From 907e30d9da2b67465dd952c8c5ef3f7b759b3cfa Mon Sep 17 00:00:00 2001 From: geometrybase Date: Mon, 15 Jun 2026 14:37:46 +0000 Subject: [PATCH] Use Chinese for analyst reports Request: - Make analyst reports Chinese by default and record the rule in the analyst skill. Changes: - Add a Simplified Chinese default-language rule to the analyst skill. - Update the single-IPO report generator to emit Chinese Markdown sections, labels, actions, risks, triggers, and exit plans. - Preserve ticker symbols, stage codes, rule ids, score buckets, and source paths as machine-readable identifiers. - Regenerate the 06106 T0 report in Chinese. - Document the Chinese report default in README and the rule change log. Verification: - Ran py_compile for scripts/generate_ipo_report.py. - Generated a 06106 dry-run report and checked Chinese section headings. - Regenerated reports/2026-06-15_06106_T0_prospectus_analysis.md. - Ran git diff --check. Next useful context: - Future analyst prediction and review reports should be written in Simplified Chinese unless the user explicitly requests another language. --- .codex/skills/analyst/SKILL.md | 6 + README.md | 2 +- ...2026-06-15_06106_T0_prospectus_analysis.md | 144 +++++------ rules/rule_change_log.md | 23 ++ scripts/generate_ipo_report.py | 227 +++++++++--------- 5 files changed, 214 insertions(+), 188 deletions(-) diff --git a/.codex/skills/analyst/SKILL.md b/.codex/skills/analyst/SKILL.md index 1343b1b..19ce120 100644 --- a/.codex/skills/analyst/SKILL.md +++ b/.codex/skills/analyst/SKILL.md @@ -85,6 +85,7 @@ If the ticker is absent from `data/snapshots/analysis_model_v0_dataset.csv`, use Generated prediction reports must remain stage-safe: +- Analyst Markdown reports should be written in Simplified Chinese by default, while preserving ticker symbols, stage codes, rule ids, source paths, and stable error tags in their original machine-readable form. - T0 reports use only prospectus-stage fields and T0 calibration. - T1 reports may add allotment demand fields and T1 calibration. - T2/D1 is the intended sell window; D5/D20/D60 returns are never shown as prediction inputs and are reserved for later review cards. @@ -111,6 +112,11 @@ Every prediction card should include: - explicit T2/D1 sell discipline - source paths +Language standard: + +- Write analyst reports, prediction cards, and review cards in Simplified Chinese by default. +- Keep field identifiers, model versions, score buckets, ticker symbols, and source paths as code-formatted English identifiers when they are part of the project data contract. + Every review card should include: - linked prediction card diff --git a/README.md b/README.md index e372d0a..c09281f 100644 --- a/README.md +++ b/README.md @@ -170,7 +170,7 @@ Use the analyst report generator after the archive and model dataset are current The generator writes `reports/{date}_{ticker}_{stage}_analysis.md` by default. It auto-selects `T1_allotment` when structured allotment-demand facts exist; otherwise it generates a `T0_prospectus` report. Use `--stdout` for a dry run or `--output` to choose a specific Markdown path. -Prediction reports are stage-safe: T0 reports use only prospectus-stage facts and T0 calibration, while T1 reports add allotment demand and T1 calibration. Each report includes a concrete stage calendar for that ticker: T0 subscription window, T1 