Research-Based Investing - موجّه تحليل بالذكاء الاصطناعي
Use this John Templeton rule prompt to apply “الاستثمار القائم على البحث” 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.
الموجّه الكامل
أنت محلل استثماري مدرّب على مبدأ John Templeton: "Research-Based Investing". مهمتك تحليل {اسم الشركة} من خلال هذا المنظور المحدد.
## السياق
يعلّم John Templeton: "Never buy a stock without thorough research. Know what you own and why you own it."
## إطار التحليل
### 1. تقييم تطبيق المبدأ
- كيف ينطبق هذا المبدأ تحديداً على {اسم الشركة}؟
- ما جوانب الشركة الأكثر صلة بـ"Research-Based Investing"؟
- قيّم التوافق: قوي / متوسط / ضعيف
- على ماذا سيركز John Templeton أولاً؟
### 2. الأدلة الكمية
- حدد 3-5 مؤشرات مالية رئيسية ذات صلة
- حلل هذه المؤشرات خلال السنوات 5-10 الماضية
- قارن مع المنافسين والمعايير التاريخية
- هل الأرقام تتحسن أم مستقرة أم تتدهور؟
### 3. التحليل النوعي
- قيّم العوامل غير القابلة للقياس التي سيفحصها John Templeton
- جودة الإدارة وتوافقها مع هذا المبدأ
- ديناميكيات الصناعة والموقف التنافسي
- استدامة نموذج الأعمال من هذا المنظور
### 4. تقييم المخاطر
- ما المخاطر التي يبرزها هذا المبدأ لـ{اسم الشركة}؟
- ما إشارات التحذير التي سيحددها John Templeton؟
- اختبار الضغط: كيف ستؤدي الشركة في ظروف معاكسة؟
- ما أسوأ سيناريو من منظور هذا المبدأ؟
### 5. تحديد الفرص
- ما الفرص التي يكشفها هذا التحليل؟
- هل هناك نقاط قوة مخفية قد يقلل السوق من قيمتها؟
- ما المحفزات التي قد تطلق القيمة؟
### 6. Templeton Verdict
- هل تجتاز {اسم الشركة} اختبار "Research-Based Investing"؟
- التقييم: 1-10
- توصية واضحة: شراء / احتفاظ / تجنب
- ملخص في فقرة واحدة
## تنسيق المخرجات
قدم بيانات محددة في كل قسم. اختم بحكم حاسم.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.
هذا المحتوى متاح حاليًا باللغتين الصينية والإنجليزية فقط.
Basic Questions
How does Templeton's deep research differ from modern quantitative analysis?
Core idea: all investment decisions must be built on thorough research
✅ Using this AI prompt, you can systematically analyze any company or investment opportunity from this principle's perspective.
The prompt guides you to:
1. Assess whether the investment target meets this principle's core requirements
2. Identify key risks and blind spots
3. Provide a 1-10 comprehensive rating
Start by analyzing companies you know well for practice, then apply the framework to new investment decisions.
✅ Using this AI prompt, you can systematically analyze any company or investment opportunity from this principle's perspective.
The prompt guides you to:
1. Assess whether the investment target meets this principle's core requirements
2. Identify key risks and blind spots
3. Provide a 1-10 comprehensive rating
Start by analyzing companies you know well for practice, then apply the framework to new investment decisions.
Usage Tips
Is the AI's 1-10 rating reliable?
⚠️ The research depth score measures "how much homework you've done," not whether conclusions are correct.
The rating's unique logic:
- Templeton believed: "The more homework you do, the luckier you get" — thorough research doesn't guarantee success but dramatically increases success probability
- A high score means your analysis is built on sufficient data foundation, though data itself may be outdated or incomplete
- A low score is a clear warning: making investment decisions without sufficient research is essentially gambling
Usage principles:
- AI can rapidly process vast data, but cannot replace your firsthand research — Templeton personally visited over a hundred countries
- Research's purpose isn't eliminating uncertainty but understanding where uncertainty lies
- Don't equate "lots of information" with "thorough research" — the key is whether you've identified the core variables affecting the investment decision
The rating's unique logic:
- Templeton believed: "The more homework you do, the luckier you get" — thorough research doesn't guarantee success but dramatically increases success probability
- A high score means your analysis is built on sufficient data foundation, though data itself may be outdated or incomplete
- A low score is a clear warning: making investment decisions without sufficient research is essentially gambling
Usage principles:
- AI can rapidly process vast data, but cannot replace your firsthand research — Templeton personally visited over a hundred countries
- Research's purpose isn't eliminating uncertainty but understanding where uncertainty lies
- Don't equate "lots of information" with "thorough research" — the key is whether you've identified the core variables affecting the investment decision
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 “الاستثمار القائم على البحث”, do not act. The safer move is usually to reduce size, slow down, and schedule the next review.
المزيد من موجّهات القواعد
استكشف مبادئ استثمارية أخرى من هذا المعلّم.
انضباط البيع
وقت البيع هو قبل الانهيار، وليس بعده. بِع عندما يكون التفاؤل في ذروته وتوجد فرص أفضل في أماكن أخرى.
→المرونة
من المستحيل تحقيق أداء متفوق ما لم تفعل شيئاً مختلفاً عن الأغلبية. كن مرناً في نهجك.
→الصبر والمثابرة
المستثمرون الوحيدون الذين لا يحتاجون للتنويع هم من يصيبون 100% من الوقت. لبقيتنا، الصبر والتنويع هما المفتاح.
→التواضع في الاستثمار
المستثمر الذي لديه كل الإجابات لا يفهم حتى الأسئلة. التواضع ضروري للنجاح طويل الأمد.
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