![bc1qDave's tweet photo. [Attack on MM 3: Statistical Advantages and Signal Design ]
The previous two episodes mentioned order flow and inventory quotes, which sound like market makers can only passively adjust, but do they have proactive means? The answer is yes. Today, we'll introduce statistical advantages and signal design, which are also the "micro alpha" that market makers pursue.
1, wtf is Market Makers' Alpha?
Micro alpha refers to a "conditional probability shift" in the direction of the next price movement / mid-price drift / asymmetry in executions over extremely short time scales (~100ms to ~10s).
It's important to note that the alpha in the eyes of market makers (MMs) isn't about trend prediction or guessing the magnitude of rises and falls; it just needs a probability shift. This is different from the alpha we commonly talk about.
Next, I'll explain it in plain language:Market makers' statistical advantage can be understood as, within an extremely short time window, whether the order book state "leans toward" making the price move one step in a certain direction first. If MMs successfully calculate the probability of the price direction in the next millisecond through some indicators, they can:
1. Be more willing to buy before a more likely rise. 2. Withdraw buy orders faster before a more likely fall. 3. Reduce exposure during dangerous moments.
The financial foundation for predicting the next price direction is: due to factors like order flow, order volume, and order book cancellation ratios (which we'll discuss later), the market isn't a "random walk" Brownian motion in a short instant but has directionality. The above sentence is the financial translation of the mathematical concept of "conditional probability."With these alphas, market makers can directionally operate on prices, and the "house" finally earns money from price levels rather than just spreads as service fees.
2, Classic Signal Introduction
2.1 Order Book Imbalance: OBI
OBI looks at which side has "more people standing" near the current price level; it's a standardized volume differential statistic.This formula is actually not difficult—it's just a summation of proportional logic. It checks if there are more buy orders or sell orders.
OBI approaching 1 means almost all are bid orders, with thick support below. Approaching -1 means thick resistance above. Approaching 0 means buys and sells are relatively symmetric. It's worth noting that OBI is a "static snapshot," a classic indicator but ineffective on its own; it needs to be used with cancellation ratios, order book slopes, etc.
2.2 Order Flow Imbalance (OFI)
OFI looks at who has been aggressively attacking in the recent short period. OFI is the first-order driver of price changes because prices are driven by taker orders, not by limit orders. It has a bit of a net buy-sell volume feel.
In the Kyle (1985) framework, ΔP ≈ λ ⋅ OFI, where λ is the tick depth, so OFI is the factor that drives prices.
2.3 Queue Dynamics
Most exchanges now use continuous auction rules, following best price and FCFS (first-come, first-served) principles, so submitted orders queue up to be filled. The queue represents the limit order situation, and the queue determines the order book state. Abnormal order book states (including replenishment and cancellation situations) imply directional price changes, which is micro alpha.Queues need attention in two situations:
1, Iceberg: Hidden orders.
For example, only 10 lots are visibly hanging, but every time they're filled, another 10 lots are immediately replenished. The actual true intention might be 1,000 lots. The method I introduced in the first episode for annoying market makers to lower cost basis is actually a manual iceberg. In practice, some players who want to hide real order sizes also use icebergs.
2, Spoof (Fake Orders).
Hanging large orders on one side to create a "pressure illusion," then quickly withdrawing them before the price approaches. Spoofing pollutes OBI and Slope, etc., making the queue falsely thicken and increasing movement risk. At the same time, some large spoofs can scare the market and potentially manipulate prices. The London exchange caught a guy manipulating forex in 2015 who used spoofing. But in the crypto world, we can also manually spoof to annoy market makers, but if it actually gets filled, your exposure becomes huge.
2.4 Order Book Cancellation Ratio (Cancel Ratio)
The cancellation ratio is an estimate of liquidity "disappearance rate": Cancel ↑ ⇒ Slope ↓ ⇒ λ ↑ ⇒ ΔP more sensitive. It's a leading instability signal ahead of OFI. CR → 1: Almost pure cancellations. CR → 0: Almost pure replenishments. The mathematical formulas in this episode are all simple; you can interpret them by looking at charts.
CR ↑ ⟹ The passive side believes future risk is rising. At the same time, CR isn't used alone; it's always combined with OFI and such.
The above might just be some outdated order book games; market making evolves quickly, and after stocks go on-chain, JS and other MMs might all get involved in on-chain market making. But these indicators are still useful and inspiring.
3, Market Makers' Absolute Domain: Speed
We often hear in movies that a certain fund has faster internet, so they're more badass. Including how many market makers move their server rooms closer to exchange servers—why is that? At the end of this article, let's talk about the advantages of physical equipment and the "execution advantage" unique to crypto exchanges.
Latency Arbitrage isn't about predicting future prices but about executing buy/sell orders at more favorable prices "before others react." In theoretical models: Prices are continuous, information is synchronous. But in reality: Markets are event-driven, information arrives asynchronously. Why does information arrive asynchronously? Because receiving exchange price signals and sending order instructions to the exchange both take time—this is a physical world limitation. Even in fully compliant markets: Different exchanges, different data sources, different matching engines, different geographic locations all cause delays. So MMs with more advanced equipment have the initiative.
This tests the market makers' own strength and has little to do with other players, so I think it's their absolute domain.The simplest example: Suppose you want to sell a position, and you quote at the market's best ask price, theoretically it should execute, but I also want to sell. Since I see prices and quote faster than you, I fill the order first, leaving your inventory unable to exit, preventing your position from returning to neutral.
Real situations are much more complex. An interesting point is that, since there's no regulation yet, almost all crypto exchanges can directly give priority execution rights to specified accounts. Meaning, the right to cut in line for certain specified accounts. This is especially common in small exchanges, showing that in crypto, becoming an "insider" is as important as in research. Whether you can safely execute is a key step from alpha theory to practice.
In this episode, I tried writing from the MM perspective; actual operations are definitely more complex, like dynamic queues and many details to watch in practice. Welcome comment.
Postscript: Actually, this article has a regret. The title "Domain Expansion in Market Making" was originally meant for dynamic hedging and options, because I think that's the conceptually hardest part of market making, worthy of the big move "domain expansion." But I worked on it all day yesterday, wrote half the article, and really didn't know how to systematically explain it, so I switched to micro alpha.
Danny has an article that mentions many professional hedging concepts; I encourage everyone to check it out: https://t.co/xwAtz9WXjs.
We'll talk about that section later, perhaps sharing it in fragments.
