AIYING in Practice: Equity Research

 AIYING in Practice: Equity Research 

Think Like an Analyst Before You Ask AI

Beginner · 15–20 minutes · For aspiring and practicing investors & research analysts

Goal of This Exercise
Use AI as a thinking partner — not a shortcut — to build rigorous investment research rooted in clarity, context, and conviction.

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Step 1 — The Common (Weak) Starting Point

Most people begin like this:
❌ “Give me a valuation of Company X.”
What’s missing:

1. Why it matters right now

2. What decision you need to make

3. What assumptions drive value
   AI guesses numbers; you need clarity.

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Step 2 — Apply AIYING Outcome Clarifier

Before you ask AI anything, answer these 5 questions on paper:

1️⃣ Outcome — What decision will your research support?
☐ Buy, Sell, Hold ☐ Sector view ☐ Risk bias ☐ Idea prioritisation
✍️ Outcome: _______________________

2️⃣ Context — Why now?
☐ Earnings reset ☐ Macro change ☐ Regulatory shift ☐ New strategy
✍️ Context: _______________________

3️⃣ Audience — Who uses this?
☐ Portfolio manager ☐ Trader ☐ Internal committee ☐ External clients
✍️ Audience: _______________________

4️⃣ Constraints — What matters most?
☐ Interpretability ☐ Time horizon ☐ Data quality ☐ Risk appetite
✍️ Constraints: ____________________

5️⃣ Success Signal — How will you judge usefulness?
☐ Return vs benchmark ☐ Better risk understanding ☐ Clear thesis articulation
✍️ Success metric: __________________

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Step 3 — Your AIYING Ask (One Clear Instruction)

Combine clarity into one sentence:

“Help me build a 12-month investment thesis for [Company X], focusing on its competitive advantage, key risks, financial drivers, valuation sensitivity, and triggers that would change my buy/hold/sell view, given [context].”

✍️ Your version: _______________________

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Step 4 — Ask AI (Now Use AI)

Paste only your final sentence into AI. When reading the response:

• Check assumptions — are they realistic?

• Notice drivers — what moves the thesis most?

• Spot missing risks the model skipped.

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Step 5 — Scenario Thinking (A Core AIYING Move)

Turn one view into three plausible narratives:

📌 Base Case: What you think will most likely happen
📌 Bull Case: What needs to go right
📌 Bear Case: What needs to go wrong

Ask AI to table these side by side and show how each affects valuation bands and risk signals.

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Step 6 — Reflection (Critical)

After your first draft, answer:

1. What assumption surprised you?

2. What would change your view fastest?

3. What data should you verify next?

✍️ Insight: _______________________

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Why This Matters — The AIYING Difference

AIYING in equity research isn’t about auto-generating target prices or copying consensus. It’s about sharpening thinking, structuring judgement, and amplifying market insight before any models or charts are drawn.

Rule for Equity Researchers:
If the outcome isn’t clear, the analysis won’t be either.