Three-Scenario Thinking: Build Bull/Base/Bear Outcomes with Probabilities

Introduction

Three-Scenario Thinking is a simple way to frame investment outcomes by building three clear scenarios: bull, base, and bear. You write one-line outcomes, assign a probability to each, and state the single assumption that makes that outcome different. This technique helps you replace gut reactions with structured probability thinking.

Why does this matter? When you put probabilities and assumptions on paper you stop thinking in extremes and start thinking in ranges. That makes decisions more defensible and less emotional. You'll learn how to create a one-page scenario table, how to pick probabilities, and how to use the results in practical decisions.

In this guide you'll get step-by-step instructions, real company examples using $AAPL and $TSLA, a sample one-page scenario template you can copy, and common mistakes to avoid. Ready to shrink uncertainty into manageable scenarios?

Key Takeaways

• Three-Scenario Thinking means creating bull, base, and bear outcomes for a position, assigning a probability to each, and naming one key assumption that changes the result.
• A one-page scenario table keeps analysis simple: outcome, probability, key driver, and a numeric estimate or range for each scenario.
• Probabilities should sum to 100% and reflect your current view, not wishful thinking or perfect foresight.
• Using expected-value math gives a quick, quantitative check, but think qualitatively about risks and catalysts too.
• This framework reduces all-or-nothing thinking and helps you communicate decisions clearly to yourself and others.

What is Three-Scenario Thinking and why it works

Three-Scenario Thinking organizes uncertainty into three plausible futures: a bull case where things go better than expected, a base case where things go mostly as you expect, and a bear case where things go worse. Each scenario includes a single key assumption that drives the outcome.

The main benefit is cognitive simplicity. By limiting yourself to three outcomes you avoid paralysis from endless possibilities. You also force yourself to state the assumption that matters most, which clarifies where to focus monitoring and risk management.

How to build a one-page scenario table

Creating the table takes about 10 to 30 minutes for a single stock if you keep it one page. The table has four columns: Scenario, Probability, Key Assumption, and Outcome Estimate. You can add a fifth column for action triggers if you like.

Step-by-step

1. Pick the asset you want to analyze, for example $AAPL or $TSLA.
2. Write three short scenario names: Bull, Base, Bear.
3. Decide the single, most important assumption that changes the scenario. Make it simple, like revenue growth rate, gross margin, or EV battery lead time.
4. Assign a probability to each scenario so they add to 100%.
5. Provide a numeric result for each scenario, such as a price range, earnings estimate, or percentage return.
6. Optionally, add triggered actions: what you will do if a scenario starts to unfold.

Keep each scenario to one or two sentences. The point is clarity, not perfection.

Choosing probabilities: practical rules

Assigning probabilities feels subjective, and it is. Use these practical rules to make them useful and consistent.

• Start with 50% for the base case if you have no strong bias, then split the remaining 50% between bull and bear according to conviction.
• Use rounded numbers like 10, 20, 30, 40 to avoid false precision.
• Update probabilities as new information arrives, and record why you changed them.
• Check that probabilities sum to 100% and that they reflect current evidence, not hope.

For example, if you think $AAPL’s core business is stable but supply risk is rising, your probabilities might be: Bull 25%, Base 60%, Bear 15%.

Real-world examples

Examples make the framework concrete. Below are two realistic scenario tables you can recreate on one page for your own research.

Example 1: $AAPL, consumer hardware company

• Bull (25%): Key assumption, iPhone average selling price rises 8% over three years due to services bundling. Outcome estimate, revenue CAGR 8%, EPS grows 12% annually, implied price up 40% in three years.
• Base (60%): Key assumption, steady demand with modest upgrades. Outcome estimate, revenue CAGR 4%, EPS grows 6% annually, implied price up 12% in three years.
• Bear (15%): Key assumption, supply chain squeeze and weaker demand from macro weakness. Outcome estimate, revenue flat, EPS down 5% annually, implied price down 20% in three years.

Ask yourself, which data would convince you to move probability weight from base to bull or bear? Maybe stronger services revenue numbers or a persistent component shortage.