Thanks for supporting the Advancing MM series, stay tuned.](https://pbs.twimg.com/media/G9I0YdjbgAILWfs.png)
![bc1qDave's tweet photo. [Attack on MM 3: Statistical Advantages and Signal Design ]
The previous two episodes mentioned order flow and inventory quotes, which sound like market makers can only passively adjust, but do they have proactive means? The answer is yes. Today, we'll introduce statistical advantages and signal design, which are also the "micro alpha" that market makers pursue.
1, wtf is Market Makers' Alpha?
Micro alpha refers to a "conditional probability shift" in the direction of the next price movement / mid-price drift / asymmetry in executions over extremely short time scales (~100ms to ~10s).
It's important to note that the alpha in the eyes of market makers (MMs) isn't about trend prediction or guessing the magnitude of rises and falls; it just needs a probability shift. This is different from the alpha we commonly talk about.
Next, I'll explain it in plain language:Market makers' statistical advantage can be understood as, within an extremely short time window, whether the order book state "leans toward" making the price move one step in a certain direction first. If MMs successfully calculate the probability of the price direction in the next millisecond through some indicators, they can:
1. Be more willing to buy before a more likely rise. 2. Withdraw buy orders faster before a more likely fall. 3. Reduce exposure during dangerous moments.
The financial foundation for predicting the next price direction is: due to factors like order flow, order volume, and order book cancellation ratios (which we'll discuss later), the market isn't a "random walk" Brownian motion in a short instant but has directionality. The above sentence is the financial translation of the mathematical concept of "conditional probability."With these alphas, market makers can directionally operate on prices, and the "house" finally earns money from price levels rather than just spreads as service fees.
2, Classic Signal Introduction
2.1 Order Book Imbalance: OBI
OBI looks at which side has "more people standing" near the current price level; it's a standardized volume differential statistic.This formula is actually not difficult—it's just a summation of proportional logic. It checks if there are more buy orders or sell orders.
OBI approaching 1 means almost all are bid orders, with thick support below. Approaching -1 means thick resistance above. Approaching 0 means buys and sells are relatively symmetric. It's worth noting that OBI is a "static snapshot," a classic indicator but ineffective on its own; it needs to be used with cancellation ratios, order book slopes, etc.
2.2 Order Flow Imbalance (OFI)
OFI looks at who has been aggressively attacking in the recent short period. OFI is the first-order driver of price changes because prices are driven by taker orders, not by limit orders. It has a bit of a net buy-sell volume feel.
In the Kyle (1985) framework, ΔP ≈ λ ⋅ OFI, where λ is the tick depth, so OFI is the factor that drives prices.
2.3 Queue Dynamics
Most exchanges now use continuous auction rules, following best price and FCFS (first-come, first-served) principles, so submitted orders queue up to be filled. The queue represents the limit order situation, and the queue determines the order book state. Abnormal order book states (including replenishment and cancellation situations) imply directional price changes, which is micro alpha.Queues need attention in two situations:
1, Iceberg: Hidden orders.
For example, only 10 lots are visibly hanging, but every time they're filled, another 10 lots are immediately replenished. The actual true intention might be 1,000 lots. The method I introduced in the first episode for annoying market makers to lower cost basis is actually a manual iceberg. In practice, some players who want to hide real order sizes also use icebergs.
2, Spoof (Fake Orders).
Hanging large orders on one side to create a "pressure illusion," then quickly withdrawing them before the price approaches. Spoofing pollutes OBI and Slope, etc., making the queue falsely thicken and increasing movement risk. At the same time, some large spoofs can scare the market and potentially manipulate prices. The London exchange caught a guy manipulating forex in 2015 who used spoofing. But in the crypto world, we can also manually spoof to annoy market makers, but if it actually gets filled, your exposure becomes huge.
2.4 Order Book Cancellation Ratio (Cancel Ratio)
The cancellation ratio is an estimate of liquidity "disappearance rate": Cancel ↑ ⇒ Slope ↓ ⇒ λ ↑ ⇒ ΔP more sensitive. It's a leading instability signal ahead of OFI. CR → 1: Almost pure cancellations. CR → 0: Almost pure replenishments. The mathematical formulas in this episode are all simple; you can interpret them by looking at charts.
CR ↑ ⟹ The passive side believes future risk is rising. At the same time, CR isn't used alone; it's always combined with OFI and such.
The above might just be some outdated order book games; market making evolves quickly, and after stocks go on-chain, JS and other MMs might all get involved in on-chain market making. But these indicators are still useful and inspiring.
3, Market Makers' Absolute Domain: Speed
We often hear in movies that a certain fund has faster internet, so they're more badass. Including how many market makers move their server rooms closer to exchange servers—why is that? At the end of this article, let's talk about the advantages of physical equipment and the "execution advantage" unique to crypto exchanges.
Latency Arbitrage isn't about predicting future prices but about executing buy/sell orders at more favorable prices "before others react." In theoretical models: Prices are continuous, information is synchronous. But in reality: Markets are event-driven, information arrives asynchronously. Why does information arrive asynchronously? Because receiving exchange price signals and sending order instructions to the exchange both take time—this is a physical world limitation. Even in fully compliant markets: Different exchanges, different data sources, different matching engines, different geographic locations all cause delays. So MMs with more advanced equipment have the initiative.
This tests the market makers' own strength and has little to do with other players, so I think it's their absolute domain.The simplest example: Suppose you want to sell a position, and you quote at the market's best ask price, theoretically it should execute, but I also want to sell. Since I see prices and quote faster than you, I fill the order first, leaving your inventory unable to exit, preventing your position from returning to neutral.
Real situations are much more complex. An interesting point is that, since there's no regulation yet, almost all crypto exchanges can directly give priority execution rights to specified accounts. Meaning, the right to cut in line for certain specified accounts. This is especially common in small exchanges, showing that in crypto, becoming an "insider" is as important as in research. Whether you can safely execute is a key step from alpha theory to practice.
In this episode, I tried writing from the MM perspective; actual operations are definitely more complex, like dynamic queues and many details to watch in practice. Welcome comment.
Postscript: Actually, this article has a regret. The title "Domain Expansion in Market Making" was originally meant for dynamic hedging and options, because I think that's the conceptually hardest part of market making, worthy of the big move "domain expansion." But I worked on it all day yesterday, wrote half the article, and really didn't know how to systematically explain it, so I switched to micro alpha.
Danny has an article that mentions many professional hedging concepts; I encourage everyone to check it out: https://t.co/xwAtz9WXjs.
