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Skillsmarket-minimal-review

market-minimal-review

Data & analytics

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Updated 10-15 19:55

About this skill

Market Minimal Review & Alerts

Overview

This skill is designed specifically forsecurities financial engineering researchers, aiming to providedata-driven minimal market review. By automatically capturing core market data, capital flow, volatility, and quantitative anomaly data, it generates standardized morning meeting briefing materials and post-market anomaly alerts, helping researchers quickly grasp market microstructure and quantitative signals, and assisting investment decisions.

All data queries must use the gildata-aidata service。

Core Analysis Framework

1. Minimal Market Recap

  • Broad-based indices: Shanghai Composite, Shenzhen Component, ChiNext, STAR 50, Beijing 50 price changes and turnover changes.
  • Style indices: Large-cap/small-cap (CSI 300 vs CSI 1000), growth/value performance comparison.
  • Market breadth: Advance/decline ratio, limit-up/limit-down counts, consecutive limit-up height (market sentiment thermometer).

2. Capital & Microstructure

  • Northbound capital: Net buying/selling amount, key industries increased/decreased (foreign capital wind vane).
  • Margin trading data: Changes in margin financing balance, margin buying ratio (leveraged capital sentiment).
  • ETF subscription and redemption: Broad-based ETF capital flows (such as CSI 300 ETF, CSI 500 ETF, etc., national team/institutional movements).
  • Main capital: Top five sectors by net inflow/outflow.

3. Volatility & Sentiment

  • Volatility indicators: VIX (China volatility index), option implied volatility (IV) changes.
  • Sentiment indicators: Turnover rate, failed limit-up rate, yesterday's limit-up performance (limit-up sentiment).
  • Crowding: Crowding warnings for popular sectors (such as AI, new energy with excessively high turnover share).

4. Quant Alerts

  • Price-volume anomalies: Volume breakout above key resistance, low-volume pullback to support, sudden volume surge at the bottom.
  • Capital anomalies: Large institutional net buying, substantial northbound capital buying, institutional premium on the dragon-tiger list.
  • Event-driven: Sector anomalies triggered by intraday breaking news and sustainability assessment.

Data Collection Guide (gildata-aidata tool mapping)

All data must be obtained through the gildata-aidata service, specific tool calls are as follows:

Core index quotes and market breadth

finx gildata-aidata IndexDailyQuote --body '{"query": "查询最新交易日上证综指、深证成指、创业板指、科创50、沪深300、中证1000的收盘价、涨跌幅、成交额"}'

Obtain daily quote data for major broad-based and style indices.

finx gildata-aidata MarketLimitUpDownCount --body '{"query": "查询最新交易日沪深京市场上涨家数、下跌家数、涨停家数、跌停家数"}'

Obtain real-time market limit-up/limit-down count statistics for calculating market breadth.

finx gildata-aidata StockMarketTradeStats --body '{"query": "查询最新交易日沪深北市场总成交额、成交量"}'

Obtain overall market trading statistics.

Capital flow and microstructure

finx gildata-aidata HSGTTradeStats --body '{"query": "查询最新交易日沪深港通北向资金净买入额、成交额"}'

Obtain daily trading statistics for northbound capital (Stock Connect).

finx gildata-aidata MarginTradeStats --body '{"query": "查询最新交易日沪深北市场融资余额、融券余额、融资买入额"}'

Obtain margin trading market statistics.

finx gildata-aidata SectorFundFlowRank --body '{"query": "查询最新交易日行业板块主力资金净流入前5名和净流出前5名"}'

Rank sectors by capital flow indicators to identify main capital reallocation direction.

Volatility and sentiment indicators

finx gildata-aidata IndexValueAnalysis --body '{"query": "查询上证指数、创业板指的最新PE、PB、波动率指标"}'

Assist in assessing market valuation and risk levels.

finx gildata-aidata StockRiskAnalysis --body '{"query": "查询市场整体或代表性指数的波动率、夏普比率等风险指标"}'

Obtain changes in market risk indicators.

Execution Process

  1. Data Collection:
    • Use IndexDailyQuote to obtain core index closing data, price changes, and trading volume.
    • Use MarketLimitUpDownCount to obtain the number of limit-up and limit-down stocks, and the advance-decline ratio.
    • Use HSGTTradeStats to obtain northbound capital flow data.
    • Use MarginTradeStats to obtain changes in margin financing and securities lending balances.
    • Use SectorFundFlowRank to obtain rankings of net capital inflow/outflow by industry sector.
  2. Signal Calculation and Analysis:
    • Calculate market breadth indicators (such as the proportion of advancing stocks).
    • Identify extreme values in capital flows (such as northbound net buying exceeding 10 billion in a single day).
    • Assess volatility percentiles and sentiment hot/cold levels.
  3. Anomaly Identification:
    • Screen for sectors with abnormal price-volume coordination or significant capital reallocation.
    • Flag extreme signals of overheated or overly cold sentiment.
  4. Report Generation:
    • Generate a minimalist Markdown-format review and anomaly briefing.

