| # **Pricing Decision — Technical Summary** | |
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| ## **1. Purpose** | |
| The difficulty of pricing under uncertainty is not estimating demand, | |
| but deciding **which price can be safely deployed**. | |
| Prices that maximize expected profit often expose unacceptable downside risk, | |
| leading to reversals, overrides, and erosion of trust in pricing decisions. | |
| This system addresses the technical question: | |
| > **How should prices be selected when profit distributions—not point estimates—matter?** | |
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| ## **2. Data Basis** | |
| Two operating modes are supported: | |
| ### **Synthetic Mode** | |
| * controlled elasticity parameter | |
| * additive demand noise | |
| * known cost structure | |
| * fully reproducible | |
| Used to demonstrate idealized pricing behavior. | |
| ### **Observational Retail Mode (UCI, local only)** | |
| * transactional retail data | |
| * time-varying prices | |
| * non-randomized price changes | |
| * aggregated per period | |
| Elasticity estimates in this mode are **observational, not causal**. | |
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| ## **3. Model Structure** | |
| Demand is modeled using a log–log specification. | |
| Parameter uncertainty is captured via bootstrap resampling. | |
| The objective is **distributional robustness**, not causal identification. | |
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| ## **4. Profit Evaluation** | |
| For each candidate price: | |
| * profit distributions are computed | |
| * median profit represents expected outcome | |
| * downside quantiles (q10 or q5) represent risk exposure | |
| All profit values are expressed **per aggregation period**. | |
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| ## **5. Decision Logic** | |
| Candidate prices are evaluated within a constrained grid around the current median price. | |
| Decisions follow explicit governance rules: | |
| * **Feasibility:** at least one price must yield positive median and downside profit | |
| * **Leverage:** price must materially affect profit | |
| * **Risk:** downside exposure must remain within relative and absolute caps | |
| Violations trigger HOLD or NO-GO outcomes. | |
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| ## **6. Output** | |
| The system produces: | |
| * decision state (OPTIMIZE / HOLD / NO-GO) | |
| * recommended deploy price | |
| * profit distribution diagnostics | |
| * traceable justification metrics | |
| This design prioritizes **auditability, explainability, and governance** over model complexity. | |
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| ## **Closing Position** | |
| Pricing under uncertainty is a decision problem, not a curve-fitting exercise. | |
| This system converts uncertain demand response into **deployable pricing actions** | |
| that remain defensible under review, volatility, and downside exposure. | |
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