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