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Judgment Under Uncertainty – Human Decision Errors

The Challenge of Uncertainty

Financial decisions are made under uncertainty—we never know future returns, market movements, or economic conditions with certainty. How humans handle this uncertainty determines investment success or failure.

Note

Core Insight: When faced with uncertainty, humans don't calculate probabilities mathematically. Instead, we use mental shortcuts (heuristics) that lead to systematic errors.

Heuristics: Mental Shortcuts

What Are Heuristics?

Heuristics are simple rules of thumb our brains use to make quick decisions when faced with complex, uncertain situations.

Benefit: Speed, cognitive efficiency
Cost: Systematic biases and errors

Common Decision Errors

Overconfidence

Error: Believing our knowledge and predictions are more accurate than they actually are.

ManifestationExample
Precision overconfidence"This stock will return exactly 15%" (too narrow range)
Forecast overconfidence"I'm 90% sure the market will rally" (too high certainty)
Ability overconfidence"I can beat the market" (most can't)

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Hindsight Bias

Error: After an event occurs, believing we "knew it all along."

Impact:

  • Overestimate our predictive abilities
  • Fail to learn from mistakes (we think we predicted them)
  • Blame others for not seeing "obvious" outcomes

Example: After 2008 crisis: "It was obvious housing prices would crash!" (It wasn't obvious at the time to most people.)

Confirmation Bias

Error: Seeking information that confirms our existing beliefs while ignoring contradictory evidence.

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Gambler's Fallacy

Error: Believing independent events are connected (e.g., "Red came up 5 times, black is 'due'").

In Finance: "The market has gone up 3 years straight, it must crash soon" or "This stock dropped 5 days, it's due for a bounce."

Reality: Past outcomes don't change probabilities of independent future events.

Hot Hand Fallacy

Error: Believing streaks will continue ("This fund beat the market 3 years, it will keep winning").

In Finance: Chasing last year's top-performing mutual funds.

Reality: Fund performance largely mean-reverts. Past winners often become future losers.

Probabilistic Thinking Errors

Base Rate Neglect

Error: Ignoring underlying probabilities (base rates) when evaluating specific cases.

Example:

  • Base rate: 90% of startups fail
  • Your friend's startup has a great idea
  • You think: "This one will succeed for sure!"
  • You ignore the 90% failure base rate

Sample Size Neglect

Error: Drawing conclusions from small samples that may not be representative.

Example: A mutual fund with only 1-year track record can't reliably predict long-term performance. Need ≥5-10 years of data.

Conjunction Fallacy

Error: Believing a specific scenario is more probable than a general one.

Example: Which is more likely?

  1. Stock market will fall
  2. Stock market will fall due to inflation and recession

Answer: #1 (it includes all scenarios where market falls, including #2)

But people often choose #2 because the detailed story feels more plausible.

Real-World Implications

Error TypeInvestment ImpactEconomic Cost
OverconfidenceExcessive trading, concentrated bets2-6% annual underperformance
Hindsight biasFailure to learn, repeat mistakesMissed learning opportunities
Confirmation biasEcho chamber investing, ignoring risksMajor losses when wrong
Gambler's fallacyPoor market timingBuy high, sell low
Hot handChasing past performanceUnderperformance (mean reversion)

Quick Recap

  • Humans use heuristics (mental shortcuts) when making uncertain decisions
  • These lead to systematic errors: overconfidence, hindsight bias, confirmation bias
  • Probabilistic thinking errors include base rate neglect and sample size neglect
  • Awareness of these biases is the first step to better judgment

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