One of my favourite thought experiments is taking the dating marketplace (as in people finding their romantic partners) and using it to explain some key concepts that are applicable to any marketplace.
To explain as the dating marketplace here I mean people looking for their mates in life, not just on apps. In the end whatever strategy you employ to find your match, you are thus taking yourself and your mate “off the market”.
For simplicity let’s focus on the largest dating marketplace there is — monogamous cisgender heterosexual. Thus we have men and women seeking one mate at a time of the opposite gender.
Now there are two very important concepts that we need to understand supply/demand imbalance and free float ratio. But in the dating market they would likely be called gender ratio and single ratio.
In out case let’s assume that the population gender ratio is 52:48 women to men (in reality gender ratio depends on age, but let’s ignore it for now). Single ratio is basically the percentage of population that is single in the age bracket. Let’s look at three brackets (the numbers are imaginary, real single ratios range wildly across the world):
20% of people in their 20s
10% of people in their 30s
5% of people in their 40s
An extremely interesting effect in any market is the fact that the price is set by the minority actually doing transactions. In our case it means that the dating behaviour is determined by the available singles.
When looking at people in their 20s, 80% of people are coupled at any given time, meaning that 40 women and 40 men from each hundred are not available, resulting in the single women:men ratio becoming 12:8.
This is the imbalance amplification effect - the smaller the free float, the more the imbalances are amplified. On the stock exchange small float means high stock volatility, since ask/bid ratio is constantly changing, but in the dating world such imbalance is shown to affect the gender behavior, by changing their strategies to account for abundance or scarcity of mates.
But what’s extremely interesting is how further reducing the size of free float the amplification grows even higher. For the general population we had 52:48 = 1.08 women per man, for people in their 20s it grew to 1.5, for people in the 30s it’s 7:3 = 2.34 and for 40s it’s 4.5:0.5 = 9 women to one man!
So this is a key concept that is often missed in marketplaces. When most of the market isn’t trading (e.g. in ridehailing when most of the drivers are busy) the supply/demand imbalance can be amplified massively. This also is a part of the explanation how a bunch of guys from Reddit can manipulate stock markets :)
There are also some quite common situations in designing products when this imbalance occurs:
Overbooking a plane by 1-2% might result in 5 people fighting for the last seat
Improperly managing table bookings at a restaurant you can easily end up with long wait times for multiple customers
But of course the best examples today are the cryptocurrencies, a lot of which have a tiny float with insane daily volatility.