Advancing MM 1: Market Maker Inventory Quoting System

深潮2025-12-28 tarihinde yayınlandı2025-12-28 tarihinde güncellendi

Özet

"Attack of the MM 1: Market Maker Inventory Quoting System" by Dave explores why altcoin prices often move against retail traders immediately after their purchases, debunking the myth of intentional manipulation by "market manipulators." The article explains that this phenomenon is not due to malicious intent but is a result of automated market maker (MM) systems using the Avellaneda-Stoikov model for inventory-based pricing and protection against toxic order flow. When retail traders execute large buy orders, MMs sell, leading to a short inventory exposure. To mitigate risk, MMs adjust their strategies in two ways: 1. **Quote Skew**: They lower prices to attract sellers and discourage further buys, aiming to replenish inventory and protect their short position. 2. **Spread Widening**: They widen bid-ask spreads to reduce transaction probability and earn more spread profit to offset potential losses. The core mechanism involves the "Reservation Price," calculated as Mid Price − γ⋅q (where q is inventory and γ is risk aversion). Large retail orders disrupt inventory balance, causing MMs to adjust prices dynamically. Retail traders often face this due to their concentrated, unconcealed, and unhedged orders, especially in low-liquidity altcoins where their trades significantly impact pricing. The article concludes with a practical tip: instead of executing large orders at once, retail traders can break them into smaller, staggered orders to exploit MM pricing adjustments,...

Author: Dave

Have you ever experienced a situation where, after buying some altcoins, the price keeps moving in the opposite direction in a short time, as if the "market manipulators" are targeting you? Why does this happen? Is it really a conspiracy by the manipulators?

This post will introduce the market maker's quoting system and unveil the mystery behind the "manipulator" conspiracy. The conclusion is: prices often move against us not due to subjective manipulation, but rather due to Inventory-based pricing quote skew under the Avellaneda–Stoikov model and the protective mechanism for handling toxic flow. How exactly? Once upon a time...

First, let's understand the concept of inventory. As we all know, market makers are not directional investors. Under strict hedging, spot price changes should not affect the total P&L. At this point, holding inventory is a "passive" behavior. Changes in inventory lead to an expansion of positions, and the more positions you hold, the greater your risk exposure to adverse price movements. At this time, retail traders' buy and sell orders cause changes, and market makers react to the risks brought by these inventory changes.

In a nutshell, you break their balance, and the MM has to protect themselves and try to return to balance. The means of protection is the quoting system.

1. Quote Skew

When the MM is heavily bought by you, it is equivalent to: the MM has sold heavily, and the inventory becomes a short exposure. What does the MM hope to do at this time: (1) Replenish the inventory as soon as possible. (2) Protect the exposed short position.

So the MM's reaction is: lower the price to attract selling, prevent further buying, and ensure that their net short position remains temporarily non-loss-making, giving time to hedge.

2. Spread Widening

When the inventory continues to deteriorate, the MM not only skews the price but also widens the spread to reduce the probability of execution.

Their goal is to reduce the execution risk per unit time and, through spread profits, earn more to protect against price losses.

While writing this article, each additional mathematical formula reduces the number of readers by 10%, but in case some小伙伴们 want to see something substantial, I will briefly introduce the formation of quotes (which is also the mathematical mechanism behind the above quote changes).

The price at which we trade with the market maker is called the Reservation Price, which comes from the Inventory-based pricing model:

Reservation Price = Mid price − γ⋅q

q: current inventory

gamma γ: risk aversion coefficient

Actually, the Reservation Price looks like the following, but I don't want to disgust everyone, so just take a glance:

When retail traders buy or sell heavily, q changes significantly, causing the quoted Reservation Price to change significantly. The specific amount of change comes from the Avellaneda–Stoikov model. As you might guess, since buying and selling cause small changes in inventory, this model is a partial differential equation. Guess what? I'm not interested in deriving this equation either, so we only need to know the core conclusion:

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

If you don't understand the above, it's okay. Just roughly understand that after retail buying, prices often move against the bullish direction, essentially because our flow changes the market's risk pricing. The reasons why retail traders often encounter this situation are:

• Retail traders almost always use aggressive orders

• Concentrated size, non-stealthy timing

• No hedging

• Not timing the market, not splitting orders

In small altcoins, this situation is even more severe because altcoin liquidity is poor. Often, your order is one of the few aggressive orders within 5 minutes. In large品种, natural hedging might occur, but in small coins, you are the counterparty to the manipulator.

