Dr. StrangePulse or: How I Learned to Stop Getting Rekt and Pulse the World

There are three things that are hard to measure; the universe, the human imagination, and now, how to provide liquidity for a prediction market. We are still a couple of generations away from figuring out the first two, if you’ll come this way with us, the secret to liquidity provisioning is just around the corner.

The Uni(swap)versal Truth

Liquidity is a yardstick for measuring the ease of converting one asset to another. An asset is either liquid or illiquid, has good liquidity or the liquidity is poor. What this simply means is if you’re looking to buy $1000 worth of X and the counterparty has $1m worth of the asset, you can easily buy without any impact on the price — for all intent and purpose, your purchase is just a drop in the ocean. However, if your $100 sell makes the market value drop 1% or more, there’s a problem with the liquidity, rendering the market for the asset unattractive. No one likes exiting any market at a loss.

Traditionally, the market will often employ market makers — firms or individuals — to add liquidity and depth for buyers and sellers. These market makers will provide bids for buying and selling assets while profiting from the difference in the prices. With the launch of Automated Market Maker (AMM) for Decentralized Exchanges (DEXs), anyone can create and add liquidity to any asset pairing, while also earning fees.

AMMs typically work by creating a pool with two assets paired against each other, for example, BTC-ETH. Users deposit both assets into the pool with equal market value meaning if 1 BTC is worth 10 ETH and you have 2 ETH that you want to create liquidity for, you will either need to buy 0.2 BTC from somewhere to pair the 2 ETH with or sell 1 ETH for 0.1 BTC and pair it with the remaining ETH.

The price of the assets in the pool is determined by their relative percentage represented by the famous x * y = k formula. X and Y represent the sum total of each asset paired in the pool, while K is a fixed constant. Simply put, this equation uses supply and demand to determine the value of the asset. If there is more demand for X (resulting in buyers using Y to buy X), the price of X goes up as supply dwindles and the value of Y goes down as its supply increases.

The Nostrektdamus Prophecy

With this basic explanation of how liquidity provisioning works, time to get to the heart of the matter. Right off the bat, providing liquidity for the prediction market has a different set of risk parameters. The biggest risk for Liquidity Providers (LP) on normal AMMs is impermanent loss where demand for X may result in LPs holding a surplus of Y whose value keeps depreciating as the market continues to dump Y.

Prediction markets are more complicated. In Binary Prediction markets where winners take all, you are guaranteed that the value of one asset will go to zero. LPs in this market provide liquidity for both sides of the market — the yes and no, true or false, short or long — exposing them to both sides of the argument, however, there can only be one winning outcome. The goal as an LP is to add and remove liquidity at the best possible moment to maximize returns and minimize losses. This is one tough art to master and the science isn’t exact, however, the following pointers should hold you in good stead:

  1. You have to remove your liquidity before the outcome is known
  2. You have to enter the pool at odds that are likely to be competitive (a lot of trading will happen around these odds getting you more fees)
  3. You should probably remove your liquidity when something big is going to happen around the event of the market that could greatly swing the price and then enter back into the market after initial price discovery

And there you have it. One less mystery to contend with.

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Powered by Flux Protocol’s open financial market infrastructure, Pulse is a decentralized and open-source prediction platform governed and maintained by a DAO

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