Strategy #0000000112 · Behavioural finance and cross-sectional pricing
Prospect-theory value ranking
Enter four return/probability outcomes, loss aversion, value curvature, probability-weighting curvature and costs.
Prospect-theory value treats a historical return distribution as an investor’s mental representation, applying a gain/loss value function and probability weights to outcomes. Barberis, Mukherjee and Wang find lower subsequent average returns for high-value stocks. Parameters, historical windows and cumulative weighting affect ranks; this page uses a small discrete illustrative approximation.
Returns and probabilities are manually entered; the full paper’s parameters and ranking are not reproduced.
Three ways in
Understand the story. Then inspect the risk.
Start with a familiar situation, check the payoff, then test how the numbers change.
The idea · in two minutes
How do loss aversion and probability weighting change the subjective value of a return distribution?
Prospect-theory value treats a historical return distribution as an investor’s mental representation, applying a gain/loss value function and probability weights to outcomes. Barberis, Mukherjee and Wang find lower subsequent average returns for high-value stocks. Parameters, historical windows and cumulative weighting affect ranks; this page uses a small discrete illustrative approximation.
Enter four return/probability outcomes, loss aversion, value curvature, probability-weighting curvature and costs.
Returns and probabilities are manually entered; the full paper’s parameters and ranking are not reproduced.
- Input assumptionsEnter four return/probability outcomes, loss aversion, value curvature, probability-weighting curvature and costs.
- Model outputReturns and probabilities are manually entered; the full paper’s parameters and ranking are not reproduced.
Illustrative research examples only. They are not live signals or a recommendation.
The mechanics · payoff and exposure
TK=\sum_j\pi(p_j)v(r_j),\quad v(r)=\begin{cases}r^\alpha&r\geq0\\-\lambda(-r)^\alpha&r<0\end{cases}
λ is loss aversion and α the value curvature; simplified probability weights are not the full cumulative weighting function.
Greeks: the directional intuition
- 模型
- Measures sensitivity to implied volatility.
- 樣本
- Measures sensitivity to implied volatility.
- 執行
- Measures sensitivity to implied volatility.
TK=\sum_j\pi(p_j)v(r_j),\quad v(r)=\begin{cases}r^\alpha&r\geq0\\-\lambda(-r)^\alpha&r<0\end{cases}
Practical context · published observations
Prospect-theory value ranking: read the record with its caveats.
The chart uses the published figures or explicitly labelled study inputs below. A historical index or model replay is not the same as an investor’s realised account return.
Returns and probabilities are manually entered; the full paper’s parameters and ranking are not reproduced. Source ↗ · Methodology ↗
Change assumptions and inspect the scenario
Inputs illustrate the strategy mechanics; they are not live quotes, forecasts or investment advice.
Variants · same family, different risk levers
Model definitions, data splits and implementation costs affect results.
Compare methodology and execution assumptions.
| Related strategy | Relationship | What changes | New cost or risk |
|---|---|---|---|
| Base scenario | Manual inputs | Prospect-theory value treats a historical return distribution as an investor’s mental representation, applying a gain/loss value function and probability weights to outcomes. Barberis, Mukherjee and Wang find lower subsequent average returns for high-value stocks. Parameters, historical windows and cumulative weighting affect ranks; this page uses a small discrete illustrative approximation. | Returns and probabilities are manually entered; the full paper’s parameters and ranking are not reproduced. |
| Conservative version | Lower risk | Raise cost assumptions and cap exposure or search space. | May reduce model adaptability. |
| Validation version | Out-of-sample test | Freeze rules before evaluating untouched data. | Needs more data and governance. |
Returns and probabilities are manually entered; the full paper’s parameters and ranking are not reproduced.
Read beyond the summary
References
Primary sources and research used to describe the strategy and its limits.