We'll talk about that section later, perhaps sharing it in fragments.
Thanks for supporting the Advancing MM series, stay tuned.](https://pbs.twimg.com/media/G9I0Q-YaYAAcgTq.jpg)
![bc1qDave's tweet photo. [Attack on MM 3: Statistical Advantages and Signal Design ]
The previous two episodes mentioned order flow and inventory quotes, which sound like market makers can only passively adjust, but do they have proactive means? The answer is yes. Today, we'll introduce statistical advantages and signal design, which are also the "micro alpha" that market makers pursue.
1, wtf is Market Makers' Alpha?
Micro alpha refers to a "conditional probability shift" in the direction of the next price movement / mid-price drift / asymmetry in executions over extremely short time scales (~100ms to ~10s).
It's important to note that the alpha in the eyes of market makers (MMs) isn't about trend prediction or guessing the magnitude of rises and falls; it just needs a probability shift. This is different from the alpha we commonly talk about.
Next, I'll explain it in plain language:Market makers' statistical advantage can be understood as, within an extremely short time window, whether the order book state "leans toward" making the price move one step in a certain direction first. If MMs successfully calculate the probability of the price direction in the next millisecond through some indicators, they can:
1. Be more willing to buy before a more likely rise. 2. Withdraw buy orders faster before a more likely fall. 3. Reduce exposure during dangerous moments.
The financial foundation for predicting the next price direction is: due to factors like order flow, order volume, and order book cancellation ratios (which we'll discuss later), the market isn't a "random walk" Brownian motion in a short instant but has directionality. The above sentence is the financial translation of the mathematical concept of "conditional probability."With these alphas, market makers can directionally operate on prices, and the "house" finally earns money from price levels rather than just spreads as service fees.
2, Classic Signal Introduction
2.1 Order Book Imbalance: OBI
OBI looks at which side has "more people standing" near the current price level; it's a standardized volume differential statistic.This formula is actually not difficult—it's just a summation of proportional logic. It checks if there are more buy orders or sell orders.
OBI approaching 1 means almost all are bid orders, with thick support below. Approaching -1 means thick resistance above. Approaching 0 means buys and sells are relatively symmetric. It's worth noting that OBI is a "static snapshot," a classic indicator but ineffective on its own; it needs to be used with cancellation ratios, order book slopes, etc.
2.2 Order Flow Imbalance (OFI)
OFI looks at who has been aggressively attacking in the recent short period. OFI is the first-order driver of price changes because prices are driven by taker orders, not by limit orders. It has a bit of a net buy-sell volume feel.
In the Kyle (1985) framework, ΔP ≈ λ ⋅ OFI, where λ is the tick depth, so OFI is the factor that drives prices.
2.3 Queue Dynamics
Most exchanges now use continuous auction rules, following best price and FCFS (first-come, first-served) principles, so submitted orders queue up to be filled. The queue represents the limit order situation, and the queue determines the order book state. Abnormal order book states (including replenishment and cancellation situations) imply directional price changes, which is micro alpha.Queues need attention in two situations:
1, Iceberg: Hidden orders.
For example, only 10 lots are visibly hanging, but every time they're filled, another 10 lots are immediately replenished. The actual true intention might be 1,000 lots. The method I introduced in the first episode for annoying market makers to lower cost basis is actually a manual iceberg. In practice, some players who want to hide real order sizes also use icebergs.
2, Spoof (Fake Orders).
Hanging large orders on one side to create a "pressure illusion," then quickly withdrawing them before the price approaches. Spoofing pollutes OBI and Slope, etc., making the queue falsely thicken and increasing movement risk. At the same time, some large spoofs can scare the market and potentially manipulate prices. The London exchange caught a guy manipulating forex in 2015 who used spoofing. But in the crypto world, we can also manually spoof to annoy market makers, but if it actually gets filled, your exposure becomes huge.
2.4 Order Book Cancellation Ratio (Cancel Ratio)
The cancellation ratio is an estimate of liquidity "disappearance rate": Cancel ↑ ⇒ Slope ↓ ⇒ λ ↑ ⇒ ΔP more sensitive. It's a leading instability signal ahead of OFI. CR → 1: Almost pure cancellations. CR → 0: Almost pure replenishments. The mathematical formulas in this episode are all simple; you can interpret them by looking at charts.
CR ↑ ⟹ The passive side believes future risk is rising. At the same time, CR isn't used alone; it's always combined with OFI and such.
The above might just be some outdated order book games; market making evolves quickly, and after stocks go on-chain, JS and other MMs might all get involved in on-chain market making. But these indicators are still useful and inspiring.
3, Market Makers' Absolute Domain: Speed
We often hear in movies that a certain fund has faster internet, so they're more badass. Including how many market makers move their server rooms closer to exchange servers—why is that? At the end of this article, let's talk about the advantages of physical equipment and the "execution advantage" unique to crypto exchanges.
Latency Arbitrage isn't about predicting future prices but about executing buy/sell orders at more favorable prices "before others react." In theoretical models: Prices are continuous, information is synchronous. But in reality: Markets are event-driven, information arrives asynchronously. Why does information arrive asynchronously? Because receiving exchange price signals and sending order instructions to the exchange both take time—this is a physical world limitation. Even in fully compliant markets: Different exchanges, different data sources, different matching engines, different geographic locations all cause delays. So MMs with more advanced equipment have the initiative.
This tests the market makers' own strength and has little to do with other players, so I think it's their absolute domain.The simplest example: Suppose you want to sell a position, and you quote at the market's best ask price, theoretically it should execute, but I also want to sell. Since I see prices and quote faster than you, I fill the order first, leaving your inventory unable to exit, preventing your position from returning to neutral.
Real situations are much more complex. An interesting point is that, since there's no regulation yet, almost all crypto exchanges can directly give priority execution rights to specified accounts. Meaning, the right to cut in line for certain specified accounts. This is especially common in small exchanges, showing that in crypto, becoming an "insider" is as important as in research. Whether you can safely execute is a key step from alpha theory to practice.
In this episode, I tried writing from the MM perspective; actual operations are definitely more complex, like dynamic queues and many details to watch in practice. Welcome comment.
Postscript: Actually, this article has a regret. The title "Domain Expansion in Market Making" was originally meant for dynamic hedging and options, because I think that's the conceptually hardest part of market making, worthy of the big move "domain expansion." But I worked on it all day yesterday, wrote half the article, and really didn't know how to systematically explain it, so I switched to micro alpha.
