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Skillsmarket-trend-style-analysis

market-trend-style-analysis

Data & analytics

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Updated 10-15 19:55

About this skill

Market Trend & Style Analysis

Overview

This skill is designed specifically forsecurities strategy researchers, aiming to provide systematicmarket trend assessmentandstyle allocation recommendations. Through comprehensive analysis of volume-price trends, liquidity environment, market sentiment and macroeconomic factors, it quantitatively evaluates market conditions, outputs clear index direction judgments, style strength rankings and dynamic position recommendations to assist investment decisions.

All data queries must use the gildata-aidata service。

Core Analysis Framework

1. Trend & Direction Model

  • Volume-Price Trend: Moving average system (bullish/bearish alignment), key support/resistance levels, volume-price coordination (rising on increased volume/falling on decreased volume).
  • Liquidity: Macro liquidity (M1/M2 scissors gap, social financing growth), micro liquidity (northbound capital, ETF subscription/redemption, margin balance).
  • Sentiment Cycle: Turnover rate, new account openings, equity public fund issuance, option implied volatility (IV).
  • Assessment Conclusion: 🟢 Bull market/uptrend, 🟡 Range-bound market/structural行情, 🔴 Bear market/downtrend.

2. Style Strength Ranking (Style Rotation)

  • Large-cap vs Small-cap:
    • Logic: Credit expansion periods favor small-caps (ample liquidity), credit contraction periods favor large-caps (certainty premium).
    • Indicators: Credit impulse, interest rate trend, micro-cap stock liquidity risk.
  • Growth vs Value:
    • Logic: Falling interest rates/earnings recovery favor growth, rising interest rates/stagflation favor value (dividends).
    • Indicators: 10-year government bond yield, earnings growth differential (growth - value), risk appetite.
  • Style Matrix:
    • Large-cap Value (Dividends/Financials)
    • Large-cap Growth (Mao Index/Core Assets)
    • Small-cap Value (Cyclicals/Resources)
    • Small-cap Growth (STAR Market/Micro-cap)

3. Position Sizing Model

  • Scoring System: A comprehensive score of 0-100 derived from overall trend, style and risk indicators.
  • Position Mapping:
    • 80-100 points (High position): Uptrend + loose liquidity + recovering sentiment -> Recommended position 70-100%
    • 50-80 points (Medium position): Range-bound market + structural opportunities -> Recommended position 40-70%
    • 0-50 points (Low position): Downtrend + tightening liquidity + freezing sentiment -> Recommended position 0-40%

Data Collection Guide (gildata-aidata tool mapping)

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

Index Quotes and Technicals

finx gildata-aidata IndexLiveQuote --body '{"indexCode": "指数代码"}'

Obtain real-time A-share index quotes, including price-volume, change percentage, order ratio and other indicators.

finx gildata-aidata IndexDailyQuote --body '{"indexCode": "指数代码", "tradeDate": "交易日期"}'

Retrieve daily market data for A-share indices, including price and volume, price change percentage, turnover rate, and other indicators.

finx gildata-aidata IndexRangeQuotation --body '{"indexCode": "指数代码", "startDate": "开始日期", "endDate": "结束日期"}'

Retrieve market data for A-share indices within a specified interval, such as interval price change percentage, trading value, and more.

finx gildata-aidata IndexQuoteTecIndicators --body '{"indexCode": "指数代码", "tradeDate": "交易日期"}'

Retrieve index technical indicators, such as MA, MACD, KDJ, BOLL, and other analytical data.

Index valuation analysis

finx gildata-aidata IndexValueAnalysis --body '{"indexCode": "指数代码", "tradeDate": "交易日期"}'

Retrieve index valuation indicators, such as PE, PB, dividend yield, PE historical percentile, and more.

Index capital flows

finx gildata-aidata IndexCapitalFlow --body '{"indexCode": "指数代码", "tradeDate": "交易日期"}'

Retrieve daily capital inflow and outflow for indices.

