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Skillsmacro-asset-allocation

macro-asset-allocation

Data & analytics

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Updated 10-15 19:55

About this skill

Macro Major Asset Class Allocation Skill

Overview

This skill simulates the major asset class allocation perspective of a macro strategy researcher, combines the latest macroeconomic data, policy forecasts, and market environment, and appliesthe Merrill Lynch Clockormacro quadrantsanalysis frameworks to automatically generate allocation recommendations for major asset classes such as equities, bonds, commodities, foreign exchange, and cash. The report is intended to provide professional investment institutions with logically supported allocation directions, weight recommendations, and risk alerts.

Data Acquisition Strategy

Core data source: gildata-aidata

All macroeconomic data, capital flows, index quotes, and market views are preferentially obtained through the gildata-aidata service.

Data Requirement Recommended Tool Description
Macroeconomic Indicators MacroIndustryEDB Core Tool. Query GDP, CPI, PPI, PMI, social financing, M2, industrial value added, etc., to determine the economic cycle quadrant (recovery/overheating/stagflation/recession).
Index Quotes IndexRangeQuotation Obtain recent gains and losses for the CSI 300, China Bond Composite, Nanhua Commodity Index, etc., to assess asset performance.
Capital Flows HSGTTradeStats, StockMarketCapitalFlow Obtain northbound capital, margin financing and securities lending balances, etc., to help judge stock market capital sentiment.
Macro Analysis Views MacroeconomicAnalysisViewpoints Obtain analytical views on the macroeconomy from research reports to assist cross-validation.
Overseas Macro MacroIndustryEDB (International Macro) Obtain data on major US and European economies to assist global macro linkage analysis.
Policy and Public Opinion PolicyMeetingsList, MacroNewslist Obtain major meeting resolutions and macro public opinion.

Data Acquisition Priority

  1. Cycle determination data: prioritize gildata-aidata MacroIndustryEDB(obtain growth and inflation data).
  2. Asset performance data: prioritize gildata-aidata IndexRangeQuotation。
  3. Capital and sentiment: prioritize gildata-aidata HSGTTradeStats。
  4. Supplementary information：web_search is used only to supplement details of sudden overseas policy or spot prices of specific commodities.

Execution Process

Phase 1: Macro Quadrant Determination and Cycle Positioning

  1. Core Macro Data Retrieval

    • Tool：gildata-aidata MacroIndustryEDB
    • Query Example： 
      调用 gildata-aidata MacroIndustryEDB
query: "GDP 同比 CPI 同比 PPI 同比 PMI 社融存量增速 M2 增速"
time_range: "最近 6 个月"
    • Growth dimension: GDP growth trend, PMI position relative to the boom-or-bust line, changes in social financing/M2 growth.
    • Inflation dimension: CPI (core/headline) trend, PPI trend.
    • Liquidity dimension: DR007, SHIBOR, net liquidity injection from central bank open market operations.

  2. Merrill Lynch Clock Positioning Based on the direction of marginal changes in growth and inflation, determine the current economic cycle position:

    • Recovery phase(Growth ↑ Inflation ↓): Corporate earnings improve, liquidity is ample.Stocks > Bonds > Commodities > Cash。
    • Overheating Phase(Growth ↑ Inflation ↑): The central bank tightens liquidity, with a focus on combating inflation.Commodities > Stocks > Cash/Bonds。
    • Stagflation Phase(Growth ↓ Inflation ↑): Corporate earnings deteriorate, inflation remains high.Cash > Commodities/Bonds > Stocks。
    • Recession Phase(Growth ↓ Inflation ↓): The central bank eases liquidity, and a bond bull market begins.Bonds > Cash > Stocks > Commodities。

Phase Two: In-Depth Analysis of Major Asset Classes

  1. Equity Assets (Stocks)

    • Valuation and Earnings: PE/PB percentiles of the All-A or major indices (CSI 300, ChiNext Index), earnings growth expectations (EPS).
    • Fund Flows: Northbound capital flows, changes in margin financing and securities lending balances, scale of newly issued funds.
    • Style Assessment: Large-cap vs. small-cap, growth vs. value, combined with the macroeconomic environment (e.g., growth-oriented during recovery, value-oriented during stagflation).

  2. Fixed-Income Assets (Bonds)

    • Interest Rate Environment: 10Y government bond yield trends and percentiles, China-US interest rate spread.
    • Credit Risk: Changes in credit spreads, monitoring of default events.
    • Allocation Recommendations: Duration strategy (long/short), leverage strategy, whether to pursue credit diversification.

  3. Commodities and Alternative Assets

    • Industrial Metals: Driven by the global manufacturing PMI and domestic infrastructure/real estate investment.
    • Precious Metals (Gold): Driven by real interest rates (US Treasury yields - inflation expectations) and safe-haven sentiment.
    • Crude Oil: Affected by supply-demand dynamics (OPEC+ production cuts, global economic expectations) and geopolitics.
    • Foreign Exchange: US dollar index trends, RMB exchange rate (onshore/offshore) expectations.

Phase Three: Allocation Strategy Generation

  1. Tactical Asset Allocation (TAA) Recommendations

    • Based on the current cycle position, provide overweight/neutral/underweight recommendations.
    • Consider hedging strategies under extreme risk scenarios (e.g., tail risk hedging).