Danny has an article that mentions many professional hedging concepts; I encourage everyone to check it out: https://t.co/xwAtz9WXjs.
We'll talk about that section later, perhaps sharing it in fragments.
Thanks for supporting the Advancing MM series, stay tuned.](https://pbs.twimg.com/media/G9I0G8bbgAADMng.jpg)
Olivia
Online
C.mist
@Cigar97ben
Crypto
Joined December 2021
463 Following
48 Followers
367 Posts
◤#MAPPA15th Info 📢◢
／
「MAPPA15周年キービジュアル」 第2弾解禁！！🎉
＼
『「進撃の巨人」The Final Season』の
描き下ろしビジュアル公開！！
✎-————————————————
レイアウト：林 祐一郎 / Layout：Yuichiro Hayashi
イラスト：岸 友洋 / Illustration：Tomohiro Kishi
彩色：大西 慈 / Digital Paint：Iku Onishi
背景：大濵夢奈 / Background Art：Yumena Ohama
撮影：淡輪雄介 / Composite：Yusuke Tannawa
-—————————————————
第3弾をお楽しみに✨
15th情報は「特設Webサイト」をCHECK！✅
https://t.co/JEGIfrZyK0
#shingeki
#MAPPA
＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝
#進撃の巨人 公式LINE「訓練兵団 学科試験」
＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝
5問中5問正解！君も小試験＜第61話＞に挑戦しよう！ https://t.co/9iwqMoY0Ys
Un nerd de 33 años acaba de convertir $1.000 en $946.207 operando Bitcoin, con un truco que robó de los pronósticos de huracanes.
Sin título en finanzas. Sin mesa de trading. Solo un truco que todo meteorólogo aplica y todo trader olvida.
Wallet pública:
https://t.co/J65WvxHpdC
El truco: los meteorólogos nunca pronostican el mañana con un solo modelo. Corren 31 y cuentan los votos. Él apuntó exactamente ese mismo truco hacia Bitcoin.
Un agente de Claude lee cada mercado de BTC de 5 minutos y lo mete en MiroFish, una simulación que corre 31 rutas de modelo y solo dispara cuando 28 de ellas coinciden. Por debajo de 26 votos, mata la operación.
La velocidad de cobertura del sistema de agentes es muchísimo mayor que la de cualquier equipo de trading de élite.
Recopilan datos 24/7 y corren simulaciones con esos datos en el motor de MiroFish, de forma completamente autónoma.
Cada operación es un ciclo perfecto. Cada dólar ganado es pura explotación de la ineficiencia del mercado.
Esa es toda la ventaja. No una predicción. Un quórum.
Dimensiona con Kelly y aprieta un botón. La mayoría de las señales nunca pasan la votación, así que la mayoría de los días se queda quieto.
Pasó años aprendiendo que la certeza es una estafa y el consenso es la ventaja.
Most traders use Volume Profile wrong.
They mark POC, HVN and LVN but never understand how price actually reacts around them.
Once you understand acceptance vs rejection, entries become much easier.
Here’s how I use it 👇 a Thread 🧵 Like, comment and Repost for more.
刚才读到了一篇非常棒的文章，关于旅行的意义:
旅行如果只是拍照、打卡、买纪念品，本质上只是换个地方娱乐。真正改变一个人的旅行，来自参与、观察和反思。
很多人旅行前都很兴奋，觉得这趟旅程可能会改变人生。到了目的地，拍照、吃饭、逛景点，回来以后给朋友讲讲经历，发发照片，送送纪念品。过一段时间，那种兴奋感就消失了，旅行慢慢变成一场昂贵的梦，像看了一部电影，只是价格更贵一点。
文章说，其实旅行不一定要这样。
真正有价值的旅行，不只是“看见了什么”，而是你在这个过程中有没有参与进去，有没有观察当地人的生活，有没有问为什么，有没有发现自己原来的想法其实很狭窄。
作者举了一个例子：200多年前，英国思想家玛丽·沃斯通克拉夫特经历了一段人生低谷。她感情受挫，生活困难，于是去了斯堪的纳维亚。她原本是为了处理一些现实问题，结果事情并没有成功，可她把这趟旅行写成了书，也在这个过程中慢慢修复了自己。
她旅行的时候，不只是看风景。她会观察当地人的农业、咖啡习惯、服装、园艺、社会等级，然后不断拿这些东西和英国对比。她发现，自己国家的很多制度和习惯，并不是天经地义的。世界上还有别的生活方式，别的秩序，别的幸福。
这就是旅行最珍贵的地方。
旅行会扩大你的样本。一个人长期生活在同一个城市、同一个圈子、同一种文化里，很容易以为自己看到的世界就是整个世界。旅行让你知道，原来人类有很多种生活方式。有人追求效率，有人追求松弛；有人重视财富，有人重视关系；有人觉得幸福是成功，有人觉得幸福是安静。
旅行也能打破确认偏误。你在熟悉的环境里，身边的人常常强化你的旧观念。到了陌生地方，你会遇到完全不同的想法，不同的价值观，不同的生活节奏。它会提醒你：你现在的人生，不是唯一选项。
文章最后给了几个很实用的建议：
旅行时写点日记，不需要很复杂，等车、休息、睡前随手记几句就可以。
不要把行程安排得太满，留一点空间给意外。很多最有价值的体验，往往不是计划出来的。
带着一个目标去旅行，不要只是复制自己在家里的生活。不要到了国外还只吃熟悉的餐厅，看熟悉的节目，活成原来的样子。
保持开放。旅行真正的意义，是让你有机会成为一个稍微不一样的人。
用最简单的话说：
旅游是看世界，旅行是让世界反过来看你。
你看见陌生的地方，也看见熟悉的自己。你理解别人怎么生活，也开始重新理解自己为什么这样生活。真正好的旅行，不只是让你休息几天，而是让你醒过来。
*原作者是FS
When you truly understand this 100% your key levels in the trending market become sharper and your win rate improves.
P-Shape. b-Shape.
Not just patterns they reveal who is in control of the market.
🔹 P-Shaped Profile
Shorts are trapped. Price squeezes higher.
Smart traders look for continuation and build levels around value acceptance.
🔹 b-Shaped Profile
Buyers are exiting. Weak hands get flushed out.
Key levels form where distribution shifts often leading to downside continuation or reversal setups.
Understand the story behind the volume and your levels stop being guesses they become precision.