Overall market trading statistics

finx gildata-aidata StockMarketTradeStats --body '{"tradeDate": "交易日期"}'

Retrieve trading statistics for the Shanghai, Shenzhen, and Beijing markets, including trading volume, trading value, number of trades, and more.

finx gildata-aidata StockMarketSizeStats --body '{"tradeDate": "交易日期"}'

Retrieve scale data for listed companies in sectors of the Shanghai, Shenzhen, and Beijing markets, including number of companies, share capital, market value, and more.

finx gildata-aidata StockMarketValueAnalysis --body '{"tradeDate": "交易日期"}'

Retrieve stock market valuation indicators, such as PE, PB, PS, PCF, and more.

Market capital flows

finx gildata-aidata StockMarketCapitalFlow --body '{"tradeDate": "交易日期"}'

Retrieve daily statistical data on capital inflows and outflows for the Shanghai, Shenzhen, and Beijing markets.

finx gildata-aidata MarketFundFlowRank --body '{"tradeDate": "交易日期"}'

Rank constituent stocks of the Shanghai, Shenzhen, and Beijing markets by capital flow indicators, supporting multi-dimensional analysis.

Statistics on the number of limit-up and limit-down companies

finx gildata-aidata MarketLimitUpDownCount --body '{"tradeDate": "交易日期"}'

Retrieve real-time statistics on the number of advancing, declining, limit-up, and limit-down companies in the Shanghai, Shenzhen, and Beijing markets.

Margin trading market statistics

finx gildata-aidata MarginTradeStats --body '{"tradeDate": "交易日期"}'

Retrieve statistical data for the Shanghai, Shenzhen, and Beijing markets, including margin financing and securities lending balance, purchase amount, selling volume, and more.

Northbound capital (Shanghai-Shenzhen-Hong Kong Stock Connect)

finx gildata-aidata HSGTTradeStats --body '{"tradeDate": "交易日期"}'

Retrieve cross-border trading statistics for the Shanghai, Shenzhen, and Beijing markets, including Northbound and Southbound capital trading value, number of trades, and more.

Industry/Sector ranking and capital flow

finx gildata-aidata SectorRank --body '{"sectorType": "行业板块", "tradeDate": "交易日期"}'

Retrieve sector lists and sort by indicators such as price change percentage and turnover rate, supporting multiple sector types.

finx gildata-aidata SectorFundFlowRank --body '{"sectorType": "行业板块", "tradeDate": "交易日期"}'

Sort sectors by capital flow indicators, supporting analysis of main force and retail capital.

Industry valuation

finx gildata-aidata IndustryValuation --body '{"industryCode": "行业代码", "tradeDate": "交易日期"}'

Query industry valuation indicator data, including total market value, circulating market value, PB, PE, and more.

Macro and industry economic data

finx gildata-aidata MacroIndustryEDB --body '{"indicatorCode": "指标代码", "startDate": "开始日期", "endDate": "结束日期"}'

Query economic indicator data such as China macro, industry economy, international macro (e.g., M1, M2, social financing, PMI, etc.).

Macro/industry analysis views

finx gildata-aidata MacroeconomicAnalysisViewpoints --body '{"limit": 5}'

Retrieve analytical views from research reports on macro dimensions such as GDP, CPI, PMI, and policy.

finx gildata-aidata IndustryAnalysisViewpoints --body '{"industry": "行业名称", "limit": 5}'

Retrieve analytical views from research reports on industry trends, competitive landscape, policy, and more.

Execution process

  1. Data collection:

    • Use IndexDailyQuote / IndexRangeQuotation to retrieve market data for major indices (Shanghai Composite, Shenzhen Component, ChiNext, CSI 300, CSI 500, CSI 1000)
    • Use IndexQuoteTecIndicators to retrieve index technical indicators (moving averages, MACD, etc.)
    • Use IndexValueAnalysis to retrieve valuation and historical percentiles of major indices
    • Use HSGTTradeStats to retrieve Northbound capital flows
    • Use MarginTradeStats to retrieve changes in margin financing and securities lending balance
    • Use StockMarketTradeStats to retrieve market-wide trading value and volume
    • Use MarketLimitUpDownCount to retrieve the number of limit-up and limit-down companies
    • Use SectorRank / SectorFundFlowRank to retrieve industry sector price change percentage and capital flow rankings
    • Use MacroIndustryEDB to retrieve macro liquidity data (M1, M2, social financing, etc.)
    • Use MacroeconomicAnalysisViewpoints to retrieve macro analysis views

