Three Reasons to Sell - موجّه تحليل بالذكاء الاصطناعي

Use this Philip Fisher rule prompt to apply “ثلاثة أسباب للبيع” 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 Philip Fisher: "Three Reasons to Sell". مهمتك تحليل {اسم الشركة} من خلال هذا المنظور المحدد.

## السياق
يعلّم Philip Fisher: "Sell only when: 1) You made a mistake in original analysis, 2) The company no longer meets the fifteen points, or 3) A clearly better opportunity exists."

## إطار التحليل

### 1. تقييم تطبيق المبدأ
- كيف ينطبق هذا المبدأ تحديداً على {اسم الشركة}؟
- ما جوانب الشركة الأكثر صلة بـ"Three Reasons to Sell"؟
- قيّم التوافق: قوي / متوسط / ضعيف
- على ماذا سيركز Philip Fisher 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 Philip Fisher
- 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 Philip Fisher؟
- 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. Fisher Verdict
- هل تجتاز {اسم الشركة} اختبار "Three Reasons to Sell"؟
- 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.

Educational only. Verify facts with primary sources and apply your own constraints.

ℹ️هذا المحتوى متاح حاليًا باللغتين الصينية والإنجليزية فقط.

Basic Questions

When does Fisher think you should sell a stock?
Fisher's selling criteria are very strict — he believed frequent selling means wrong buying:

🔴 Fisher's three reasons to sell:
1. Original judgment was wrong: Deeper research reveals the company isn't as good as thought
2. Company no longer qualifies: Management deterioration, competitive advantage lost, market saturated
3. Found clearly better opportunity: But this should be extremely rare

🟢 Should NOT sell:
- Just because stock dropped short-term
- Just because overall market declined
- Just because it's up a lot and you want to 'lock in profits'

Fisher held Motorola and similar companies for over 20 years.

Usage Tips

Is the AI's 1-10 rating reliable?
⚠️ Sell assessment isn't a simple yes/no — it's an ongoing dynamic judgment.

The rating's unique value:
- Fisher would sell only in three situations: the original buy thesis was wrong, the company no longer meets standards, or a clearly better opportunity is found
- The score helps distinguish "genuine sell signals" from "short-term noise" — price drops aren't sell reasons; fundamental deterioration is
- Most valuable is comparing the current state against your original buy reasons one by one — if core reasons still hold, don't sell

Core reminders:
- Fisher believed the biggest selling mistake is "selling excellent companies too early" — far more common and fatal than selling too late
- AI may over-recommend selling due to short-term negative news; apply your long-term perspective as correction
- Don't sell just because you've made a lot — "I've profited enough" is not a sell reason Fisher would endorse

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 “ثلاثة أسباب للبيع”, do not act. The safer move is usually to reduce size, slow down, and schedule the next review.

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