Which profile is not in the picture? 👇
https://t.co/VKwrqiLcyp
https://t.co/AcdrphkXda
人生只有4000周，你却总在痛苦焦虑？
过年看完了Naval（纳瓦尔）的三小时访谈。
他说，人生其实只有4000周。
我被这个数字惊到了。全球平均寿命73岁，约3800周；掐指一算，如果我能活到78岁，刚好4050周。
4000周。
如果你已经30岁，那还剩2000多周；40岁，还剩1500周。每一周过去，就少一格。
可我们是怎么度过这些周的？焦虑、内耗、比较、等待——等有时间了，等有钱了，等孩子大了，等退休了……
等来的却是更多的焦虑。
人生不是一条线，是一场可选择的游戏
Naval有个比喻：人生不是一条从A到B的线，而是一场游戏。并且，它是可以被选择、被设计、被退出的。
大多数人痛苦，不是因为失败，而是因为在不知道规则的情况下，一遍又一遍重复同一个关卡。
这场游戏的最终奖励是什么？
Naval说：是自由。
赢得游戏的好处是，你可以随时退出。
第一关：你要不要参加主流游戏？
其实，人生这场游戏并不是强制参与的。
你可以选择不追逐、不比较、不竞争。降低欲望，保持平静。看到别人成功、焦虑、内卷，你依然内心稳定——如果能做到这样，你已经赢了。
但大多数人做不到。我们还是会选择进入主流游戏，因为钱确实能帮我们得到很多想要的东西。
如果你选择参加，那就面临第二个选择：玩哪一种游戏？
两种游戏：地位 vs 财富
主流世界里只有两种核心游戏。
第一种：地位游戏。
本质是零和博弈——总量有限，你高我就低，你赢我就输。就像一个梯子，有人上去就有人下来。职场里的晋升、朋友圈的攀比、同学会的较劲，都是地位游戏。
为什么我们这么在意排名？因为刻在基因里。远古部落里，资源有限，地位高的人更容易活下来、找到配偶。所以我们对地位特别敏感，这是底层程序。
第二种：财富游戏。
本质是正和博弈——通过创造价值把蛋糕做大，不需要别人输，你也可以赢。
你开一家小店，用心服务顾客，顾客满意，你赚钱，这是财富游戏。你写一篇文章，帮读者解惑，读者受益，你收获认可，这也是财富游戏。
财富游戏不需要踩别人，只需要创造。
Naval选择的就是财富游戏。因为这才是能持续获胜的游戏。
通关法则一：做你自己
如果你选择财富游戏，怎么通关？
公式很简单：你热爱的 × 你擅长的 × 市场需要的 = 不可替代的你。
很多人说不知道自己喜欢什么。Naval给了一个方法：别坐着想，去找——那些对你来说像玩一样、对别人来说像工作一样的事。
我有个朋友就特别喜欢到处玩，对她来说就是极富生命力，又不费劲的事。后来，她成了旅行博主。也创立了自己的户外品牌。
这就是把自己产品化。本质是逃离竞争——在做你自己这件事上，没有人比你更有竞争力。说白了，就是成为无法被复制的人。
通关法则二：决策算法
人生充满选择，怎么决定？
Naval给了一套清晰的算法：
第一，如果你犹豫一件事要不要做，先问自己：有非它不可的理由吗？
比如留学。表面光鲜，实际要考雅思、写申请、适应陌生环境、面对文化冲击。如果你不是特别想去，只是有点心动，那答案就是“不”。因为真正适合你的选择，通常是你会立刻想去做的那一个。
我见过一个邻居，纠结了三年要不要辞职开咖啡店，到现在还在纠结。而另一个朋友，想清楚后三个月就把店开起来了。前者在犹豫中消耗，后者在行动中迭代。
第二，如果两个选项看起来差不多，怎么选？
答案是：选短期痛苦的。
为什么？因为大脑不是为成功设计的，而是为生存设计的。它天然逃避眼前的痛苦，却几乎不计算长期平庸、后悔、停滞的代价。
大脑会骗你，别上当。选短期痛苦，长期有发展的路。
通关法则三：迭代大于重复
一万次重复，不如一万次迭代。
很多人以为努力就是重复做同一件事。但如果你只是简单重复，没有改进，那就是原地踏步。
真正的成长是：做事、犯错、修正、再做一遍。失败不是问题，不修正才是。
比如写作，第一篇写得不好，第二篇改进开头，第三篇优化结构……十篇之后，水平自然提升。如果每次只是复制粘贴，写一百篇也没用。
失败是迭代的必经之路。螺旋上升，才能达到精通。
终极奖励：自由
我们努力赚钱、提升自己，到底为了什么？
Naval说得很清楚：不是为了名声，不是为了更多欲望，而是为了自由——空间自由、社交自由、时间自由。
说白了，就是不用被迫去你不想去的地方，不用被迫见你不想见的人，可以按自己的意愿安排时间。
解决了钱的问题，就不用再想钱的事。解决了身份焦虑，就不用再比来比去。这才是真正的奖励。
最后的装备：从零开始的勇气
有个读者说：“我想做自己喜欢的事，但怕别人笑话。”
其实你坚持一个月就会发现：根本没人在看你。大家都很忙，忙着过自己的日子。
Naval反复提到一种能力：从零开始的勇气（resilience）。
你看那些真正厉害的人，比如马斯克，他们共同点不是“我一定会赢”，而是“我跌倒了还能再站起来”。工厂可以推倒，项目可以归零，身份可以重置。
因为他们真正确信的，不是永不失败，而是：失败不会抹掉我继续游戏的资格。
这种人的内心是自由的。他们不怕失败，不是因为失败不痛，而是知道即使输了，还可以再开一局。
人生真正的底气，不是你现在拥有什么，而是你是否拥有从零再来一次的能力。当你拥有这种能力，地位、金钱、评价都只是游戏里的变量。你会更敢选那条想走的路，更敢活得更完整。
4000周的沙漏一直在流。既然终点如此确定，就别再等待。
最昂贵的，是因为害怕而浪费的时间。注意力才是你真正拥有的财产。
去玩那个——即使失败了你也觉得值得的人生游戏。
毕竟，我们只有这一生。
https://t.co/V75wCdCqQ2
https://t.co/7ilvn4mz8i
https://t.co/S96SSn17Hr
这是桥水创始人达利欧最受欢迎的投资课（建议收藏）
为什么桥水基金可以做到稳定年化收益15%
无数基金经理/投资机构花费半生去研究理解市场，
而达利欧把 75 年的投资智慧，浓缩成了 42 分钟。
建议大家把这段视频收藏起来，反复观看！
卧槽，这篇《How to Simulate Like a Quant Desk》太牛逼了，
所有观点都经过了作者交易实践观察+行为心理学认知偏误实证的，
讲的是一套从散户入门到机构级的预测市场量化模拟完整体系，
作者gemchanger以“硬币翻转的散户认知误区”为起点，
以蒙特卡洛方法为核心根基，
逐层拆解了从基础概率估算到生产级交易系统的全链路技术、可运行代码与理论支撑，
彻底解决了散户在预测市场交易中概率估算失准、尾部风险失控、无法动态适配新信息、忽略极端联动性等核心痛点，
每一层内容环环相扣，最终形成一套可直接落地的量化交易模拟全栈，
具体提炼总结在评论区👇
https://t.co/Pv1goXYlCA
Responsive Activity and Initative Activity🧵
A practical perspective to read orderflow is to watch the behaviour of participants at the edges of value (the extremes).
