All-Weather Strategy - Prompt de Análisis IA
Use this Ray Dalio rule prompt to apply “Estrategia para Todo Clima” to a specific company. It turns a vague opinion into a repeatable checklist: what facts you must verify, which assumptions matter most, what would invalidate the thesis, and the common misreads that create false certainty. Expect a written output you can save: a thesis summary, key risks, and next-step questions for filings and earnings calls. If a claim matters, require primary-source citations before you act. Educational only — not investment advice.
Prompt completo
Eres un analista de inversiones entrenado en el principio de Ray Dalio: "All-Weather Strategy". Tu tarea es analizar {Nombre de la Empresa} a través de esta perspectiva específica.
## Contexto
Ray Dalio enseña: "Structure your portfolio to perform well across all economic environments - growth, recession, inflation, and deflation."
## Marco de Análisis
### 1. Evaluación de Aplicación del Principio
- ¿Cómo se aplica específicamente este principio a {Nombre de la Empresa}?
- ¿Qué aspectos de la empresa son más relevantes para "All-Weather Strategy"?
- Califica la alineación: Fuerte / Moderada / Débil
- ¿En qué se enfocaría Ray Dalio primero?
### 2. Evidencia Cuantitativa
- Identifica 3-5 métricas financieras clave relevantes
- Analiza estas métricas durante los últimos 5-10 años
- Compara con competidores y benchmarks históricos
- ¿Los números están mejorando, estables o deteriorándose?
### 3. Análisis Cualitativo
- Evalúa factores no cuantificables que Ray Dalio examinaría
- Calidad de la gestión y alineación con este principio
- Dinámica de la industria y posición competitiva
- Sostenibilidad del modelo de negocio desde esta perspectiva
### 4. Evaluación de Riesgos
- ¿Qué riesgos destaca este principio para {Nombre de la Empresa}?
- ¿Qué señales de advertencia identificaría Ray Dalio?
- Prueba de estrés: ¿Cómo se desempeñaría bajo condiciones adversas?
- ¿Cuál es el peor escenario desde esta perspectiva?
### 5. Identificación de Oportunidades
- ¿Qué oportunidades revela este análisis?
- ¿Hay fortalezas ocultas que el mercado podría estar subvalorando?
- ¿Qué catalizadores podrían liberar valor?
### 6. Dalio Verdict
- ¿{Nombre de la Empresa} pasa la prueba de "All-Weather Strategy"?
- Calificación: 1-10
- Recomendación clara: Comprar / Mantener / Evitar
- Resumen en un párrafo
## Formato de Salida
Presenta datos específicos en cada sección. Termina con un veredicto decisivo.Related reading (close the loop)
Pick one path below to turn the output into a checkable, repeatable decision policy.
- Read the matching principleDefinition, boundaries, pitfalls, and a minimal checklist.
- Master profileMethodology summary + common misreads for this framework.
- Practice in scenariosTranslate conclusions into “what I do under stress”.
- More prompts from this masterTriangulate with multiple rules instead of anchoring on one prompt.
Educational only. Verify facts with primary sources and apply your own constraints.
Este contenido solo está disponible en chino e inglés por el momento.
Basic Questions
How does the all-weather portfolio make money in any economic environment?
Dalio divides economic environments into four and allocates corresponding assets:
📊 Four-quadrant framework:
1. Rising growth + Rising inflation → Commodities, TIPS
2. Rising growth + Falling inflation → Stocks
3. Falling growth + Rising inflation → TIPS, Gold
4. Falling growth + Falling inflation → Government bonds
🎯 Core idea:
- You don't know which environment is coming, so prepare for all
- Risk parity: Each environment's assets contribute equal risk
- Goal is 'never too bad in any situation,' not 'best in one situation'
📊 Four-quadrant framework:
1. Rising growth + Rising inflation → Commodities, TIPS
2. Rising growth + Falling inflation → Stocks
3. Falling growth + Rising inflation → TIPS, Gold
4. Falling growth + Falling inflation → Government bonds
🎯 Core idea:
- You don't know which environment is coming, so prepare for all
- Risk parity: Each environment's assets contribute equal risk
- Goal is 'never too bad in any situation,' not 'best in one situation'
Usage Tips
Is the AI's 1-10 rating reliable?
⚠️ The All Weather score measures "portfolio environmental adaptability," not the quality of individual assets.
The rating's unique value:
- Helps you understand your portfolio's vulnerability across four quadrants: growth above/below expectations x inflation above/below expectations
- A high score means the portfolio has reasonable hedges across multiple economic environments, not that returns will be maximized
- Compare All Weather scores across different allocation schemes to find the optimal risk balance
Core limitations:
- The All Weather strategy pursues robustness over maximum returns — in any single environment, concentrated allocation may outperform
- AI's macro environment assessment is based on historical patterns; future economic quadrants may present unprecedented combinations
- Historical correlations may break down under extreme market conditions ("all assets declining simultaneously")
The rating's unique value:
- Helps you understand your portfolio's vulnerability across four quadrants: growth above/below expectations x inflation above/below expectations
- A high score means the portfolio has reasonable hedges across multiple economic environments, not that returns will be maximized
- Compare All Weather scores across different allocation schemes to find the optimal risk balance
Core limitations:
- The All Weather strategy pursues robustness over maximum returns — in any single environment, concentrated allocation may outperform
- AI's macro environment assessment is based on historical patterns; future economic quadrants may present unprecedented combinations
- Historical correlations may break down under extreme market conditions ("all assets declining simultaneously")
Getting started
Does this prompt give investment advice or buy/sell calls?
No. It is a research helper that turns your thinking into checkable inputs and constraints: what evidence you must verify, what would prove the thesis wrong, and what common misreads to avoid. Treat the output as a draft, not a signal. Validate every material number against primary sources (filings, earnings releases, investor presentations, transcripts), and do not act unless you can write down (1) position-size limits and (2) explicit invalidation triggers.
What inputs should I provide for a reliable result?
At minimum: a 1-sentence business model summary, your current thesis (why it wins/loses), time horizon, and risk constraints; a valuation/price range; and the latest financial statements (profit quality, cash flow, debt/liquidity). Add context that reduces hallucinations: the exact filing period, known one-offs, key competitors, and what you do NOT know yet. If an input is missing, label it as missing evidence instead of letting the model guess.
Validation and boundaries
How do I validate the output?
Validate falsifiable claims one by one. Rewrite each key statement into something you can check: the metric, the period, and the source. Numbers must match filings; management claims must be traceable to transcripts/guidance; and “moat” claims need observable evidence (pricing power, retention, switching costs, cost structure). Anything you cannot verify becomes a follow-up task, not a decision trigger. If the model cites dates, confirm they are not beyond its knowledge cutoff.
When should I NOT act on the output?
If you cannot write down invalidation triggers, a position-size cap, or primary-source evidence for the key claims behind “Estrategia para Todo Clima”, do not act. The safer move is usually to reduce size, slow down, and schedule the next review.
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