong_watch
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T1_allotment:
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total_score_lt_0: avoid
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total_score_0_to_9: avoid_or_wait
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total_score_10_to_17: watch_or_small
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total_score_18_to_25: selective_subscribe
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total_score_gte_26: high_conviction_subscribe
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calibration_policy:
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method: empirical_bucket_rate
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primary_label: D1_return_pct > 0
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strong_label: D1_return_pct >= 10
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report_path: reports/2026-06-15_analysis_model_v0.md
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dataset_path: data/snapshots/analysis_model_v0_dataset.csv
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known_limitations:
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- T0 has weaker discrimination than T1 because demand data is not available yet.
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- T1 structured demand facts are incomplete for older HTML-only allotment notices.
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- Industry labels and issuer fundamentals are not yet sufficiently structured for v0.
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- T2 grey-market signal is intentionally disabled until a reliable source exists.
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- Current D1 outcomes are from archived market data and should be reviewed for extreme corporate-action or data-vendor anomalies.
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