allotment-result date, T2 grey-market date/window, and D1 listing date. Reports should frame the trade as a T2/D1 exit. Post-listing D5/D20/D60 performance stays out of prediction reports and is reserved for review cards. +Single-IPO analyst reports are written in Simplified Chinese by default, while ticker symbols, stage codes, rule ids, and source paths remain machine-readable. Prediction reports are stage-safe: T0 reports use only prospectus-stage facts and T0 calibration, while T1 reports add allotment demand and T1 calibration. Each report includes a concrete stage calendar for that ticker: T0 subscription window, T1 allotment-result date, T2 grey-market date/window, and D1 listing date. Reports should frame the trade as a T2/D1 exit. Post-listing D5/D20/D60 performance stays out of prediction reports and is reserved for review cards. ## Incremental Archive Sync diff --git a/reports/2026-06-15_06106_T0_prospectus_analysis.md b/reports/2026-06-15_06106_T0_prospectus_analysis.md index 8a65c63..8c52d59 100644 --- a/reports/2026-06-15_06106_T0_prospectus_analysis.md +++ b/reports/2026-06-15_06106_T0_prospectus_analysis.md @@ -1,96 +1,96 @@ -# 06106 IPO Analyst Report +# 06106 IPO 分析报告 -## Summary +## 摘要 -- Ticker: `06106` -- Company: Shanghai Seer Intelligent Technology Co., Ltd. -- Stage: `T0_prospectus` -- Report as of: `2026-06-15T15:00:00Z` -- Model dataset as of: `2026-06-15T14:04:34Z` -- Rule version: `ipo_score_v0` -- Rule path: `rules/ipo_score_v0.yaml` -- Strategy horizon: short IPO subscription trade; intended exit is T2 grey market if reliable, otherwise D1. -- Decision: `strong_watch` -- PM action: Strong watch at T0, still pending T1 demand confirmation for a T2/D1 exit. -- T0 score: `11` -- Score bucket: `t0_gte_8` -- Calibrated D1 positive probability: 76.4% from 72 historical D1 labels +- 股票代码：`06106` +- 公司：Shanghai Seer Intelligent Technology Co., Ltd. +- 分析阶段：`T0_prospectus` +- 报告生成时间：`2026-06-15T15:00:00Z` +- 模型数据时间：`2026-06-15T14:04:34Z` +- 规则版本：`ipo_score_v0` +- 规则路径：`rules/ipo_score_v0.yaml` +- 策略周期：短线 IPO 申购交易；优先在可靠 T2 暗盘卖出，否则默认 D1 卖出。 +- 结论代码：`strong_watch` +- 执行动作：T0 强关注，仍需等待 T1 认购热度确认后执行 T2/D1 退出纪律。 +- T0 分数：`11` +- 分数分桶：`t0_gte_8` +- 历史校准 D1 正收益概率：76.4%，样本数 72 -## Stage Calendar +## 阶段日期表 -| Stage | Concrete Date For This IPO | Meaning | +| 阶段 | 本 IPO 对应日期 | 含义 | | --- | --- | --- | -| `T0_prospectus` | 2026-06-15 to 2026-06-18 | Subscription window; use prospectus and offer terms only. | -| `T1_allotment` | 2026-06-23 | Allotment results day; use public demand, placing demand, and allocation facts. | -| `T2_grey_market` | 2026-06-23 after allotment results | Pre-listing grey-market sell window if a reliable executable source exists. | -| `D1` | 2026-06-24 | First official trading day; default sell window when T2 data is unavailable or unreliable. | +| `T0_prospectus` | 2026-06-15 至 2026-06-18 | 申购前/申购中阶段；只使用招股书和发行条款。 | +| `T1_allotment` | 2026-06-23 | 分配结果日；使用公开认购热度、国际配售热度和分配事实。 | +| `T2_grey_market` | 2026-06-23 分配结果公布后 | 上市前暗盘窗口；只有存在可靠且可执行的数据源时才作为卖出依据。 | +| `D1` | 2026-06-24 | 正式上市首日；T2 数据不可用或不可靠时的默认卖出窗口。 | -## Facts +## 基础事实 -| Field | Value | +| 字段 | 数值 | | --- | --- | -| Board | Main Board | -| Status | open_for_subscription | -| Listing date | 2026-06-24 | -| Application period | 2026-06-15 to 2026-06-18 | -| Allotment result date | 2026-06-23 | -| Listing method | n/a | -| Industry | Industrial intelligent robots / robot controllers | -| Sponsors | n/a | -| Offer price | HK$101.60 | -| Offer size | HK$1,066.5m | -| Market cap | HK$11,226.5m | -| Board lot | 50 | -| Minimum subscription | HK$5,131.24 | -| Initial public offer percentage | 5.0% | -| Over-allotment shares | 1,574,550 | +| 板块 | Main Board | +| 状态 | open_for_subscription | +| 上市日期 | 2026-06-24 | +| 申购期 | 2026-06-15 至 2026-06-18 | +| 分配结果日期 | 2026-06-23 | +| 上市方式 | 未记录 | +| 行业 | Industrial intelligent robots / robot controllers | +| 保荐人 | 未记录 | +| 发行价 | HK$101.60 | +| 发行规模 | HK$1,066.5m | +| 市值 | HK$11,226.5m | +| 每手股数 | 50 | +| 最低认购金额 | HK$5,131.24 | +| 初始公开发售比例 | 5.0% | +| 超额配股权股数 | 1,574,550 | -## Short-Exit Model Inference +## 短线退出模型推断 -- D1 positive probability: 76.4% -- D1 >= 10% probability: 47.2% -- Historical average D1 return for bucket: 28.6% -- Historical median D1 return for bucket: 9.6% -- T2 sell return is not modeled until an approved grey-market data source exists. -- D5/D20/D60 outcomes are review labels only, not holding targets. +- D1 正收益概率：76.4% +- D1 涨幅不低于 10% 概率：47.2% +- 同分桶历史 D1 平均收益：28.6% +- 同分桶历史 D1 中位收益：9.6% +- T2 暗盘卖出收益暂未建模，直到项目确认可靠暗盘数据源。 +- D5/D20/D60 只作为复盘标签，不是持仓目标。 -## Score Breakdown +## 评分拆解 -| Component | Points | Reason | +| 评分项 | 分数 | 原因代码 | | --- | ---: | --- | -| Offer size | 4 | `800m_to_2000m` | -| Initial public offer percentage | 3 | `lte_5pct` | -| Minimum subscription | 2 | `3500_to_10000` | -| Offer price | 1 | `gte_100` | -| Over-allotment option | 1 | `present` | +| 发行规模 | 4 | `800m_to_2000m` | +| 初始公开发售比例 | 3 | `lte_5pct` | +| 最低认购金额 | 2 | `3500_to_10000` | +| 发行价 | 1 | `gte_100` | +| 超额配股权 | 1 | `present` | -## Bull Points +## 正面因素 -- Offer size: +4 (`800m_to_2000m`). -- Initial public offer percentage: +3 (`lte_5pct`). -- Minimum subscription: +2 (`3500_to_10000`). -- Offer price: +1 (`gte_100`). -- Over-allotment option: +1 (`present`). +- 发行规模：+4 (`800m_to_2000m`)。 +- 初始公开发售比例：+3 (`lte_5pct`)。 +- 最低认购金额：+2 (`3500_to_10000`)。 +- 发行价：+1 (`gte_100`)。 +- 超额配股权：+1 (`present`)。 -## Risks And Gaps +## 风险与缺口 -- No material negative scoring component. -- No required report field is blank for this stage. -- T2 grey-market signal is not used yet because the project has no approved reproducible source. -- Post-listing D5/D20/D60 outcomes are labels for later review only and are not holding-period targets. +- 没有明显负向评分项。 +- 本阶段必需字段没有明显空缺。 +- T2 暗盘信号暂未使用，因为项目还没有批准可复现的数据源。 +- 上市后的 D5/D20/D60 表现只用于后续复盘，不是本模型的持仓周期目标。 -## Triggers +## 触发条件 -- Upgrade: stronger verified T1 demand, better allocation scarcity, or a new rule-backed positive catalyst. -- Downgrade: weak public or international demand, oversized supply, low-quality missing fields, or adverse market window. +- 上调：T1 认购热度显著更强、分配稀缺性更好，或出现有规则支持的新正面催化。 +- 下调：公开或国际需求偏弱、供给过大、关键字段质量不足，或市场窗口明显转差。 -## Exit Plan +## 退出计划 -- If subscribed and allocated, plan to sell in T2 grey market when reliable executable data is available. -- If T2 is unavailable or unreliable, use D1 as the default exit window. -- Do not treat D5/D20/D60 as planned holding periods for this model. -- Record D1/D5/D20/D60 outcomes later as review labels, not as retroactive prediction inputs. +- 如果申购并获配，且 T2 暗盘数据可靠且可执行，优先按 T2 暗盘卖出计划处理。 +- 如果 T2 不可用或不可靠，默认使用 D1 作为卖出窗口。 +- 不把 D5/D20/D60 作为本模型的计划持仓周期。 +- 后续记录 D1/D5/D20/D60 结果时，只作为复盘标签，不作为倒推预测输入。 -## Source Paths +## 来源路径 - `data/raw/06106/prospectus_candidate_2026-06-15.pdf` diff --git a/rules/rule_change_log.md b/rules/rule_change_log.md index 4684b74..b3c8414 100644 --- a/rules/rule_change_log.md +++ b/rules/rule_change_log.md @@ -1,5 +1,28 @@ # Rule Change Log +## 2026-06-15 - Use Chinese for analyst reports + +Request: + +- Make analyst reports Chinese by default and record the rule in the analyst skill. + +Change: + +- Added a Simplified Chinese default language rule to the analyst skill. +- Updated the single-ticker report generator to write Chinese Markdown reports while preserving ticker symbols, stage codes, rule ids, score buckets, and source paths as machine-readable identifiers. +- Regenerated the 06106 T0 report in Chinese. +- Documented the Chinese report default in README. + +Rationale: + +- The analysis workflow is intended for Chinese-language IPO subscription decisions, while project identifiers still need to remain stable for scripts and audits. + +Verification: + +- Generated a 06106 dry-run report and checked the Chinese sections. +- Regenerated `reports/2026-06-15_06106_T0_prospectus_analysis.md`. +- Ran py_compile for the report generator and git diff --check. + ## 2026-06-15 - Add concrete stage dates to reports Request: diff --git a/scripts/generate_ipo_report.py b/scripts/generate_ipo_report.py index 83a8d65..de17c0b 100644 --- a/scripts/generate_ipo_report.py +++ b/scripts/generate_ipo_report.py @@ -104,49 +104,49 @@ def as_bool(value: Any) -> bool: def fmt_value(value: Any) -> str: if value in {None, ""}: - return "n/a" + return "未记录" return str(value) def fmt_num(value: float | None, suffix: str = "", decimals: int = 1) -> str: if value is None: - return "n/a" + return "未记录" return f"{value:,.{decimals}f}{suffix}" def fmt_pct_rate(value: float | None) -> str: if value is None: - return "n/a" + return "未记录" return f"{value * 100:.1f}%" def fmt_pct_points(value: float | None) -> str: if value is None: - return "n/a" + return "未记录" return f"{value:.1f}%" def fmt_money_m(value: float | None) -> str: if value is None: - return "n/a" + return "未记录" return f"HK${value:,.1f}m" def fmt_hkd(value: float | None) -> str: if value is None: - return "n/a" + return "未记录" return f"HK${value:,.2f}" def fmt_times(value: float | None) -> str: if value is None: - return "n/a" + return "未记录" return f"{value:,.2f}x" def fmt_int(value: int | None) -> str: if value is None: - return "n/a" + return "未记录" return f"{value:,}" @@ -214,37 +214,37 @@ def t0_decision_band(score: int) -> str: def action_for_decision(decision: str) -> str: actions = { - "weak_or_avoid": "Avoid at T0 unless later T1 demand changes the setup.", - "neutral": "Wait for T1 allotment demand before subscribing.", - "positive_watch": "Watch positively, but wait for T1 confirmation before sizing for a T2/D1 exit.", - "strong_watch": "Strong watch at T0, still pending T1 demand confirmation for a T2/D1 exit.", - "avoid": "Avoid subscription.", - "avoid_or_wait": "Avoid or wait; do not size without a stronger catalyst.", - "watch_or_small": "Small subscription only if execution constraints support a T2/D1 exit.", - "selective_subscribe": "Selective subscription with disciplined T2/D1 sell sizing.", - "high_conviction_subscribe": "Subscribe, subject to allocation, liquidity, and T2/D1 sell discipline.", + "weak_or_avoid": "T0 阶段回避，除非后续 T1 