So professional MMs are not trying to crush you; their objective is maxE[Spread Capture]−Inventory Risk−Adverse Selection. Actually, their objective function looks like this, with inventory risk being exponentially penalized.

Readers who have made it this far must be韭菜 with dreams of becoming market manipulators. So to激励 the brave, I'll share a small trick to utilize the quoting mechanism. We said retail traders often have concentrated size and non-stealthy timing, so just do the opposite. Suppose Dave wants to go long 1000U. Instead of going all in at once, using the manipulator's method, first buy 100U. The quoting system will lower the price, allowing me to build a position at a cheaper level. Then I buy another 100U, and the price will continue to fall. Thus, my average entry cost will be much cheaper than going all in at once.

The story of retail's bad luck is only half told here. Besides inventory management quoting factors, the MM's handling of order flow is another element causing price divergence, namely the toxic order flow mentioned at the beginning. In the next part, 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惨案.

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

İlgili Sorular

QWhat is the main reason why altcoin prices often move against retail traders after they buy, according to the article?

AIt is not due to subjective manipulation, but rather the result of the Avellaneda-Stoikov model's Inventory-based pricing quote skew and a protection mechanism against toxic order flow.

QHow does a market maker (MM) react when its inventory becomes short due to a large buy order from a retail trader?

AThe MM will lower its prices to attract sell orders and discourage further buying, while also widening the bid-ask spread to reduce the probability of execution and protect its exposed short position.

QWhat is the 'Reservation Price' in the context of the market maker's pricing model?

AThe Reservation Price is the price at which traders transact with the market maker. It is derived from the Inventory-based pricing model and is calculated as: Reservation Price = Mid price - γ * q, where q is the current inventory and γ is the risk aversion coefficient.

QWhat are the characteristics of retail trader orders that make them particularly vulnerable to price movements against them?

ARetail orders are often aggressive (taking liquidity), concentrated in size, not stealthy in timing, unhedged, and not split or timed strategically.

QWhat practical tip does the article suggest for a retail trader who wants to buy a large position to get a better average entry price?

AInstead of buying the entire position at once, the trader should split the order into smaller chunks. Buying a small amount first causes the MM's pricing system to lower the price, allowing subsequent buys to be executed at cheaper levels, resulting in a lower average cost.

İlgili Okumalar

a16z: AI's 'Amnesia', Can Continuous Learning Cure It?

The article "a16z: AI's 'Amnesia' – Can Continual Learning Cure It?" explores the limitations of current large language models (LLMs), which, like the protagonist in the film *Memento*, are trapped in a perpetual present—unable to form new memories after training. While methods like in-context learning (ICL), retrieval-augmented generation (RAG), and external scaffolding (e.g., chat history, prompts) provide temporary solutions, they fail to enable true internalization of new knowledge. The authors argue that compression—the core of learning during training—is halted at deployment, preventing models from generalizing, discovering novel solutions (e.g., mathematical proofs), or handling adversarial scenarios. The piece introduces *continual learning* as a critical research direction to address this, categorizing approaches into three paths: 1. **Context**: Scaling external memory via longer context windows, multi-agent systems, and smarter retrieval. 2. **Modules**: Using pluggable adapters or external memory layers for specialization without full retraining. 3. **Weights**: Enabling parameter updates through sparse training, test-time training, meta-learning, distillation, and reinforcement learning from feedback. Challenges include catastrophic forgetting, safety risks, and auditability, but overcoming these could unlock models that learn iteratively from experience. The conclusion emphasizes that while context-based methods are effective, true breakthroughs require models to compress new information into weights post-deployment, moving from mere retrieval to genuine learning.

