Exploring the Mechanics of Automated Market Makers

When I’m sipping coffee on the balcony in Lisbon, I think about how much easier it would be for people to get a piece of the market without having to go through a broker or a lot of paperwork. The market becomes something you can lean on, not something that bites back because you’re unfamiliar with how it works. A lot of people are still stuck in the old model of using a traditional exchange, filling out orders, and waiting to see if someone will match them. That friction can feel like a hurdle in front of your savings or your dream.

Automated Market Makers, or AMMs, aim to reduce that friction. They let you trade directly with a pool of liquidity that the platform itself manages. When you deposit the right combination of tokens, you’re essentially becoming a market maker yourself, supplying the book for the market by providing the assets required for other traders to swap.

We all know the story of a liquidity provider who accidentally lost their capital because of impermanent loss. It’s one of those stories that gets told each time a new DeFi protocol pops up. But that story also reflects a market dynamic that has been around since early days of exchanges: who supplies the liquidity, and how does the market determine the price? AMMs are a way to automate that dynamic.

Let’s zoom out from the pool and look at the core primitive: a mathematical formula that sets the price. The most common is the constant product market maker, expressed as the equation x × y = k. In this version, two assets, x and y, are pooled together. The product of the two balances must equal a constant, k. Whenever someone swaps one token for another, the balances shift, but the product stays the same. This simple relationship guarantees that the pool can always offer a price, and it automatically adjusts that price based on the relative supply in the pool.

Imagine a garden where you mix two kinds of seeds in proportions that stay consistent. If one seed becomes scarce because many gardeners pick it, the mix will lean on the other seed. That’s how price adjusts on the fly, no need for a human to update it.

The constant product model makes sense when you think of liquidity as a buffer against volatility. In the garden analogy, the more water you have in the pot, the less likely the plants will thirst. In DeFi, the more capital you lock into a pool, the more you protect traders from huge price swings.

A trade in an AMM also has a built‑in fee, usually a fraction of the trade volume (often around 0.3 %). That fee is added to the pool and then distributed back to liquidity providers. Because the fee accrues continuously, providing liquidity becomes a steady source of passive income, albeit with the risk of impermanent loss.

Why “impermanent” loss matters

Impermanent loss occurs when the price ratio of the pooled tokens diverges from when you joined. If you deposited equal values of token A and token B, and the market later values token A higher, the pool’s reserve will now contain more of B and less of A—meaning you’ve effectively sold some of your A. If you withdraw at that point, you might end up with less than your original capital, even after adding the earned fees. However, the loss is “impermanent” because if the price ratio returns to the original ratio, your capital might rebalance.

The fear in the narrative of impermanent loss is that traders won’t stay if they see losses. That’s a legitimate concern, and it underscores the need for good data and transparency. A platform that shows real‑time impermanent loss curves will let providers decide if the risk is acceptable.

Beyond the constant product, there are generalized market makers, or GMMs, that allow other price‐curve functions. For instance, the constant sum model uses the equation x + y = c. That shape is useful for stablecoin pools, because you want prices near the peg and you don’t want them to rise too sharply as supply changes.

Other protocols use a virtual balance or virtual price model that introduces a “price impact” coefficient. This adds a controlled slippage curve. Take the example of Curve on stablecoins: they use a weighted function to keep prices very tight for assets that track the same value, while still delivering the benefits of an AMM.

From a practical viewpoint, the generalization is like having adjustable knobs for the shape of your garden. If you’re planting a delicate herb that can handle less sun, you set the knob to keep it in a shaded area. If you’re growing tomatoes that crave full sun, you crank that knob up.

Let’s walk through a practical example that feels less abstract. You have two tokens, ETH and DAI, and you want to set up a liquidity pool that will let people swap between them. The price of ETH is 2000 DAI. In a constant product pool, if you want to start with an equal dollar value, you could deposit 2 ETH and 4000 DAI. The product k would be 2 × 4000 = 8000.