认购热度明显改变格局。", + "neutral": "暂等 T1 分配结果，不在 T0 阶段主动下重注。", + "positive_watch": "正面观察，但需要等 T1 确认后再决定 T2/D1 退出仓位。", + "strong_watch": "T0 强关注，仍需等待 T1 认购热度确认后执行 T2/D1 退出纪律。", + "avoid": "回避申购。", + "avoid_or_wait": "回避或等待；没有更强催化前不放大仓位。", + "watch_or_small": "仅在执行条件支持 T2/D1 退出时小额参与。", + "selective_subscribe": "选择性申购，并严格按 T2/D1 卖出纪律控制仓位。", + "high_conviction_subscribe": "积极申购，但仍受分配、流动性和 T2/D1 卖出纪律约束。", } return actions[decision] def component_label(name: str) -> str: labels = { - "offer_size": "Offer size", - "public_pct": "Initial public offer percentage", - "min_subscription": "Minimum subscription", - "offer_price": "Offer price", - "over_allotment": "Over-allotment option", - "public_os": "Public oversubscription", - "international_os": "International oversubscription", - "valid_applications": "Valid applications", - "success_rate": "Application success rate", - "hk_reallocation": "HK public offer reallocation", + "offer_size": "发行规模", + "public_pct": "初始公开发售比例", + "min_subscription": "最低认购金额", + "offer_price": "发行价", + "over_allotment": "超额配股权", + "public_os": "公开认购倍数", + "international_os": "国际配售认购倍数", + "valid_applications": "有效申请数", + "success_rate": "申请成功率", + "hk_reallocation": "香港公开发售回拨", } return labels.get(name, name.replace("_", " ").title()) def components_table(components: list[ScoreComponent]) -> str: - lines = ["| Component | Points | Reason |", "| --- | ---: | --- |"] + lines = ["| 评分项 | 分数 | 原因代码 |", "| --- | ---: | --- |"] for component in components: lines.append(f"| {component_label(component.name)} | {component.points} | `{component.reason}` |") return "\n".join(lines) @@ -252,36 +252,36 @@ def components_table(components: list[ScoreComponent]) -> str: def facts_table(record: dict[str, str], stage: str) -> str: rows = [ - ("Board", fmt_value(record["board"])), - ("Status", fmt_value(record["status"])), - ("Listing date", fmt_value(record["listing_date"])), - ("Application period", f"{fmt_value(record['application_start_date'])} to {fmt_value(record['application_end_date'])}"), - ("Allotment result date", fmt_value(record["allotment_results_expected_date"])), - ("Listing method", fmt_value(record["listing_method"])), - ("Industry", fmt_value(record["industry_label"])), - ("Sponsors", fmt_value(record["sponsors"])), - ("Offer price", fmt_hkd(as_float(record["offer_price_hkd"]))), - ("Offer size", fmt_money_m(as_float(record["offer_size_hkd_m"]))), - ("Market cap", fmt_money_m(as_float(record["market_cap_hkd_m"]))), - ("Board lot", fmt_int(as_int(record["board_lot"]))), - ("Minimum subscription", fmt_hkd(as_float(record["min_subscription_amount_hkd"]))), - ("Initial public offer percentage", fmt_pct_points(as_float(record["public_offer_pct_initial"]) * 100 if record["public_offer_pct_initial"] else None)), - ("Over-allotment shares", fmt_int(as_int(record["over_allotment_offer_shares"]))), + ("板块", fmt_value(record["board"])), + ("状态", fmt_value(record["status"])), + ("上市日期", fmt_value(record["listing_date"])), + ("申购期", f"{fmt_value(record['application_start_date'])} 至 {fmt_value(record['application_end_date'])}"), + ("分配结果日期", fmt_value(record["allotment_results_expected_date"])), + ("上市方式", fmt_value(record["listing_method"])), + ("行业", fmt_value(record["industry_label"])), + ("保荐人", fmt_value(record["sponsors"])), + ("发行价", fmt_hkd(as_float(record["offer_price_hkd"]))), + ("发行规模", fmt_money_m(as_float(record["offer_size_hkd_m"]))), + ("市值", fmt_money_m(as_float(record["market_cap_hkd_m"]))), + ("每手股数", fmt_int(as_int(record["board_lot"]))), + ("最低认购金额", fmt_hkd(as_float(record["min_subscription_amount_hkd"]))), + ("初始公开发售比例", fmt_pct_points(as_float(record["public_offer_pct_initial"]) * 