marsbit2 saat önce

a16z: AI's 'Amnesia', Can Continuous Learning Cure It?

marsbit2 saat önce

Can a Hair Dryer Earn $34,000? Deciphering the Reflexivity Paradox in Prediction Markets

An individual manipulated a weather sensor at Paris Charles de Gaulle Airport with a portable heat source, causing a Polymarket weather market to settle at 22°C and earning $34,000. This incident highlights a fundamental issue in prediction markets: when a market aims to reflect reality, it also incentivizes participants to influence that reality. Prediction markets operate on two layers: platform rules (what outcome counts as a win) and data sources (what actually happened). While most focus on rules, the real vulnerability lies in the data source. If reality is recorded through a specific source, influencing that source directly affects market settlement. The article categorizes markets by their vulnerability: 1. **Single-point physical data sources** (e.g., weather stations): Easily manipulated through physical interference. 2. **Insider information markets** (e.g., MrBeast video details): Insiders like team members use non-public information to trade. Kalshi fined a剪辑师 $20,000 for insider trading. 3. **Actor-manipulated markets** (e.g., Andrew Tate’s tweet counts): The subject of the market can control the outcome. Evidence suggests Tate’sociated accounts coordinated to profit. 4. **Individual-action markets** (e.g., WNBA disruptions): A single person can execute an event to profit from their pre-placed bets. Kalshi and Polymarket handle these issues differently. Kalshi enforces strict KYC, publicly penalizes insider trading, and reports to regulators. Polymarket, with its anonymous wallet-based system, has historically been more permissive, arguing that insider information improves market accuracy. However, it cooperated with authorities in the "Van Dyke case," where a user traded on classified government information. The core paradox is reflexivity: prediction markets are designed to discover truth, but their financial incentives can distort reality. The more valuable a prediction becomes, the more likely participants are to influence the event itself. The market ceases to be a mirror of reality and instead shapes it.

marsbit3 saat önce

Can a Hair Dryer Earn $34,000? Deciphering the Reflexivity Paradox in Prediction Markets

marsbit3 saat önce

İşlemler

Spot
Futures

Popüler Makaleler

WL Nedir

I. Proje TanıtımıWorldLand, Ethereum ekosistemini geliştirmek için tasarlanmış, Ethereum'un L2 veya yan zinciridir.II. Token Bilgileri1) Temel BilgilerToken adı: WL (WorldLand)III. İlgili BağlantılarWeb sitesi:https://worldland.foundation/Keşif Araçları:https://bscscan.com/address/0x8aaB31fbc69C92fa53f600910Cf0f215531F8239Sosyal Medya:https://x.com/WorldLand_space Not: Proje tanıtımı, resmi proje ekibi tarafından yayımlanan veya sağlanan materyallerden gelmektedir, yalnızca referans amaçlıdır ve yatırım tavsiyesi niteliği taşımaz. HTX, ortaya çıkan doğrudan veya dolaylı kayıplardan sorumluluk kabul etmez.