Someone wants to swap 1 ETH for DAI. The new balance of ETH will become 3. The new balance of DAI will solve for k: 3 × y = 8000 → y ≈ 2666.67 DAI. That means the pool will give 1333.33 DAI back. The price here is not exactly 2000 DAI per ETH because of the fee and the pool’s math. The difference is the slippage; the more you trade relative to pool size, the greater the slippage.

Now imagine a 0.3 % fee. That fee goes into the pool: the amount of DAI the pool receives is slightly less than 1 ETH divided by the price, because 0.3 % is taken as a buffer. Over time, the fee accumulation makes the pool gradually larger, and the fee income compensates providers for potential impermanent loss.

In the early days of DeFi, pools were typically created as a pair of tokens only. Later, some protocols introduced “meta pools” that let multiple token types share liquidity, and “weighted pools” that enable more complex ratio distributions. The weighted pools allow for different token weights—think of a gardener who chooses to plant more of certain plants because they need more support.

When you provide liquidity to a weighted pool, you must deposit tokens in a specific ratio. If you think one token will outperform the others, you can skew your risk accordingly. This flexibility is powerful but also demands that you understand how those ratios evolve with market dynamics.

The emotional terrain around AMMs is layered. There’s the excitement of “now anyone can be a market maker” and the fear that “what if I lose my capital?” There’s a hope people can earn a passive stream in a market that traditionally rewards active traders. There’s also the dread of impermanent loss and the skepticism that these systems hide complex math behind a simple UI.

When I talk to people, I often see them echoing the feeling that, "I love the idea of decentralised finance, but the math and risk make me wary." That’s why I keep the conversation grounded. I don’t promise gold, I provide clarity and give them a sense of what to look out for.

It’s less about timing, more about time. And that applies to liquidity provision as the same way it applies to long‑term investing. The value of your capital may not be obvious day‑by‑day. Impermanent loss may be small now, but over months of fee income, that same capital could grow.

The market’s “test patience before rewarding it” is a sentiment that fits both DeFi and traditional investing. When the pool grows, fees accumulate. The rewards are capped by the pool’s depth and volatility. When the market is highly volatile, the pool can suffer larger price slippage, but also earns more fees.

A simple analogy is a community garden. Each resident brings a certain amount of seeds (tokens) to the plot. The garden is meant to grow vegetables for everyone. The garden’s health (pool depth) ensures that a person who picks an eggplant (swap) doesn’t eat the entire crop. Over time, if the garden’s yield (fees) surpasses what each resident might have harvested privately, the garden becomes worthwhile for the whole community—even if a particular resident’s harvest was a bit lower than expected because they chose to plant a riskier crop.

What is the takeaway for someone who just wants to dive in?

When you consider adding liquidity to an AMM, ask yourself three questions:

1. Do I understand the price curve? Is it a constant product, constant sum, weighted, or something else? Knowing the math helps you foresee potential slippage or price impact.

2. What are the expected fees and how do they compare to potential impermanent loss? Look at the historical yield for that pool. If the fee rate is high and the pool has low volatility, you might end up with positive net returns.

3. How much capital am I comfortable locking up? Think in terms of a budget: the token portion that you leave in the pool should be something you could live without if the market turns around.

Once you feel confident on those points, add a small amount, monitor the pool, and slowly scale if the metrics align with your risk tolerance.

By treating liquidity provision like a monthly saving plan—contributing a modest amount with a clear understanding of how it will grow over time—you can reduce the fear of impermanent loss being the sole outcome. You’re not betting; you’re simply giving your capital a home in a system that rewards its presence.

Remember, the most valuable thing a market maker can do is keep the market alive. By adding depth, you help traders get better prices, and that, in turn, nurtures a healthier ecosystem. That symbiosis is why AMMs succeed, and why they deserve a spot in the broader conversation about financial empowerment.