100 if record["public_offer_pct_initial"] else None)), + ("超额配股权股数", fmt_int(as_int(record["over_allotment_offer_shares"]))), ] if stage == T1_STAGE: rows.extend( [ - ("Public oversubscription", fmt_times(as_float(record["public_oversubscription_times"]))), - ("International oversubscription", fmt_times(as_float(record["international_oversubscription_times"]))), - ("Valid applications", fmt_int(as_int(record["valid_applications"]))), - ("Successful applications", fmt_int(as_int(record["successful_applications"]))), - ("Application success rate", fmt_pct_points(as_float(record["application_success_rate"]) * 100 if record["application_success_rate"] else None)), - ("International placees", fmt_int(as_int(record["international_placees"]))), - ("HK offer reallocation multiple", fmt_times(as_float(record["hk_offer_reallocation_multiple"]))), + ("公开认购倍数", fmt_times(as_float(record["public_oversubscription_times"]))), + ("国际配售认购倍数", fmt_times(as_float(record["international_oversubscription_times"]))), + ("有效申请数", fmt_int(as_int(record["valid_applications"]))), + ("成功申请数", fmt_int(as_int(record["successful_applications"]))), + ("申请成功率", fmt_pct_points(as_float(record["application_success_rate"]) * 100 if record["application_success_rate"] else None)), + ("国际配售承配人数", fmt_int(as_int(record["international_placees"]))), + ("香港公开发售回拨倍数", fmt_times(as_float(record["hk_offer_reallocation_multiple"]))), ] ) - lines = ["| Field | Value |", "| --- | --- |"] + lines = ["| 字段 | 数值 |", "| --- | --- |"] for label, value in rows: lines.append(f"| {label} | {value} |") return "\n".join(lines) @@ -292,36 +292,36 @@ def stage_calendar_table(record: dict[str, str]) -> str: application_end = fmt_value(record["application_end_date"]) allotment_date = fmt_value(record["allotment_results_expected_date"]) listing_date = fmt_value(record["listing_date"]) - if allotment_date != "n/a": - t2_date = f"{allotment_date} after allotment results" - elif listing_date != "n/a": - t2_date = "trading day before D1; exact date not archived" + if allotment_date != "未记录": + t2_date = f"{allotment_date} 分配结果公布后" + elif listing_date != "未记录": + t2_date = "D1 前一个交易日；精确日期未归档" else: - t2_date = "n/a" + t2_date = "未记录" rows = [ ( "T0_prospectus", - f"{application_start} to {application_end}", - "Subscription window; use prospectus and offer terms only.", + f"{application_start} 至 {application_end}", + "申购前/申购中阶段；只使用招股书和发行条款。", ), ( "T1_allotment", allotment_date, - "Allotment results day; use public demand, placing demand, and allocation facts.", + "分配结果日；使用公开认购热度、国际配售热度和分配事实。", ), ( "T2_grey_market", t2_date, - "Pre-listing grey-market sell window if a reliable executable source exists.", + "上市前暗盘窗口；只有存在可靠且可执行的数据源时才作为卖出依据。", ), ( "D1", listing_date, - "First official trading day; default sell window when T2 data is unavailable or unreliable.", + "正式上市首日；T2 数据不可用或不可靠时的默认卖出窗口。", ), ] - lines = ["| Stage | Concrete Date For This IPO | Meaning |", "| --- | --- | --- |"] + lines = ["| 阶段 | 本 IPO 对应日期 | 含义 |", "| --- | --- | --- |"] for stage, date_text, meaning in rows: lines.append(f"| `{stage}` | {date_text} | {meaning} |") return "\n".join(lines) @@ -340,29 +340,29 @@ def reason_lines(components: list[ScoreComponent], positive: bool) -> list[str]: filtered = [component for component in components if (component.points > 0 if positive else component.points < 0)] filtered.sort(key=lambda component: component.points, reverse=positive) if not filtered: - return ["- No material positive scoring component." if positive else "- No material negative scoring component."] - return [f"- {component_label(component.name)}: {component.points:+d} (`{component.reason}`)." for component in filtered[:5]] + return ["- 没有明显正向评分项。" if positive else "- 没有明显负向评分项。"] + return [f"- {component_label(component.name)}：{component.points:+d} (`{component.reason}`)。" for component in filtered[:5]] def missing_field_lines(record: dict[str, str], stage: str) -> list[str]: required = [ - ("industry_label", "industry label"), - ("market_cap_hkd_m", "market cap"), - ("min_subscription_amount_hkd", "minimum subscription"), + ("industry_label", "行业"), + ("market_cap_hkd_m", "市值"), + ("min_subscription_amount_hkd", "最低认购金额"), ] if stage == T1_STAGE: required.extend( [ - ("public_oversubscription_times", "public oversubscription"), - ("international_oversubscription_times", "international oversubscription"), - ("valid_applications", "valid applications"), - ("successful_applications", "successful applications"), + ("public_oversubscription_times", "公开认购倍数"), + ("international_oversubscription_times", "国际配售认购倍数"), + ("valid_applications", "有效申请数"), + ("successful_applications", "成功申请数"), ] ) missing = [label for key, label in required if not record.get(key)] if not missing: - return ["- No required report field is blank for this stage."] - return [f"- Missing or blank: {', '.join(missing)}."] + return ["- 本阶段必需字段没有明显空缺。"] + return [f"- 缺失或空白字段：{', '.join(missing)}。"] def build_report(record: dict[str, str], rows: list[dict[str, str]], stage: str, as_of: str) -> str: @@ -376,85 +376,82 @@ def build_report(record: dict[str, str], rows: list[dict[str, str]], stage: str, decision = t0_decision_band(score) components = parse_components(record["t0_score_breakdown"]) metric = bucket_metric(rows, "t0_score_bucket", bucket, require_t1=False) - score_label = "T0 score" else: score = as_int(record["total_score"]) or 0 bucket = record["total_score_bucket"] decision = record["decision_band"] components = parse_components(record["t0_score_breakdown"]) + parse_components(record["t1_score_breakdown"]) metric = bucket_metric(rows, "total_score_bucket", bucket, require_t1=True) - score_label = "Total score" paths = source_paths(record, stage) - source_lines = [f"- `{path}`" for path in paths] or ["- No source path recorded for this stage."] + source_lines = [f"- `{path}`" for path in paths] or ["- 本阶段没有记录来源路径。"] lines = [ - f"# {ticker} IPO Analyst Report", + f"# {ticker} IPO 分析报告", "", - "## Summary", + "## 摘要", "", - f"- Ticker: `{ticker}`", - f"- Company: {fmt_value(record['company_name_en'])}", - f"- Stage: `{stage}`", - f"- Report as of: `{as_of}`", - f"- Model dataset as of: `{dataset_as_of}`", - f"- Rule version: `{model_version}`", - f"- Rule path: `{MODEL_RULE_PATH.as_posix()}`", - "- Strategy horizon: short IPO subscription trade; intended exit is T2 grey market if reliable, otherwise D1.", - f"- Decision: `{decision}`", - f"- PM