Report Template (Markdown)

# 📊 市场极简复盘与异动简报 | [日期]

> **数据来源**: gildata-aidata 专业金融数据服务
> **核心观点**: [一句话总结当日市场特征，如：缩量震荡，北向大幅加仓红利，微盘股情绪退潮]

---

## 一、 市场概况 (Market Overview)

| 指数 | 收盘价 | 涨跌幅 | 成交额 (亿) | 环比变化 |
|------|--------|--------|-------------|----------|
| 上证指数 | ... | ... | ... | ... |
| 深证成指 | ... | ... | ... | ... |
| 创业板指 | ... | ... | ... | ... |
| 科创 50 | ... | ... | ... | ... |

*   **市场广度**: 上涨 [XX] 家，下跌 [XX] 家，涨停 [XX] 家，跌停 [XX] 家。
*   **风格表现**: [如：大盘强于小盘，价值优于成长]

---

## 二、 资金与微观结构 (Capital Flow)

*   **🌍 北向资金**: 净买入/卖出 **[XX] 亿元**。
    *   *重点动向*: [如：大幅加仓家电、电力设备，减仓计算机]
*   **📈 两融数据**: 融资余额 **[XX] 亿元** (变动 [XX])，融资买入占比 **[XX]%**。
*   **🏦 ETF 申赎**:
    *   *净流入*: [如：沪深 300ETF 获净申购 50 亿]
    *   *净流出*: [如：中证 1000ETF 遭赎回 10 亿]
*   **💰 主力资金**:
    *   *净流入前三*: [行业 1]、[行业 2]、[行业 3]
    *   *净流出前三*: [行业 1]、[行业 2]、[行业 3]

---

## 三、 波动率与情绪 (Volatility & Sentiment)

*   **📊 波动率**: 市场波动率报 **[XX]**，[上升/下降]。
    *   *解读*: [如：期权隐含波动率回落，市场恐慌情绪缓解 / 波动率飙升，避险情绪升温]
*   **🔥 情绪指标**:
    *   *炸板率*: **[XX]%** (市场情绪 [强/弱])
    *   *昨日涨停表现*: **[XX]%** (赚钱效应 [好/差])
*   **⚠️ 拥挤度预警**:
    *   [如：AI 板块成交额占比突破 40%，进入极度拥挤区，警惕回调]

---

## 四、 🚨 量化异动提醒 (Quant Alerts)

### 4.1 板块异动
*   **[板块名称]**: [异动描述，如：午后突然放量拉升，成交额激增 200%]
    *   *驱动逻辑*: [如：传闻政策利好 / 龙头业绩超预期]
    *   *持续性评估*: [⭐⭐⭐ 高 / ⭐⭐ 中 / ⭐ 低]

### 4.2 资金异动
*   **[个股/板块]**: [异动描述，如：北向资金单日净买入超 5 亿，创近一个月新高]
    *   *信号含义*: [如：外资认可当前估值，中线资金入场]

### 4.3 量价异动
*   **[指数/个股]**: [异动描述，如：缩量回踩 20 日均线，获得支撑]
    *   *技术含义*: [如：洗盘结束，有望开启新一轮上涨]

---

## 五、 明日关注 (Watchlist)

1.  **宏观数据/事件**: [如：美联储议息会议、国内 LPR 报价、XX 行业重要会议]
2.  **技术关键位**: [如：上证指数 4100 点压力位，创业板 3700 点支撑位]
3.  **策略建议**: [如：关注业绩超预期方向，回避高位缩量题材]

---

*免责声明：本报告基于 gildata-aidata 公开数据和量化模型生成，仅供参考，不构成投资建议。*

Notes

  • Data Source Uniqueness: All index quotes, capital flows, limit-up/limit-down statistics, and volatility data must be obtained through the gildata-aidata service to ensure data authority and consistency.
  • Minimalist Principle: The report should focus on core data and anomaly signals, avoiding lengthy fundamental analysis, and be suitable for quick reading.
  • Anomaly Explanation: For quantitative anomalies, try to provide reasonable explanations based on market news or capital behavior, avoiding "anomalies for the sake of anomalies."
  • Crowding Threshold: Crowding warnings for popular tracks need to be dynamically adjusted based on historical data to avoid false alarms.
  • Timeliness: Ensure the data is the latest closing or intraday real-time data (depending on the trigger time).