Behaviour of these participants usually what defines acceptance and failed auctions.
i've learned many lessons this year but one easily stands above the rest. one i feel like was under my nose my for a long time
the greatest indicator i've seen for figuring out if you're doing the right thing in trading (or anything else for that matter) has been not doing what everyone else is doing
if you want to be exceptional (and you have to be to generate consistent returns) you cannot be doing what everyone else is doing. they are an antithesis to one another
when i reflect on some of the best traders i've encountered on CT, they have all had certain first principles in common but were ultimately very unique in their personal approach to the markets. all of them were 'the best' in their own category. and almost all of them arrived to that position through a journey entirely constructed on their own
in 2021-2023 i made most of my returns scalping altcoin perps using naked tick charts. for me, they painted a picture of microstructure that i had not been able to find any other way. before finding this edge for myself, i did not see a single trader using this approach. i was called retarded and a gambler for much of this time - which definitely created self-doubt. but looking back, its clear that part of my success came from the decision to do something different
for the last few weeks, i've been trading crypto up/down markets on polymarket using a DOM interface. an edge i found on my own in an attempt to take advantage of a growing set of traders vibe coding highly inefficient bots you see all over the timeline
i find my self in a similar position as last time. again, it probably sounds stupid and impractical at the surface level. and also again, i haven't seen anyone do anything similar
is the edge large and persistent enough for massive returns? who knows. but the point is the journey of finding something that works for yourself. entirely on your own
replicating what you already see will almost never work. you need your own secret sauce
merry xmas
i wish you all success in your own journeys in the new year
《彼得·蒂尔：如何从零开始打造垄断型企业》
2014年，彼得·蒂尔举办了一场时长1小时的大师班，讲解如何从零开始打造。
他详细分析了以下几个成功案例：
• 谷歌如何成为不可撼动的巨头；
• PayPal如何逆势而上；
• Facebook如何碾压竞争对手。
以下是他大师班中总结出的11条永恒真理：
1. 创造价值，然后攫取价值
一家有价值的企业必须：
• 创造 X 美元的价值
• 获取其中 Y% 的价值。
大多数人认为 X 和 Y 是相关的，但事实并非如此。你可以创造巨大的价值，却几乎一无所获；
你也可以创造适度的价值，却获取其中的大部分。垄断企业在这两方面都表现出色。
2. 利润比规模更重要。
航空公司创造的收入比谷歌多，但美国航空公司一百多年来的累计利润几乎为零。
谷歌则赚得盆满钵满。价值并非由规模决定，而是由利润和生命周期决定。
3. 完全竞争会扼杀价值。
完全竞争在教科书中看起来很高效，但在现实中却会：
• 没有差异化
• 没有定价权
• 没有利润。
如果你和其他人为了同样的理由而竞争，你就不是在创造价值，而只是在竞争。
4. 只有两种类型的企业
根据蒂尔的说法：
• 完全竞争型企业
• 垄断
几乎没有介于两者之间的任何状态。
稳定且盈利的公司都是垄断企业。
那些苦苦挣扎、利润微薄的企业也很有竞争力。
这是商业中的基本二元对立。
5. 人们会谎称市场竞争激烈。
非垄断者为了吸引投资，会假装自己的市场特殊且规模小；而垄断者为了规避监管，则会假装自己身处竞争激烈的庞大市场。
这种叙事上的差异或许细微，但经济上的差异却巨大。
6. 小市场是强大的立足点
先从一个你可以主导的小市场开始。
然后以同心圆的方式向外扩展：
• 亚马逊→最初以图书起家。
• eBay →最初是卖收藏品的
• Facebook →起源于哈佛大学
• PayPal →专注于eBay超级卖家
成功的公司并非从规模庞大的市场起步。
它们起步规模小，但有发展潜力。
7. 突破并非渐进式的
要实现垄断，你需要：
→比替代方案改进10倍
PayPal 处理付款的速度比支票快 10 倍。
亚马逊提供的商品种类是实体书店的10倍。
渐进式改进很少能取得成功。
量子飞跃才行.
8. 垄断特征堆叠
强大的企业总是在四个方面很牛：
• 专有技术
• 网络效应
• 规模经济
• 品牌推广
一个人就能解决问题。
你不再是竞争对手，而是统治者。
9. “后发者”比“先发者”更重要
先行者会获得关注。
最后行动的人才能赚到真正的钱。
微软并非第一个操作系统；它只是成为了行业标准。
谷歌并非第一个搜索引擎；它只是成为了市场主导者。
Facebook 不是第一个社交网络；它只是成为了主要的社交网络。
价值存在于未来，而非过去。
10. 你的大部分价值都体现在未来几十年。
Thiel 对早期的 PayPal 进行了 DCF 分析。
• 公司约 75% 的价值来自未来 10 年以上的预期。
如今的增长看起来是实实在在的。
未来的耐用性决定价值。
未来是创造财富的地方。
11. 竞争挤占了有意义的工作
竞争教会你模仿。
但模仿并不能带来价值获取。
蒂尔认为：
当每个人都做同样的事情时，没有人是赢家。
在生物学、体育和商业领域：
竞争奖励的是竞争技巧，而不是原创价值创造。
失败者进行比赛。
成功者创造。
最终结论：垄断并非邪恶。
垄断的经济战略：
• 创造实际价值
• 取得优势
• 持续存在
蒂尔的观点不仅仅是“垄断是好事”。
竞争会吞噬你的利润、精力和个性。
而那些最终胜出的公司，并非更擅长竞争。
他们更擅长与众不同。
[Attack on MM 3: Statistical Advantages and Signal Design ]
The previous two episodes mentioned order flow and inventory quotes, which sound like market makers can only passively adjust, but do they have proactive means? The answer is yes. Today, we'll introduce statistical advantages and signal design, which are also the "micro alpha" that market makers pursue.
