Welcome to the ‘Buying and Selling Game’ Contest number three. This game requires basic understanding of economics and statistics as well as a dash of luck. Knowledge of economics and/or statistics will guide participants to select the goods that have the highest probability of making the most money. The luck element of the game is relying on my ‘Buying and Selling Game’ model to produce the final prices. This contest does not require a separate post but just simply a response in the comment section in the format described in this post.
Objectives of the game
The objective of the game is to end the contest with as much money as possible based on your buying and selling decisions. This will be achieved by buying goods at the lowest possible price and then selling them at the highest possible price. Transaction and transport costs are assumed to be zero. This contest though has an extra twist; read the required information section to find out more.
How to play
Participants are required to buy goods with the money allocated to them. For this contest, participants have been allocated $3 million to spend. Participants can choose to spend all of it or just some of it. Participants can choose to buy 1 or more goods but from just one planet (yes, we have moved on to planets). Participants are not permitted to buy goods from multiple planets. Buying occurs on what I am calling ‘Day 1’ of the contest. Day 1, is in fact any day from the start of this contest to the close of this contest.
Contest #3 will have a space theme involving buying and selling furniture to different planets.
Note: All planets are hypothetical, any resemblance in name to any real planets is purely a coincidence.
All furniture bought by the participants are automatically sold on Day 7. Participants decide which planet their furniture will be sold on; only one planet can be selected. After the contest closes, I will upload a video of myself running my ‘Buying and Selling Game’ model. The model will generate the Day 7 prices for all the goods on all the planets. The model determines the prices using a triangle distribution. The post containing the video will also contain the results of the contest based on the prices generated in the video.
Budget = $3 Million (Participants can spend all, some or none of the budget on goods)
One planet will be eaten by Galactus. If you choose to sell on the planet that is to be eaten, you will receive nothing for your furniture. The triangle distribution does not factor the probability of being eaten into the price generation. The planet to be eaten will be determined at the end of the contest by a random number generator built into the game model.
Prices Day 1
Minimum, maximum, and mode for triangle distribution on Day 7
Responses to the contest will be made in the comments section of this post.
The participant with largest profit (highest amount of money at the end of the game) based on prices generated from the model will win 5 SBD. If we have several people with the same profit figure, the winner will be awarded to the participant who entered first (commented).
I will also give out 10 random upvotes to entries. Please take this as even more incentive to participate in this contest.
How to enter
All responses must be in the form of a single comment as shown below
Name of Planet: Menopion
Good purchased: Credenza
Amount spent on good: $3M
Name of Planet: Korganoog
Entry also requires 1 upvote of this post. Participants are not required to give a 100% upvote. You can give a 100% if you like or as low as 1%, it’s up to you. Each participant is only allowed one entry.
The closing date and time for this contest is 6PM USA Eastern Time 15/07/2018. Responses after this time will not be accepted. The answers will be provided in the results post along with the video of the generation of prices using the model.
I hope everyone has fun and enjoys this contest.
If you have any questions, feel free to ask in the comments section.
If you want to know more about the 'Buying and Selling Game' model you can watch a brief video I made which explains how the model operates using the link below.
Also, here is a link to the results post. This will give you a better idea of how it all plays out.