Among many powerful features of digital technology, one of the most exciting ones is automation. From auto-translation to news-summation machine-learning, automating financial markets is evolving at a rapid pace.
Eliminating the Corruptive Potential from Market Makers
As Decentralized Finance — DeFi — keeps evolving, there will be a greater need to understand how decentralized systems can effectively replace centralized institutions exerting influence on financial markets. After all, if the GameStop/Robinhood/Citadel scandal has taught us anything, it’s that no amount of regulatory framework can work in the long run. Instead, we must move away from financial markets that heavily rely on hidden levers of power, activated when certain market players are threatened.
From the Liquidity Providers article, you have learned the critical role of market makers in the traditional financial arena:
- Market makers are liquidity providers.
- Market makers are both sellers and buyers.
- Market makers reap profits from their ask-bid spreads.
- Market makers make the market happen by meeting traders’ asks and bids at all price levels, thus providing necessary liquidity.
In the DeFi space, the vital role of providing liquidity is served by liquidity pools in which users — liquidity providers — add and lock-in their tokens. Incentivized by rewards — yield farming — the greater their stake is in the liquidity pool, the greater their profit becomes from interest rates.
In other words, market makers become automated because the trade is no longer conducted between buyers and sellers, facilitated by market makers in the form of hedge funds or exchanges. Instead, the trade is executed against liquidity pools — shared pools of various tokens present in the DeFi ecosystem. Furthermore, there are different types of automated market makers to keep in mind.
How Automated Market Makers Evolved
Coming into fruition on the Ethereum blockchain, automated market makers (AMMs) started as one would expect within the blockchain playground — on an internet post. Ethereum’s core developer, Vitalik Buterin, published a blog post on the topic of “on-chain market makers”. In it, he outlined how AMMs can work, based on the power of math:
tokenA balance(p) * tokenB_balance(p) = k
With the example provided in the Liquidity Providers, you already know that liquidity pools are created by token pairs, such as ETH–USDT. In the above formula, “k” represents a constant balance of these tokens. In turn, this determines the token prices in the liquidity pool.
Let’s take another example of a token pair that doesn’t rely on the USDT stablecoin. Both ETH and BTC are volatile cryptocurrencies compared to fiat money. If we have ETH-BTC for the liquidity pool, every time someone buys ETH, its price goes up because there is less ETH present in the liquidity pool. Vice-versa for BTC as well, the more of BTC in the liquidity pool there is, the lower its price.
As you can see, the entire asset price signaling would collapse without AMMs in place, by ensuring that every liquidity pool is in constant balance. In other words, the total value of a token is matched by the total value of its paired token in the liquidity pool.
However, there are times when AMMs make the DeFi market more interesting than usual. If AMM’s balancing veers slightly off from the token’s price on centralized exchanges, a money-making opportunity arises. This incentivizes traders to leverage the price differences generated by AMMs and centralized crypto exchanges until the balance is fully restored. This is often referred to as ‘arbitrage’.
After all, Buterin, in his original “on-chain market makers” blog post, cautioned against exclusively using AMMs to determine the token’s accurate price. Nonetheless, different AMM approaches emerged to tackle the issue of maintaining token price accuracy.
Different Automated Market Makers
Among dozens of DeFi platforms accounting for over $30 billion locked assets, three AMM models emerged on how to keep asset prices accurate:
Curve Finance – It creates liquidity pools by pairing up similar assets, such as stablecoins. Therefore, Curve has achieved a reputation for generating the most stable prices and speedy trades in the DeFi ecosystem. It launched in early 2020 and gained traction in the latter half of the year. By focusing on stablecoin liquidity pools, Curve can easily complete large-volume trades with an exceedingly low slippage — the price difference between the original market order and the executed one.
Uniswap – The first DeFi Ethereum protocol to create a liquidity pool of ERC-20 tokens with a 1:1 ratio. Any token qualifying as an ERC-20 token can be paired with any other ERC-20 token. With the current DeFi market share of $3.5 billion, Uniswap imposes a flat 0.3% fee for every trade from its liquidity pools, in which tokens must be deposited in a precise 50% ratio. Otherwise, a trader can’t join the pool.
Balancer – Growing in popularity, Balancer represents the maximum flexibility offered by AMMs. Unlike Uniswap, this DeFi protocol makes it possible to create liquidity pools with up to eight different tokens, with varying ratios to each other. Therefore, you can view it as an evolution of Uniswap with its multi-token liquidity pools, private pools, custom pool ratios, and dynamic pool fees. However, this extended flexibility leaves pools to vulnerabilities. One of them is the so-called STA Deflationary Hack, proving that tokens with questionable security features can endanger the integrity of the whole liquidity pool.
With these three approaches to AMMs governing price correction, we can see that each DeFi platform has its own advantages and disadvantages. Fortunately, thanks to secure and convenient wallets such as MetaMask, one can easily switch between them within a space of a few clicks. No doubt, by the end of this decade, we will see the DeFi ecosystem become as much a part of our financial lives as your e-banking smartphone apps.