1, wtf is Market Makers' Alpha?
Micro alpha refers to a "conditional probability shift" in the direction of the next price movement / mid-price drift / asymmetry in executions over extremely short time scales (~100ms to ~10s).
It's important to note that the alpha in the eyes of market makers (MMs) isn't about trend prediction or guessing the magnitude of rises and falls; it just needs a probability shift. This is different from the alpha we commonly talk about.
Next, I'll explain it in plain language:Market makers' statistical advantage can be understood as, within an extremely short time window, whether the order book state "leans toward" making the price move one step in a certain direction first. If MMs successfully calculate the probability of the price direction in the next millisecond through some indicators, they can:
1. Be more willing to buy before a more likely rise. 2. Withdraw buy orders faster before a more likely fall. 3. Reduce exposure during dangerous moments.
The financial foundation for predicting the next price direction is: due to factors like order flow, order volume, and order book cancellation ratios (which we'll discuss later), the market isn't a "random walk" Brownian motion in a short instant but has directionality. The above sentence is the financial translation of the mathematical concept of "conditional probability."With these alphas, market makers can directionally operate on prices, and the "house" finally earns money from price levels rather than just spreads as service fees.
2, Classic Signal Introduction
2.1 Order Book Imbalance: OBI
OBI looks at which side has "more people standing" near the current price level; it's a standardized volume differential statistic.This formula is actually not difficult—it's just a summation of proportional logic. It checks if there are more buy orders or sell orders.
OBI approaching 1 means almost all are bid orders, with thick support below. Approaching -1 means thick resistance above. Approaching 0 means buys and sells are relatively symmetric. It's worth noting that OBI is a "static snapshot," a classic indicator but ineffective on its own; it needs to be used with cancellation ratios, order book slopes, etc.
2.2 Order Flow Imbalance (OFI)
OFI looks at who has been aggressively attacking in the recent short period. OFI is the first-order driver of price changes because prices are driven by taker orders, not by limit orders. It has a bit of a net buy-sell volume feel.
In the Kyle (1985) framework, ΔP ≈ λ ⋅ OFI, where λ is the tick depth, so OFI is the factor that drives prices.
2.3 Queue Dynamics
Most exchanges now use continuous auction rules, following best price and FCFS (first-come, first-served) principles, so submitted orders queue up to be filled. The queue represents the limit order situation, and the queue determines the order book state. Abnormal order book states (including replenishment and cancellation situations) imply directional price changes, which is micro alpha.Queues need attention in two situations:
1, Iceberg: Hidden orders.
For example, only 10 lots are visibly hanging, but every time they're filled, another 10 lots are immediately replenished. The actual true intention might be 1,000 lots. The method I introduced in the first episode for annoying market makers to lower cost basis is actually a manual iceberg. In practice, some players who want to hide real order sizes also use icebergs.
2, Spoof (Fake Orders).
Hanging large orders on one side to create a "pressure illusion," then quickly withdrawing them before the price approaches. Spoofing pollutes OBI and Slope, etc., making the queue falsely thicken and increasing movement risk. At the same time, some large spoofs can scare the market and potentially manipulate prices. The London exchange caught a guy manipulating forex in 2015 who used spoofing. But in the crypto world, we can also manually spoof to annoy market makers, but if it actually gets filled, your exposure becomes huge.
2.4 Order Book Cancellation Ratio (Cancel Ratio)
The cancellation ratio is an estimate of liquidity "disappearance rate": Cancel ↑ ⇒ Slope ↓ ⇒ λ ↑ ⇒ ΔP more sensitive. It's a leading instability signal ahead of OFI. CR → 1: Almost pure cancellations. CR → 0: Almost pure replenishments. The mathematical formulas in this episode are all simple; you can interpret them by looking at charts.
CR ↑ ⟹ The passive side believes future risk is rising. At the same time, CR isn't used alone; it's always combined with OFI and such.
The above might just be some outdated order book games; market making evolves quickly, and after stocks go on-chain, JS and other MMs might all get involved in on-chain market making. But these indicators are still useful and inspiring.
3, Market Makers' Absolute Domain: Speed
We often hear in movies that a certain fund has faster internet, so they're more badass. Including how many market makers move their server rooms closer to exchange servers—why is that? At the end of this article, let's talk about the advantages of physical equipment and the "execution advantage" unique to crypto exchanges.
Latency Arbitrage isn't about predicting future prices but about executing buy/sell orders at more favorable prices "before others react." In theoretical models: Prices are continuous, information is synchronous. But in reality: Markets are event-driven, information arrives asynchronously. Why does information arrive asynchronously? Because receiving exchange price signals and sending order instructions to the exchange both take time—this is a physical world limitation. Even in fully compliant markets: Different exchanges, different data sources, different matching engines, different geographic locations all cause delays. So MMs with more advanced equipment have the initiative.
This tests the market makers' own strength and has little to do with other players, so I think it's their absolute domain.The simplest example: Suppose you want to sell a position, and you quote at the market's best ask price, theoretically it should execute, but I also want to sell. Since I see prices and quote faster than you, I fill the order first, leaving your inventory unable to exit, preventing your position from returning to neutral.
Real situations are much more complex. An interesting point is that, since there's no regulation yet, almost all crypto exchanges can directly give priority execution rights to specified accounts. Meaning, the right to cut in line for certain specified accounts. This is especially common in small exchanges, showing that in crypto, becoming an "insider" is as important as in research. Whether you can safely execute is a key step from alpha theory to practice.
In this episode, I tried writing from the MM perspective; actual operations are definitely more complex, like dynamic queues and many details to watch in practice. Welcome comment.
Postscript: Actually, this article has a regret. The title "Domain Expansion in Market Making" was originally meant for dynamic hedging and options, because I think that's the conceptually hardest part of market making, worthy of the big move "domain expansion." But I worked on it all day yesterday, wrote half the article, and really didn't know how to systematically explain it, so I switched to micro alpha.
Danny has an article that mentions many professional hedging concepts; I encourage everyone to check it out: https://t.co/xwAtz9WXjs.
We'll talk about that section later, perhaps sharing it in fragments.
Thanks for supporting the Advancing MM series, stay tuned.