action: {action_for_decision(decision)}", - f"- {score_label}: `{score}`", - f"- Score bucket: `{bucket}`", - f"- Calibrated D1 positive probability: {fmt_pct_rate(metric.d1_positive_rate)} from {metric.sample_size} historical D1 labels", + f"- 股票代码：`{ticker}`", + f"- 公司：{fmt_value(record['company_name_en'])}", + f"- 分析阶段：`{stage}`", + f"- 报告生成时间：`{as_of}`", + f"- 模型数据时间：`{dataset_as_of}`", + f"- 规则版本：`{model_version}`", + f"- 规则路径：`{MODEL_RULE_PATH.as_posix()}`", + "- 策略周期：短线 IPO 申购交易；优先在可靠 T2 暗盘卖出，否则默认 D1 卖出。", + f"- 结论代码：`{decision}`", + f"- 执行动作：{action_for_decision(decision)}", + f"- {'T0 分数' if stage == T0_STAGE else '总分'}：`{score}`", + f"- 分数分桶：`{bucket}`", + f"- 历史校准 D1 正收益概率：{fmt_pct_rate(metric.d1_positive_rate)}，样本数 {metric.sample_size}", "", - "## Stage Calendar", + "## 阶段日期表", "", stage_calendar_table(record), "", - "## Facts", + "## 基础事实", "", facts_table(record, stage), "", - "## Short-Exit Model Inference", + "## 短线退出模型推断", "", - f"- D1 positive probability: {fmt_pct_rate(metric.d1_positive_rate)}", - f"- D1 >= 10% probability: {fmt_pct_rate(metric.d1_strong_rate)}", - f"- Historical average D1 return for bucket: {fmt_num(metric.average_d1_return_pct, '%')}", - f"- Historical median D1 return for bucket: {fmt_num(metric.median_d1_return_pct, '%')}", - "- T2 sell return is not modeled until an approved grey-market data source exists.", - "- D5/D20/D60 outcomes are review labels only, not holding targets.", + f"- D1 正收益概率：{fmt_pct_rate(metric.d1_positive_rate)}", + f"- D1 涨幅不低于 10% 概率：{fmt_pct_rate(metric.d1_strong_rate)}", + f"- 同分桶历史 D1 平均收益：{fmt_num(metric.average_d1_return_pct, '%')}", + f"- 同分桶历史 D1 中位收益：{fmt_num(metric.median_d1_return_pct, '%')}", + "- T2 暗盘卖出收益暂未建模，直到项目确认可靠暗盘数据源。", + "- D5/D20/D60 只作为复盘标签，不是持仓目标。", "", - "## Score Breakdown", + "## 评分拆解", "", components_table(components), "", - "## Bull Points", + "## 正面因素", "", *reason_lines(components, positive=True), "", - "## Risks And Gaps", + "## 风险与缺口", "", *reason_lines(components, positive=False), *missing_field_lines(record, stage), - "- T2 grey-market signal is not used yet because the project has no approved reproducible source.", - "- Post-listing D5/D20/D60 outcomes are labels for later review only and are not holding-period targets.", + "- T2 暗盘信号暂未使用，因为项目还没有批准可复现的数据源。", + "- 上市后的 D5/D20/D60 表现只用于后续复盘，不是本模型的持仓周期目标。", "", - "## Triggers", + "## 触发条件", "", - "- Upgrade: stronger verified T1 demand, better allocation scarcity, or a new rule-backed positive catalyst.", - "- Downgrade: weak public or international demand, oversized supply, low-quality missing fields, or adverse market window.", + "- 上调：T1 认购热度显著更强、分配稀缺性更好，或出现有规则支持的新正面催化。", + "- 下调：公开或国际需求偏弱、供给过大、关键字段质量不足，或市场窗口明显转差。", "", - "## Exit Plan", + "## 退出计划", "", - "- If subscribed and allocated, plan to sell in T2 grey market when reliable executable data is available.", - "- If T2 is unavailable or unreliable, use D1 as the default exit window.", - "- Do not treat D5/D20/D60 as planned holding periods for this model.", - "- Record D1/D5/D20/D60 outcomes later as review labels, not as retroactive prediction inputs.", + "- 如果申购并获配，且 T2 暗盘数据可靠且可执行，优先按 T2 暗盘卖出计划处理。", + "- 如果 T2 不可用或不可靠，默认使用 D1 作为卖出窗口。", + "- 不把 D5/D20/D60 作为本模型的计划持仓周期。", + "- 后续记录 D1/D5/D20/D60 结果时，只作为复盘标签，不作为倒推预测输入。", "", - "## Source Paths", + "## 来源路径", "", *source_lines, - "", ] return "\n".join(lines)