  2. Model analysis and scoring:

    • Use the above framework to conduct multi-dimensional diagnosis of the market
    • Calculate market trend score and style preference score

  3. Logical reasoning:

    • Explain the current market state in light of the macroeconomic backdrop (e.g., Merrill Lynch Clock position, policy cycle)
    • Predict the market trend and the possibility of style rotation over the next 1-3 months

  4. Report generation:

    • Generate a strategy research report in Markdown format; data must be accompanied by source and cutoff date

Report template (Markdown)

# 📈 市场大势与风格研判报告 | [日期]

> **数据来源**: gildata-aidata 专业金融数据服务
> **数据截止**: [具体日期]
> **大势研判**: [🟢 震荡偏强 / 🟡 震荡市 / 🔴 调整]
> **建议仓位**: [XX%]
> **核心风格**: [如：大盘价值占优，成长风格筑底]

---

## 一、 核心观点 (Executive Summary)

*   **大势判断**: [简述当前市场处于什么阶段，核心驱动力或阻力是什么]
*   **风格展望**: [明确当前及未来一段时间的最强风格，如"哑铃策略：红利打底，科技进攻"]
*   **操作建议**: [简述仓位管理和交易节奏，如"逢低布局，切忌追高"]

---

## 二、 大势研判 (Market Trend Analysis)

### 2.1 量价与技术面
*   **指数状态**: [描述主要指数的技术形态，基于 IndexDailyQuote 和 IndexQuoteTecIndicators 数据]
*   **成交量**: [描述量能变化，基于 StockMarketTradeStats 数据，是否支持指数突破]

### 2.2 资金与流动性
*   **宏观流动性**: [基于 MacroIndustryEDB 数据，解读社融、M1 等]
*   **微观资金**:
    *   北向资金：[基于 HSGTTradeStats 数据分析流向]
    *   两融数据：[基于 MarginTradeStats 分析杠杆情绪]
    *   主力资金：[基于 StockMarketCapitalFlow 分析]

### 2.3 情绪与风险
*   **情绪指标**: [基于 MarketLimitUpDownCount 分析涨跌停家数、炸板率]
*   **估值水平**: [基于 IndexValueAnalysis 和 StockMarketValueAnalysis 分析市场整体估值分位]
*   **风险预警**: [提示潜在风险点，如"高位股拥挤度过高"]

---

## 三、 风格强弱排序 (Style Ranking)

| 风格维度 | 强弱排序 (强 -> 弱) | 核心逻辑 |
|----------|---------------------|----------|
| **市值** | 大盘 > 小盘 | [如：流动性边际收敛，确定性溢价上升] |
| **属性** | 价值 > 成长 | [如：利率下行空间有限，红利资产性价比仍存] |
| **综合** | **大盘价值** > 小盘价值 > 大盘成长 > 小盘成长 | [综合排序结论] |

### 3.1 重点风格解析
*   **[最强风格]**: [详细分析为何该风格占优，结合 SectorFundFlowRank 资金数据]
*   **[最弱风格]**: [详细分析为何该风格承压，资金流出，利空因素]

---

## 四、 策略建议与仓位管理 (Strategy & Allocation)

*   **仓位建议**: **[建议仓位区间，如 50%-70%]**
    *   **依据**: [基于大势评分和风险提示]
*   **配置主线**:
    *   **主线 1**: [如：高股息红利（底仓配置）]
    *   **主线 2**: [如：出海/涨价（弹性进攻）]
*   **交易节奏**: [如：急跌买入，冲高减仓]

---

*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 market trend and style related data must be obtained through the gildata-aidata service to ensure data authority and consistency
  • Data timeliness: The latest market data must be used for analysis, and the data date must be noted in the report
  • Logical consistency: Market trend judgments and position recommendations must match (for example, if judged as a bear market trend, position recommendations should not be too high)
  • Dynamic adjustment: Style judgments must be adjusted promptly in light of changes in the macroeconomic environment (e.g., rate cuts, policy shifts)
  • Risk disclosure: Clearly point out extreme situations (black swans) that may invalidate the judgment
  • Tool invocation specification: When invoking the gildata-aidata tool, index codes and industry codes must use standard codes, and date formats must meet API requirements