![bc1qDave's tweet photo. [Attack on MM 3: Statistical Advantages and Signal Design ]
The previous two episodes mentioned order flow and inventory quotes, which sound like market makers can only passively adjust, but do they have proactive means? The answer is yes. Today, we'll introduce statistical advantages and signal design, which are also the "micro alpha" that market makers pursue.
1, wtf is Market Makers' Alpha?
Micro alpha refers to a "conditional probability shift" in the direction of the next price movement / mid-price drift / asymmetry in executions over extremely short time scales (~100ms to ~10s).
It's important to note that the alpha in the eyes of market makers (MMs) isn't about trend prediction or guessing the magnitude of rises and falls; it just needs a probability shift. This is different from the alpha we commonly talk about.
Next, I'll explain it in plain language:Market makers' statistical advantage can be understood as, within an extremely short time window, whether the order book state "leans toward" making the price move one step in a certain direction first. If MMs successfully calculate the probability of the price direction in the next millisecond through some indicators, they can:
1. Be more willing to buy before a more likely rise. 2. Withdraw buy orders faster before a more likely fall. 3. Reduce exposure during dangerous moments.
The financial foundation for predicting the next price direction is: due to factors like order flow, order volume, and order book cancellation ratios (which we'll discuss later), the market isn't a "random walk" Brownian motion in a short instant but has directionality. The above sentence is the financial translation of the mathematical concept of "conditional probability."With these alphas, market makers can directionally operate on prices, and the "house" finally earns money from price levels rather than just spreads as service fees.
2, Classic Signal Introduction
2.1 Order Book Imbalance: OBI
OBI looks at which side has "more people standing" near the current price level; it's a standardized volume differential statistic.This formula is actually not difficult—it's just a summation of proportional logic. It checks if there are more buy orders or sell orders.
OBI approaching 1 means almost all are bid orders, with thick support below. Approaching -1 means thick resistance above. Approaching 0 means buys and sells are relatively symmetric. It's worth noting that OBI is a "static snapshot," a classic indicator but ineffective on its own; it needs to be used with cancellation ratios, order book slopes, etc.
2.2 Order Flow Imbalance (OFI)
OFI looks at who has been aggressively attacking in the recent short period. OFI is the first-order driver of price changes because prices are driven by taker orders, not by limit orders. It has a bit of a net buy-sell volume feel.
In the Kyle (1985) framework, ΔP ≈ λ ⋅ OFI, where λ is the tick depth, so OFI is the factor that drives prices.
2.3 Queue Dynamics
Most exchanges now use continuous auction rules, following best price and FCFS (first-come, first-served) principles, so submitted orders queue up to be filled. The queue represents the limit order situation, and the queue determines the order book state. Abnormal order book states (including replenishment and cancellation situations) imply directional price changes, which is micro alpha.Queues need attention in two situations:
1, Iceberg: Hidden orders.
For example, only 10 lots are visibly hanging, but every time they're filled, another 10 lots are immediately replenished. The actual true intention might be 1,000 lots. The method I introduced in the first episode for annoying market makers to lower cost basis is actually a manual iceberg. In practice, some players who want to hide real order sizes also use icebergs.
2, Spoof (Fake Orders).
Hanging large orders on one side to create a "pressure illusion," then quickly withdrawing them before the price approaches. Spoofing pollutes OBI and Slope, etc., making the queue falsely thicken and increasing movement risk. At the same time, some large spoofs can scare the market and potentially manipulate prices. The London exchange caught a guy manipulating forex in 2015 who used spoofing. But in the crypto world, we can also manually spoof to annoy market makers, but if it actually gets filled, your exposure becomes huge.
2.4 Order Book Cancellation Ratio (Cancel Ratio)
The cancellation ratio is an estimate of liquidity "disappearance rate": Cancel ↑ ⇒ Slope ↓ ⇒ λ ↑ ⇒ ΔP more sensitive. It's a leading instability signal ahead of OFI. CR → 1: Almost pure cancellations. CR → 0: Almost pure replenishments. The mathematical formulas in this episode are all simple; you can interpret them by looking at charts.
CR ↑ ⟹ The passive side believes future risk is rising. At the same time, CR isn't used alone; it's always combined with OFI and such.
The above might just be some outdated order book games; market making evolves quickly, and after stocks go on-chain, JS and other MMs might all get involved in on-chain market making. But these indicators are still useful and inspiring.
3, Market Makers' Absolute Domain: Speed
We often hear in movies that a certain fund has faster internet, so they're more badass. Including how many market makers move their server rooms closer to exchange servers—why is that? At the end of this article, let's talk about the advantages of physical equipment and the "execution advantage" unique to crypto exchanges.
Latency Arbitrage isn't about predicting future prices but about executing buy/sell orders at more favorable prices "before others react." In theoretical models: Prices are continuous, information is synchronous. But in reality: Markets are event-driven, information arrives asynchronously. Why does information arrive asynchronously? Because receiving exchange price signals and sending order instructions to the exchange both take time—this is a physical world limitation. Even in fully compliant markets: Different exchanges, different data sources, different matching engines, different geographic locations all cause delays. So MMs with more advanced equipment have the initiative.
This tests the market makers' own strength and has little to do with other players, so I think it's their absolute domain.The simplest example: Suppose you want to sell a position, and you quote at the market's best ask price, theoretically it should execute, but I also want to sell. Since I see prices and quote faster than you, I fill the order first, leaving your inventory unable to exit, preventing your position from returning to neutral.
Real situations are much more complex. An interesting point is that, since there's no regulation yet, almost all crypto exchanges can directly give priority execution rights to specified accounts. Meaning, the right to cut in line for certain specified accounts. This is especially common in small exchanges, showing that in crypto, becoming an "insider" is as important as in research. Whether you can safely execute is a key step from alpha theory to practice.
In this episode, I tried writing from the MM perspective; actual operations are definitely more complex, like dynamic queues and many details to watch in practice. Welcome comment.
Postscript: Actually, this article has a regret. The title "Domain Expansion in Market Making" was originally meant for dynamic hedging and options, because I think that's the conceptually hardest part of market making, worthy of the big move "domain expansion." But I worked on it all day yesterday, wrote half the article, and really didn't know how to systematically explain it, so I switched to micro alpha.
Danny has an article that mentions many professional hedging concepts; I encourage everyone to check it out: https://t.co/xwAtz9WXjs.
We'll talk about that section later, perhaps sharing it in fragments.
Thanks for supporting the Advancing MM series, stay tuned.](https://pbs.twimg.com/media/G9I0YdkbgAIuYdh.png)
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