Introducing the Market Maker's Quoting System, Unveiling the Mystery of the "Dog庄" Conspiracy.

Author: Dave

Have you ever experienced a situation where some altcoins, after you buy them, the price consistently moves in the opposite direction in a short period, as if the "dog庄" is targeting you? Why is this happening? Is it really a conspiracy by the dog庄?

This post will introduce the market maker's quoting system and unveil the mystery of the "dog庄" conspiracy. To start with the conclusion: the price often moves against us not due to subjective manipulation, but because of the Inventory-based pricing quote skew under the Avellaneda–Stoikov model, and the protective mechanism for handling toxic flow. How does this work? Once upon a time…

First, let's understand the concept of inventory. Everyone knows that market makers are not directional investors. Under rigorous hedging, changes in spot prices should not affect the total PnL. At this point, holding inventory is a "passive" behavior. Changes in inventory lead to an expansion of positions; the more positions you hold, the greater your exposure to the risk of price reversals. At this time, retail traders' buy and sell orders cause changes in inventory, and market makers will respond to the risks brought about by these inventory changes.

In short, when you disrupt their balance, the market maker will find ways to protect themselves and try to return to balance. The means of protecting themselves is the quoting system.

1. Quote Skew

When you buy a large amount, it is equivalent to the market maker selling a large amount, resulting in a short exposure in their inventory. At this point, what does the market maker want to do? (1) Quickly replenish inventory. (2) Protect the exposed short position.

So the market maker's response is to lower the price, attract sell orders, prevent further buying, and ensure that their net short position remains temporarily unprofitable, giving them time to hedge.

2. Spread Widening

As inventory continues to deteriorate, the market maker not only skews the price but also widens the spread, reducing the probability of transactions.

Their goal is to lower the transaction risk per unit of time while earning more through spread profits to protect against price losses.

While writing this article, I found that every additional mathematical formula reduces the readership by 10%, but in case some friends want to see the details, I will briefly introduce how quotes are formed (which is also the mathematical mechanism behind the quote changes mentioned above).

The price at which we transact with market makers is called the Reservation Price, derived from the Inventory-based pricing model:

Reservation Price = Mid price − γ⋅q

q: Current inventory

gamma γ: Risk aversion coefficient

In fact, the Reservation Price looks like this, but I don't want to overwhelm you, so I'll just show you a glimpse.

When retail traders buy and sell in large quantities, q undergoes significant changes, leading to substantial changes in the Reservation Price. The specific amount of change comes from the Avellaneda–Stoikov model. You might guess that due to buying and selling, inventory undergoes small changes, and since these changes are small, this model is a partial differential equation. Guess what? I'm not interested in solving this equation, so we just need to know the core conclusion:

The optimal quote is symmetrically centered around the Reservation Price. Inventory will inevitably mean-revert to 0. The optimal spread widens with risk.

It's okay if you don't understand the above; just have a general idea that after retail traders buy, the price often moves against their bullish expectations. Essentially, our flow alters the market's risk pricing. The reasons retail traders often encounter this situation are:

• Retail traders are almost always on the active side.

• Size is concentrated, and the rhythm is not concealed.

• No hedging.

• No time separation, no order splitting.

In small altcoins, this situation is even more severe because the liquidity of altcoins is very poor. Often, your orders are just a few active orders within a 5-minute window. In larger assets, there may be natural hedging, but in small coins, you are essentially the counterpart to the dog庄.

So professional market makers do not want to blow you up; rather, they aim to maxE[Spread Capture]−Inventory Risk−Adverse Selection. In fact, their objective function looks like this, with inventory risk being exponentially penalized.

Readers who have made it this far must have dreams of becoming the dog庄, so to encourage the brave, I will share a little trick using the quoting mechanism. We say retail traders often have concentrated sizes and non-concealed rhythms, so we can turn that around. Suppose Dave wants to go long 1000u; instead of going all in at once, the dog庄's approach is to first buy 100u. The quoting system will lower the price, allowing me to build my position at a cheaper price. Then I buy another 100u, and the price will continue to drop, making my average holding cost much cheaper than going all in at once.

The story of retail traders' bad luck ends here for now. Besides the inventory management quoting factors, the market maker's handling of order flow is another element causing price divergence, which is the toxic order flow mentioned at the beginning. In the next post, I will introduce the market maker's order book and order flow, and I will also speculate on the micro-market reasons behind the 1011 disaster.

To know what happens next, stay tuned for the next installment.

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