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# CORPUS-0013
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## Festival Demand And After-Event Bargains
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### Status: Training Corpus Seed
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### Layer: Layer_1--Worked_Examples
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### Purpose: Teach that predictable gatherings can raise demand before an event and create discounted surplus after the event
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### Repository Path: docs/training/corpus/Layer_1--Worked_Examples/CORPUS-0013-festival-demand-and-after-event-bargains.md
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---
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## 0. Scenario
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A trader in Ostia learns that a festival or public gathering in Capua will increase demand for food, oil, cheap cloth, drink, lamps, and small comforts.
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Before the event, sellers move goods toward Capua because buyers will gather there.
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After the event, some sellers may be tired, short of coin, unwilling to pay storage, or eager to move on.
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The same event can create two different opportunities:
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1. selling into rising demand before the gathering
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2. buying leftover stock after the gathering and moving it to the next place
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---
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## 1. Before The Event
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Before the event, demand may rise for:
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- food
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- oil
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- wine
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- lamps
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- cloth
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- cheap ornaments
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- animal feed
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- lodging
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- porterage
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- temporary stalls
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- repair work
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A trader may send goods early to sell into higher demand.
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Example:
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```text
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purchase value in Ostia = 20 asses
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transport and handling = 6 asses
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expected sale value in Capua before festival = 34 asses
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expected result = 8 asses profit
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```
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The profit depends on arriving before the demand peak is satisfied.
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---
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## 2. During The Event
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During the event:
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- prices may rise for urgent goods
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- porterage may become expensive
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- lodging may tighten
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- carts may be unavailable
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- buyers may pay more for convenience
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- sellers may run out of stock
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- officials or local organizers may restrict certain spaces
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The trader may profit if positioned early.
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But late arrival can be costly.
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---
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## 3. After The Event
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After the event, unsold goods may become discounted.
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Sellers may want to avoid:
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- storage cost
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- return transport
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- spoilage
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- breakage
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- fatigue
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- tied-up capital
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- missed next market
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A trader with available coin, storage, or transport may buy leftover goods below ordinary value.
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Example:
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```text
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leftover goods bought after event = 18 asses
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handling and storage = 4 asses
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transport to next location = 5 asses
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expected sale value elsewhere = 34 asses
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expected result = 7 asses profit
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```
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The bargain exists because the seller faces post-event pressure.
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---
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## 4. Incorrect Model Behavior
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The model should not:
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- treat festival demand as random
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- ignore predictable timing
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- assume high demand lasts forever
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- assume leftovers are worthless
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- ignore post-event seller pressure
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- ignore transport scarcity before the event
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- ignore storage pressure after the event
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- treat every after-event bargain as automatically safe
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The event creates a cycle, not a single price change.
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---
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## 5. Correct Model Behavior
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The model should separate:
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| Stage | Market Condition |
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|---|---|
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| before event | rising demand, transport competition |
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| during event | high urgency, crowded access, price volatility |
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| after event | surplus, fatigue, storage pressure, discounted stock |
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| next location | possible resale if demand remains unmet elsewhere |
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The trader must identify where in the cycle he is acting.
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---
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## 6. Risk Variants
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### Variant A — Arrives Early
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The trader reaches Capua before the event.
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```text
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sale value = 34 asses
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total cost = 26 asses
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result = 8 asses profit
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```
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### Variant B — Arrives Late
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Other sellers satisfy demand first.
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```text
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sale value = 27 asses
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total cost = 26 asses
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result = 1 as profit
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```
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### Variant C — Buys Leftovers Poorly
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The trader buys leftover goods, but they are damaged or unsuitable for the next location.
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```text
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sale value = 24 asses
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total cost = 27 asses
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result = 3 asses loss
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```
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### Variant D — Buys Leftovers Well
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The trader buys sound leftovers from tired sellers and moves them to another event location.
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```text
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sale value = 34 asses
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total cost = 27 asses
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result = 7 asses profit
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```
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---
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## 7. Timing Questions
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The trader must ask:
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- when does the event begin?
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- when does demand peak?
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- when do sellers arrive?
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- when do buyers depart?
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- which goods spoil or lose value quickly?
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- which goods remain useful after the event?
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- is transport available after the crowd leaves?
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- where is the next demand location?
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The event calendar is an economic map.
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---
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## 8. Non-Coin Settlement Variant
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After the event, a seller may accept mixed settlement:
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- some coin now
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- help moving goods
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- storage for one night
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- a share of resale
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- goods exchanged for transport
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- future priority at the next gathering
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The trader should track obligations, not only coin.
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---
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## 9. Layer-0 And Layer-1 Concepts Used
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This example uses:
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- `Layer_0/CORPUS-0002-goods-have-local-prices`
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- `Layer_0/CORPUS-0004-cost-includes-more-than-purchase-price`
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- `Layer_0/CORPUS-0005-profit-is-sale-minus-total-cost`
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- `Layer_0/CORPUS-0006-delay-is-economic-cost`
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- `Layer_0/CORPUS-0012-every-venture-risks-loss`
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- `Layer_0/CORPUS-0013-non-coin-settlement-exists`
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- `Layer_0/CORPUS-0016-opportunistic-bargains-come-from-pressure`
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- `Layer_0/CORPUS-0018-rivalry-changes-conditions`
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- `Layer_1/CORPUS-0003-arithmetic-resolves-the-venture`
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- `Layer_1/CORPUS-0007-rival-buys-the-cart-space`
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---
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## 10. Success Condition
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If the model sees a festival or public gathering and asks how demand, transport, storage, leftovers, and next-location resale change before, during, and after the event, this file is functioning correctly.
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