Skip to main content

Investment Decision Framework

An investment opportunity is in front of you. It might be a stock you've been researching, a private company asking for your check, a real estate deal that arrived through your network, or a significant capital allocation decision within your own business. You have partial information, genuine uncertainty about the future, and β€” if you're honest β€” some emotional pull toward the opportunity that makes neutral analysis harder.

Investment decisions are among the clearest tests of mental model quality. The decisions are quantified, the outcomes are eventually measurable, and the cognitive biases that distort analysis are well-documented. Yet most investors β€” individual and institutional β€” consistently underperform because they don't have a repeatable process.

Why a Mental Model Framework Helps​

Three failure modes dominate investment decision-making. Overconfidence: most investors overestimate both how much they know and how accurately they can predict outcomes. Inside view bias: investors focus on the specific story of the investment and ignore the base rate of similar investments. Sizing errors: even when the investment thesis is sound, investors frequently size positions either too large (resulting in catastrophic losses when wrong) or too small (resulting in immaterial gains when right). This framework addresses all three.

The Framework β€” Step by Step​

Step 1: Apply Circle of Competence β€” Should You Be Making This Investment?​

Why this model fits: Before evaluating whether an investment is good, you must evaluate whether you are qualified to evaluate it. Charlie Munger and Warren Buffett attribute much of Berkshire's outperformance not to their analytical ability but to their discipline about staying inside their circle.

How to apply it:

  1. Define what "inside the circle" means for this investment: you understand the business model and economics, you understand the competitive dynamics and why incumbents win or lose, you have a view on the industry that differs from consensus and can articulate why it differs.
  2. Ask: can you write a two-page explanation of why this investment will work, citing specific mechanisms, without using the phrases "strong management team" or "large TAM"? If not, you're outside the circle.
  3. Ask: do you have knowledge or insight about this investment that most other market participants don't? If everyone sees the same thing, the price already reflects it.
  4. If you're outside the circle, the decision is simple: pass, or learn until you're inside it. Resist the FOMO that makes outside-the-circle investments feel urgent.

The key question: What specifically do I know about this investment that justifies confidence β€” and is that knowledge real or borrowed?

Step 2: Calculate Expected Value Across Scenarios​

How to apply it:

  1. Define 3–4 scenarios: bear case, base case, bull case, and optionally a tail scenario in each direction.
  2. For each scenario, estimate the probability and the outcome (in terms of multiple of capital or IRR, not narrative).
  3. Calculate EV: sum of (probability Γ— outcome) across all scenarios.
  4. Ask: does the EV justify the risk? Is the expected return materially above your hurdle rate after accounting for uncertainty?

The key question: If I played this decision 100 times with these scenarios and probabilities, would I be satisfied with the average outcome?

Step 3: Apply Margin of Safety to Set Your Entry Price and Position Size​

How to apply it:

  1. Estimate intrinsic value β€” what the investment is worth, independent of its current price. The gap between current price and intrinsic value is your margin of safety.
  2. Standard guidance: require at least a 25–33% discount to intrinsic value before investing. This buffer absorbs errors in your intrinsic value calculation.
  3. Size the position according to your conviction and how much of your analysis could be wrong: higher margin of safety = can justify a larger position; lower margin of safety = smaller position regardless of conviction.
  4. Define your exit conditions in advance: at what price or what change in fundamentals would you sell? Pre-committing to exit conditions prevents the "I'll wait for it to come back" trap.

The key question: If my intrinsic value estimate is 30% too high, is this still a good investment at this price?

Full Workflow​

Investment Decision β€” Framework

Step 1: Circle of Competence  ──  Output: In/out decision + competence gap map
          ↓
Step 2: Expected Value  ─────── Output: Scenario-weighted return vs. hurdle rate
          ↓
Step 3: Margin of Safety  ──────  Output: Entry price + position size

Worked Example​

Rachel is evaluating an investment in a publicly traded regional bank at $28/share. She's been following the sector for 4 years.

Step 1: Rachel checks her circle. She understands bank economics (NIM, efficiency ratio, credit quality), has read 8 years of the bank's annual reports, and has a view that the market is pricing in credit deterioration that her analysis suggests is overstated. She's inside the circle.

Step 2: Her scenarios: Bear (credit losses spike, book value erodes to $20) β€” 25% probability; Base (credit normalizes, bank earns 12% ROE, worth $34) β€” 50%; Bull (management executes acquisition strategy, worth $42) β€” 25%. EV = (0.25 Γ— 20) + (0.50 Γ— 34) + (0.25 Γ— 42) = $32.50. At $28, the expected return is 16% β€” above her hurdle rate of 10%.

Step 3: She estimates intrinsic value at $34 (base case). Margin of safety at $28 = 18% β€” lower than her preferred 25%. She sizes the position at 3% of portfolio rather than her normal 5%, reflecting the thinner margin of safety. She pre-commits to sell at $38 or if the credit thesis breaks (non-performing loans exceed 2.5% of the book).

Common Mistakes​

Confusing a good story with a good investment. Narrative quality and investment quality are uncorrelated. The best story often comes with a price that already reflects it.

Skipping the Circle of Competence check. FOMO makes outside-the-circle investments feel urgent. They are usually not. The opportunity cost of missing an investment you don't understand is zero. The cost of making it can be large.

Not pre-committing to exit conditions. Exit decisions made in real-time are made under different psychological conditions than entry decisions. Define them in advance.

Apply This Framework with AI​

Describe the investment in MindMax β€” the opportunity, your knowledge of the domain, and your current thinking. The AI will guide you through the competence check, build the scenario model, and help you determine position sizing.

πŸš€ Evaluate your investment in MindMax β†’

This page is part of the MindMax Mental Models Knowledge Base.