  2. Weight Recommendations and Logical Support

    • Provide recommended asset weight ranges (e.g., stocks 40-50%, bonds 30-40%, commodities 10%, cash 5%).
    • Elaborate on the allocation logic in detail.

Phase Four: Asset Allocation Report Generation

  1. Generate a Markdown Format Report

    Use the following template structure to generate the final report:

# 宏观大类资产配置建议报告

> 报告日期：YYYY-MM-DD
> 核心观点：[一句话总结，如：经济弱复苏，建议超配股票，标配债券]
> 宏观象限：[复苏 / 过热 / 滞胀 / 衰退]

---

## 一、宏观经济周期定位

### 1.1 核心宏观数据监控
| 指标类别 | 指标名称 | 最新值 | 趋势 | 信号 |
|---------|---------|-------|------|------|
| 增长 | GDP/PMI | | | |
| 通胀 | CPI/PPI | | | |
| 信用 | 社融/M2 | | | |

### 1.2 周期象限判定
- **当前位置**：[如：衰退向复苏过渡期]
- **判定依据**：（详细分析增长与通胀的组合特征...）

---

## 二、大类资产分析与建议

### 2.1 权益资产（股票）
- **配置评级**：[超配 / 标配 / 低配]
- **核心逻辑**：（盈利预期、估值分位、资金流向、政策催化...）
- **风格建议**：（大盘/小盘，成长/价值，红利/科技...）

### 2.2 固定收益（债券）
- **配置评级**：[超配 / 标配 / 低配]
- **核心逻辑**：（利率趋势、货币政策、信用环境...）
- **策略建议**：（久期长短、信用资质要求...）

### 2.3 商品与实物资产
- **配置评级**：[超配 / 标配 / 低配]
- **核心逻辑**：（供需格局、通胀预期、地缘风险...）
- **细分品种**：（黄金、原油、铜等...）

### 2.4 现金与外汇
- **配置评级**：[超配 / 标配 / 低配]
- **核心逻辑**：（流动性充裕度、汇率预期...）

---

## 三、资产配置组合建议

### 3.1 建议权重
| 资产类别 | 建议权重 | 评级 | 备注 |
|---------|---------|------|------|
| 股票 | | | |
| 债券 | | | |
| 商品 | | | |
| 现金 | | | |

### 3.2 策略逻辑与风险提示
- **核心逻辑**：（总结为何这样配置...）
- **潜在风险**：（如：通胀超预期反弹、海外衰退拖累出口、政策收紧不及预期等...）
- **动态调整触发条件**：（若出现什么信号，需调整配置...）

---

## 四、后续关注重点
- **关键数据**：（未来需跟踪的宏观指标...）
- **重大事件**：（重要会议、央行决议等...）

---

*免责声明：本报告基于公开数据与宏观分析框架生成，仅供参考，不构成投资建议。市场有风险，投资需谨慎。*

Notes

  • gildata-aidata Priority: All domestic macroeconomic data, fund flows, and market data should prioritize the use of the gildata-aidata service.
  • Rigorous Logic: Asset allocation recommendations must be derived from macroeconomic data; unsupported subjective forecasts are strictly prohibited.
  • Dynamic Perspective: Emphasize "marginal changes" rather than absolute levels (e.g., focus on whether PMI is rising or falling, not merely whether it is above 50).
  • Risk Disclosure: Must include risk warnings that the allocation strategy may fail (such as black swan events).
  • Professional expression: Use professional terminology (such as "equity-bond cost-effectiveness", "term spread", "credit downgrade", "real interest rate", etc.).

Example invocation

User input: "How should assets be allocated in the current macroeconomic environment?"

Skill execution:

  1. Obtain macroeconomic data: gildata-aidata MacroIndustryEDB (query GDP, CPI, PPI, PMI, social financing, etc.)
  2. Obtain index quotes: gildata-aidata IndexRangeQuotation (query CSI 300, treasury bond index performance)
  3. Obtain capital flows: gildata-aidata HSGTTradeStats (query northbound capital)
  4. Obtain macroeconomic views: gildata-aidata MacroeconomicAnalysisViewpoints
  5. Determine the cycle quadrant: based on the data, determine which stage of the Merrill Lynch clock it is in
  6. Write the report: generate a Markdown-format asset allocation report according to the template
  7. Output the report: display the complete report content directly in the conversation

Output requirements

  • The report uses standard Markdown format
  • Must include the Merrill Lynch clock/macro quadrant determination
  • Must provide ratings for each major asset class (overweight/neutral/underweight) and recommended weights
  • The report length should be controlled at 2000-3000 characters
  • The language should be professional and objective, suitable for institutional investors' asset allocation reference

Skill update log

Updated on 2026-05-11：

  • Core data source changes: Fully integrated with gildata-aidata services.
  • Clear tool mapping: Added MacroIndustryEDB(macro cycle determination),IndexRangeQuotation(asset performance),HSGTTradeStats(capital conditions) and other tool mappings.
  • Process optimization: Clarified the logic flow of first obtaining Gildata macroeconomic data to determine the cycle, then combining capital and market data to generate allocation recommendations.