Loss Aversion and Prospect Theory

Overview

People evaluate outcomes relative to a reference point (not absolute wealth), weight losses ~2.25x as heavily as equivalent gains, are risk-averse in gain frames and risk-seeking in loss frames, and distort probabilities (overweighting small, underweighting large). The same physical outcome feels different depending on framing — this skill diagnoses and corrects that asymmetry.

Composes with sunk-cost-fallacy, framing-effect, expected-value-and-kelly, anchoring, pricing-strategy.

When to Use

• A decision involves uncertainty and the chooser is visibly averse to a "loss" framing
• People are refusing positive-EV bets because the downside feels disproportionately bad
• Negotiations are stuck because concessions feel like losses from an anchored reference point
• A product launch, pricing, or incentive is producing unexpected adoption patterns
• Small-probability events are being over- or under-insured against
• An investor is holding a losing AI / Nvidia / semiconductor position waiting to "get back to breakeven," or is reacting to an AI-capex, AI-valuation, or AI-adoption drawdown (e.g. the DeepSeek shock) rather than re-deriving forward EV
• Someone says "loss aversion," "prospect theory," "reference point," "endowment effect," "status quo bias," "disposition effect"

Not when: the asymmetric weighting is rational (genuinely catastrophic stakes); the reference point is legitimate; the decision is small and one-shot.