Description
Return a reference-dependent piecewise prospect value.
Decision models distinguish monetary payoffs, probabilities, model values and subjective equivalents. Discounting, probability weighting and reference-dependent utility terms depend on supplied parameters and cannot by themselves establish actual preferences or an appropriate allocation.
Return a reference-dependent piecewise prospect value.
When to use this tool
Use Prospect Loss Aversion Value Gap when evaluating the stated decision-model, lottery or discount contribution.
How to use the tool and how it works
- Enter outcome, reference, gainExponent, lossExponent, lossAversion. Use the units and conventions below.
- Run the tool. Correct any format, range, or cross-field input error before interpreting the output.
- Read relativeOutcome, value. Use the output convention below.
Return a reference-dependent piecewise prospect value. Require positive gain/loss exponents and lossAversion >= 0; relativeOutcome = outcome-reference, nonnegative branch raises it to gainExponent, negative branch is -lossAversion*(-relative)^lossExponent.1
Prospect models distinguish reference-dependent outcome value from probability weighting. A single supplied value or weighting branch is not a complete cumulative-prospect evaluation or an empirical preference estimate.2
| Input field | Meaning and units | Accepted input |
|---|---|---|
| outcome | Outcome | Required. Finite number. |
| reference | Reference | Required. Finite number. |
| gainExponent | Gain Exponent | Required. Finite number; strictly above 0. |
| lossExponent | Loss Exponent | Required. Finite number; strictly above 0. |
| lossAversion | Loss Aversion | Required. Finite number; minimum 0. |
| Output field | Interpretation | Returned shape |
|---|---|---|
| relativeOutcome | Relative Outcome | Required. Finite number. |
| value | Piecewise model-value score, not currency or an empirically measured utility. | Required. Finite number. |
{
"input": {
"outcome": 120,
"reference": 100,
"gainExponent": 0.5,
"lossExponent": 0.5,
"lossAversion": 2
},
"output": {
"relativeOutcome": 20,
"value": 4.47213595499958
}
}Limitations and assumptions
- Parameters and reference are supplied; value is a model score, not money, observed utility or a recommended choice.
- Inputs must satisfy both the field types and the cross-field conditions above. Invalid input causes an error; a successful false flag or documented placeholder is a different result.
- Numeric calculations use binary floating point unless exact decimal-integer arithmetic is explicitly stated. No hidden measurement tolerance or decimal rounding is added; nonfinite or out-of-contract results are rejected. Numeric signed-zero results are exported as zero.
Alternative or Complementary methods
Fit and validate an appropriate complete decision model against relevant observations; distinguish model scores from money and assess actual financial choices separately.
References
-
Calculation and input contract: behavioral-economics/prospect-loss-aversion-value-gap — tool.io
-
Advances in prospect theory: cumulative representation of uncertainty — Amos Tversky and Daniel Kahneman
Similar or alternative tools
- Probability Weighting One Branch Term
Return one probability-weighting function value.
- Loss Aversion Reference Change Label
Label a supplied outcome as gain, loss or unchanged relative to an explicit reference value without estimating loss aversion.