161 Toplam GörüntülenmeYayınlanma 2026.03.28Güncellenme 2026.03.28

WL Nedir

WL Nasıl Satın Alınır

HTX.com’a hoş geldiniz! WorldLand (WL) satın alma işlemlerini basit ve kullanışlı bir hâle getirdik. Adım adım açıkladığımız rehberimizi takip ederek kripto yolculuğunuza başlayın. 1. Adım: HTX Hesabınızı OluşturunHTX'te ücretsiz bir hesap açmak için e-posta adresinizi veya telefon numaranızı kullanın. Sorunsuzca kaydolun ve tüm özelliklerin kilidini açın. Hesabımı Aç2. Adım: Kripto Satın Al Bölümüne Gidin ve Ödeme Yönteminizi SeçinKredi/Banka Kartı: Visa veya Mastercard'ınızı kullanarak anında WorldLand (WL) satın alın.Bakiye: Sorunsuz bir şekilde işlem yapmak için HTX hesap bakiyenizdeki fonları kullanın.Üçüncü Taraflar: Kullanımı kolaylaştırmak için Google Pay ve Apple Pay gibi popüler ödeme yöntemlerini ekledik.P2P: HTX'teki diğer kullanıcılarla doğrudan işlem yapın.Borsa Dışı (OTC): Yatırımcılar için kişiye özel hizmetler ve rekabetçi döviz kurları sunuyoruz.3. Adım: WorldLand (WL) Varlıklarınızı SaklayınWorldLand (WL) satın aldıktan sonra HTX hesabınızda saklayın. Alternatif olarak, blok zinciri transferi yoluyla başka bir yere gönderebilir veya diğer kripto para birimlerini takas etmek için kullanabilirsiniz.4. Adım: WorldLand (WL) Varlıklarınızla İşlem YapınHTX'in spot piyasasında WorldLand (WL) ile kolayca işlemler yapın.Hesabınıza erişin, işlem çiftinizi seçin, işlemlerinizi gerçekleştirin ve gerçek zamanlı olarak izleyin. Hem yeni başlayanlar hem de deneyimli yatırımcılar için kullanıcı dostu bir deneyim sunuyoruz.

208 Toplam GörüntülenmeYayınlanma 2026.03.28Güncellenme 2026.03.28

WL Nasıl Satın Alınır

BASED Nasıl Satın Alınır

HTX.com’a hoş geldiniz! Based (BASED) satın alma işlemlerini basit ve kullanışlı bir hâle getirdik. Adım adım açıkladığımız rehberimizi takip ederek kripto yolculuğunuza başlayın. 1. Adım: HTX Hesabınızı OluşturunHTX'te ücretsiz bir hesap açmak için e-posta adresinizi veya telefon numaranızı kullanın. Sorunsuzca kaydolun ve tüm özelliklerin kilidini açın. Hesabımı Aç2. Adım: Kripto Satın Al Bölümüne Gidin ve Ödeme Yönteminizi SeçinKredi/Banka Kartı: Visa veya Mastercard'ınızı kullanarak anında Based (BASED) satın alın.Bakiye: Sorunsuz bir şekilde işlem yapmak için HTX hesap bakiyenizdeki fonları kullanın.Üçüncü Taraflar: Kullanımı kolaylaştırmak için Google Pay ve Apple Pay gibi popüler ödeme yöntemlerini ekledik.P2P: HTX'teki diğer kullanıcılarla doğrudan işlem yapın.Borsa Dışı (OTC): Yatırımcılar için kişiye özel hizmetler ve rekabetçi döviz kurları sunuyoruz.3. Adım: Based (BASED) Varlıklarınızı SaklayınBased (BASED) satın aldıktan sonra HTX hesabınızda saklayın. Alternatif olarak, blok zinciri transferi yoluyla başka bir yere gönderebilir veya diğer kripto para birimlerini takas etmek için kullanabilirsiniz.4. Adım: Based (BASED) Varlıklarınızla İşlem YapınHTX'in spot piyasasında Based (BASED) ile kolayca işlemler yapın.Hesabınıza erişin, işlem çiftinizi seçin, işlemlerinizi gerçekleştirin ve gerçek zamanlı olarak izleyin. Hem yeni başlayanlar hem de deneyimli yatırımcılar için kullanıcı dostu bir deneyim sunuyoruz.

222 Toplam GörüntülenmeYayınlanma 2026.03.30Güncellenme 2026.03.30

BASED Nasıl Satın Alınır

Tartışmalar

HTX Topluluğuna hoş geldiniz. Burada, en son platform gelişmeleri hakkında bilgi sahibi olabilir ve profesyonel piyasa görüşlerine erişebilirsiniz. Kullanıcıların A (A) fiyatı hakkındaki görüşleri aşağıda sunulmaktadır.

活动图片