AIYING in Practice — Equity Research (Scenario Thinking)

Beginner · 15–20 minutes · For investors, analysts, and serious learners

Purpose of This Practice

To move equity research from prediction to preparedness by using AI to think in scenarios, not single outcomes.

This is not about target prices.
It is about decision resilience.

---

Step 1 — The Common (Fragile) Approach

Most equity research starts like this:

❌ “What is the fair value of Company X?”

What this assumes (often incorrectly):

• The future is linear

• One forecast is sufficient

• Confidence comes from precision

Markets punish this thinking.

---

Step 2 — Apply the AIYING Outcome Clarifier

Before using AI, pause and write answers to these:

1️⃣ Outcome
What decision will this research support?
☐ Buy ☐ Hold ☐ Avoid ☐ Position sizing ☐ Risk framing
✍️ Outcome: _______________________

2️⃣ Time Horizon
☐ 6 months ☐ 1 year ☐ 3–5 years
✍️ Horizon: _______________________

3️⃣ Uncertainty Source
What is most likely to surprise the market?
☐ Demand ☐ Margins ☐ Regulation ☐ Execution ☐ Macro
✍️ Key uncertainty: _______________________

4️⃣ Failure Definition
What would make this investment thesis wrong?
✍️ Failure signal: _______________________

---

Step 3 — Reframe the AI Ask (Critical Shift)

Instead of asking for a single valuation, ask:

“Help me build three plausible future scenarios for [Company X] over the next [time horizon], explaining what must be true for each scenario to occur, the key assumptions behind them, and how each would affect my investment decision.”

✍️ Your version: _______________________

This is AIYING in Practice — intent before instruction.

---

Step 4 — Build the Scenario Set

With AI’s help, articulate:

📌 Base Case

• What continues as expected

• Why the market is comfortable here

📌 Bull Case

• What improves unexpectedly

• What the market may be underestimating

📌 Bear Case

• What breaks

• What risk the market is ignoring

Do not attach probabilities yet.

---

Step 5 — Sensitivity Thinking (Where Insight Lives)

Ask AI:

“Which single variable has the greatest impact across all three scenarios, and why?”

This reveals:

• Fragile assumptions

• Hidden leverage points

• Real risk drivers

✍️ Insight: _______________________

---

Step 6 — Human Judgment Check

Now step away from AI and answer:

1. Which scenario makes me uncomfortable — and why?

2. Which assumption do I believe without enough evidence?

3. What would I watch quarterly to detect scenario drift?

✍️ Reflection: _______________________

---

Step 7 — Close the Loop (AIYING Feedback)

After earnings, news, or time passage, return and ask:

“Which scenario moved closer to reality, and what did I miss?”

Turn this into a personal research playbook.

---

Why This Is AIYING in Practice

AI does not predict markets.
AI helps you think across uncertainty.

In equity research:

• Certainty is fragile

• Preparedness compounds

AIYING in Practice — Scenario Thinking
is how analysts survive reality instead of forecasting it.