macro-regime-detector

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Original

English

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Translation

Chinese

Macro Regime Detector

宏观市场状态检测器

Detect structural macro regime transitions using monthly-frequency cross-asset ratio analysis. This skill identifies 1-2 year regime shifts that inform strategic portfolio positioning.

通过月度频率的跨资产比率分析检测结构性宏观市场状态转换。本工具可识别1-2年周期的状态转换，为战略性投资组合配置提供依据。

When to Use

使用场景

User asks about current macro regime or regime transitions
User wants to understand structural market rotations (concentration vs broadening)
User asks about long-term positioning based on yield curve, credit, or cross-asset signals
User references RSP/SPY ratio, IWM/SPY, HYG/LQD, or other cross-asset ratios
User wants to assess whether a regime change is underway

用户询问当前宏观市场状态或状态转换情况
用户希望了解结构性市场轮动（集中vs扩张）
用户基于收益率曲线、信贷或跨资产信号询问长期配置策略
用户提及RSP/SPY比率、IWM/SPY、HYG/LQD或其他跨资产比率
用户希望评估是否正在发生市场状态变化

Workflow

工作流程

Load reference documents for methodology context:

references/regime_detection_methodology.md

references/indicator_interpretation_guide.md

Execute the main analysis script:
bash
```
python3 skills/macro-regime-detector/scripts/macro_regime_detector.py
```
This fetches 600 days of data for 9 ETFs + Treasury rates (10 API calls total).
Read the generated Markdown report and present findings to user.
Provide additional context using
```
references/historical_regimes.md
```
when user asks about historical parallels.

加载方法论相关的参考文档：

references/regime_detection_methodology.md

references/indicator_interpretation_guide.md

执行主分析脚本：
bash
```
python3 skills/macro-regime-detector/scripts/macro_regime_detector.py
```
该脚本会获取9只ETF+国债利率的600天数据（共10次API调用）。
读取生成的Markdown报告并向用户展示结果。
当用户询问历史相似情况时，使用
```
references/historical_regimes.md
```
提供额外背景信息。

Prerequisites

前置条件

FMP API Key (required): Set
```
FMP_API_KEY
```
environment variable or pass
```
--api-key
```
Free tier (250 calls/day) is sufficient (script uses ~10 calls)

FMP API Key（必填）：设置
```
FMP_API_KEY
```
环境变量或通过
```
--api-key
```
参数传入
免费 tier（每日250次调用）已足够（脚本约使用10次调用）

6 Components

6大核心组件

#	Component	Ratio/Data	Weight	What It Detects
1	Market Concentration	RSP/SPY	25%	Mega-cap concentration vs market broadening
2	Yield Curve	10Y-2Y spread	20%	Interest rate cycle transitions
3	Credit Conditions	HYG/LQD	15%	Credit cycle risk appetite
4	Size Factor	IWM/SPY	15%	Small vs large cap rotation
5	Equity-Bond	SPY/TLT + correlation	15%	Stock-bond relationship regime
6	Sector Rotation	XLY/XLP	10%	Cyclical vs defensive appetite

序号	组件	比率/数据	权重	检测内容
1	市场集中度	RSP/SPY	25%	大盘股集中vs市场扩张
2	收益率曲线	10Y-2Y利差	20%	利率周期转换
3	信贷环境	HYG/LQD	15%	信贷周期风险偏好
4	规模因子	IWM/SPY	15%	小盘股vs大盘股轮动
5	股债关系	SPY/TLT + 相关性	15%	股债关系状态
6	行业轮动	XLY/XLP	10%	周期vs防御板块偏好

5 Regime Classifications

5种市场状态分类

Concentration: Mega-cap leadership, narrow market
Broadening: Expanding participation, small-cap/value rotation
Contraction: Credit tightening, defensive rotation, risk-off
Inflationary: Positive stock-bond correlation, traditional hedging fails
Transitional: Multiple signals but unclear pattern

Concentration（集中状态）：大盘股领涨，市场行情狭窄
Broadening（扩张状态）：市场参与度提升，小盘股/价值股轮动
Contraction（收缩状态）：信贷收紧，防御板块轮动，风险规避
Inflationary（通胀状态）：股债正相关，传统对冲失效
Transitional（过渡状态）：多信号但模式不清晰

Output

输出结果

```
macro_regime_YYYY-MM-DD_HHMMSS.json
```
— Structured data for programmatic use
```
macro_regime_YYYY-MM-DD_HHMMSS.md
```
— Human-readable report with:
1. Current Regime Assessment
2. Transition Signal Dashboard
3. Component Details
4. Regime Classification Evidence
5. Portfolio Posture Recommendations

```
macro_regime_YYYY-MM-DD_HHMMSS.json
```
— 供程序化使用的结构化数据
```
macro_regime_YYYY-MM-DD_HHMMSS.md
```
— 面向人类阅读的报告，包含：
1. 当前市场状态评估
2. 转换信号仪表盘
3. 组件详情
4. 状态分类依据
5. 投资组合配置建议

Relationship to Other Skills

与其他工具的关系

Aspect	Macro Regime Detector	Market Top Detector	Market Breadth Analyzer
Time Horizon	1-2 years (structural)	2-8 weeks (tactical)	Current snapshot
Data Granularity	Monthly (6M/12M SMA)	Daily (25 business days)	Daily CSV
Detection Target	Regime transitions	10-20% corrections	Breadth health score
API Calls	~10	~33	0 (Free CSV)

维度	Macro Regime Detector	Market Top Detector	Market Breadth Analyzer
时间周期	1-2年（结构性）	2-8周（战术性）	当前快照
数据粒度	月度（6M/12M SMA）	每日（25个交易日）	每日CSV
检测目标	状态转换	10-20%回调	市场广度健康评分
API调用次数	~10	~33	0（免费CSV）

Script Arguments

脚本参数

bash

python3 macro_regime_detector.py [options]

Options:
  --api-key KEY       FMP API key (default: $FMP_API_KEY)
  --output-dir DIR    Output directory (default: current directory)
  --days N            Days of history to fetch (default: 600)

bash

python3 macro_regime_detector.py [options]

Options:
  --api-key KEY       FMP API key (default: $FMP_API_KEY)
  --output-dir DIR    输出目录（默认：当前目录）
  --days N            要获取的历史数据天数（默认：600）