# Beer Stock Exchange

by **Daniel Dyla**

- Let
`S(x)`

be the sigmoid function. - Let
`t`

be the time period between price changes - Let
`p`

be the starting price for a given beer. - Let
`s`

be the amount of $ you want to let the price “swing”. E.G a 0.5`s`

would let a beer that costs $3 base cost from $2.5 to $3.5 - Let
`c`

be the amount you want to allow any given beer’s x to change in a single trading period (I’m going to use .5). - Let
`l`

be the largest absolute value of the difference between actual sales of each beer and the average sales per beer. - Let
`a`

be the normalizing factor where`a = l/c`

## Abusing the Sigmoid Function for fun and profit

We need to modify our sigmoid function so that we can control its min and max.

- Realize
`S(x)`

has a base price of $0.50 with a $0.50 swing. - =>
`S(x)-.5`

has a base price of $0 with a $0.50 swing. - =>
`2(S(x)-.5)`

has a base price of $0 with a $1 swing. - =>
`2s * (S(x)-.5) + b`

has a base price of`b`

with a swing of`s`

.

## Description of the algorithm

Start with your list of beers `[b1,b2,b3,b4,b5]`

.At the beginning of the night the price for all beers is its base price (`x=0`

)
`[0,0,0,0,0]`

.
At the end of each trading period, count the number of beers sold in the time period `[135, 152, 65, 103, 201]`

.
Find the average number sold per beer (`131.2`

) and find the difference between average and actual number sold for each beer
`[3.8, 20.8, -66.2, -28.2, 69.8]`

. Normalize this against your `c`

by dividing by `a`

(139.6) to get `[0.03, 0.15, -0.47, -0.20, 0.5]`

.
This becomes the change between the old x and the new x for each beer. If you never round, the average x will always be 0, however this
is not feasible so you may want to normalize x every few rounds to make sure your average x stays 0.

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