Example 2: $TSLA, growth and execution risk

• Bull (30%): Key assumption, global EV adoption accelerates and $TSLA achieves consistent margin improvements. Outcome estimate, vehicle deliveries +30% CAGR, EBITDA margin expands, stock +80% in three years.
• Base (50%): Key assumption, EV market growth steady but competition rises. Outcome estimate, deliveries +15% CAGR, margins stable, stock +10% in three years.
• Bear (20%): Key assumption, execution delays and margin pressure from competitors. Outcome estimate, deliveries flat, margins compress, stock down 40% in three years.

These numbers are example estimates, not predictions. The point is to tie each outcome to the assumption that matters.

Using expected value: quick quantitative check

You can calculate a simple expected outcome by multiplying each scenario outcome by its probability and summing the results. This gives a single number you can compare to the current price or your investment threshold.

Example with $AAPL base numbers turned into percent price change: Bull +40% at 25% probability, Base +12% at 60%, Bear -20% at 15%. Expected price change = 0.25*40 + 0.60*12 + 0.15*(-20) = 10 + 7.2 - 3 = +14.2% over three years.

Expected value is a check, not a truth. It doesn't replace judgment, but it helps prioritize ideas and size positions logically.

Monitoring and triggers

The single most useful part of the table is the key assumption column. That tells you what to watch. If the assumption starts to break down, you update probabilities or act.

• Set 2-3 simple indicators to watch, like quarterly revenue growth, margin, or delivery numbers.
• Decide ahead of time what will shift the probability materially, for example a supply contract loss or a new product beating expectations.
• Record the reason when you change probabilities so you can learn over time.

Monitoring turns a static table into an ongoing decision tool.

Practical tips for beginners

• Keep it to one page and simple language so you will actually use it.
• Use round percentages for probabilities and round target outcomes to avoid false precision.
• Focus on one key assumption per scenario; if there are many drivers, pick the one that matters most.
• Use this framework for positions you already own and for ideas you are considering.

Common Mistakes to Avoid

1. All-or-nothing probabilities: assigning 100% to one scenario. How to avoid, always split probabilities so they total 100% and reflect uncertainty.
2. Too many assumptions: listing long checklists instead of one key driver per scenario. How to avoid, pick the single assumption that would change your outlook most.
3. False precision: using exact decimals for probabilities and targets. How to avoid, use rounded numbers like 10, 20, or 25 percent.
4. Not updating the table: leaving probabilities unchanged after major news. How to avoid, review your scenarios after each earnings report or major industry update.
5. Confusing optimism with probability: letting hope inflate bull-case weight. How to avoid, base probabilities on evidence or comparable historical outcomes.

FAQ

Q: How precise do probabilities need to be?

A: Use rounded probabilities like 10, 20, 25, or 50 percent. The goal is clarity, not statistical precision. Rounded numbers reduce the illusion of accuracy and make updating easier.

Q: Can I use more than three scenarios?

A: You can, but three is recommended for beginners because it balances realism with simplicity. If you add more, keep each scenario focused and label why it matters.

Q: How often should I update probabilities?

A: Update when new, relevant information arrives such as earnings, regulatory news, or industry shifts. A quarterly review is a good habit, with immediate updates for material events.

Q: Should I set action rules based on the table?

A: Yes, define simple triggers like "reduce position if base probability falls below 40%" or "reassess if the key assumption changes materially." These rules help convert scenarios into decisions.

Bottom Line

Three-Scenario Thinking is a low-friction way to move from gut feelings to structured probability thinking. By writing bull, base, and bear outcomes on one page and naming the single assumption behind each, you make uncertainty actionable and reviewable.

Start small with one stock or one decision. Create the one-page table, assign rounded probabilities, and pick a few monitoring triggers. Over time you'll get better at judging probabilities and using the method to size positions and manage risk.

At the end of the day, investing is about making decisions under uncertainty. Three-Scenario Thinking gives you a simple, repeatable framework for doing exactly that.