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【Hardcore】SAMM(Smart Automated Market Maker)

Intro

Smart Automated Market Maker (SAMM) could be used to provide on-chain liquidity to a simplified binary-outcome parimutuel market.

Pain points

In the case of UNISWAP, the AMM applying a constant pricing function on the 2 supplied liquidity pools and price based on the size required.

Which is purely based on the pricing function and the on-chain liquidity pools without any actual pricing context on the pair from any other external source.

AMM showing equal pools for both outcomes, so 2 to 1 odds 【why??】 before fees or odds which are inline with the current pool sizes for each outcome.

An informed speculator might harm the LPs. This will result in LPs incurring negative expected value per event to which the protocol could then respond by raising fees to ensure that LPs eventually recover their capital.

(赔率低，手续费比例高，因为中间人抽的x=赚的钱*%，赔率低，x就少了)

i.e. an accurate indication of the events probabilities.

Pari mutuels

Liquidity in a parimutuel market is largely driven by the speculators. While the main problem is it requires liquidity, which is resolevd by market makers

Solution(Lower fee+ more speculator+liquidity)

Decentralised parimutuel market (Like uniswap)

UNISWAP requires large liquidity pools in order to provide low slippage. So the protocol offers them high fees relative to centralised exchanges as well as initial rewards in order to make LP capital sticky.

Creating an AMM with probability-guided liquidity, a Smart Automated Market Maker (SAMM), would result in neutral to positive expected value per event for LPs. This then allows the overall fee to be reduced to further encourage new speculator activity which creates a positive liquidity feedback loop.

So who is the external context?

A SAMM with external context would have an additional stakeholder over the UNISWAP protocol, a Probability Provider (PP)???? How

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PP’s are projecting unknown events

The PPs would be incentivized by earning a portion of the fees on the pool based on their rolling success rate.

PP’s would be encouraged to join as they are not carrying any capital risk, apart from oracle staking if required.

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从蓝色突出显示的单元格中可以看出，PP表明结果1的概率是40%，结果2的概率是60%。

SAMM消耗了这些信息，并按这些比例播种了LP资本，分别为4000和6000个单位。这可以在Pools-LP投注行中看到。进一步假设投机者的观点不同，相对于SAMM而言，他们的投注比例较小。

这在Pools-Traders一行中可以看到，他们对任何一个结果都投注500和500。我们将留给读者去研究其余的细节，但假设有3%的房费，LP最后会有一个小的正EV。投机者的EV值为负值，而且还得支付房费。这些费用是对所有其他利益相关者的激励，使他们为SAMM和分散的准绳的最佳利益而行动。

Incentive Structure

LPs

PPs

GTs

Fees need to be appropriately apportioned between these 3 stakeholders in a manner that ensures equilibrium of the system.

Gts will recalibrate the rate for a particular parimutuel

LP pool sizing(They need money)

The SAMM will need to seed the pools with a reasonable size such that it minimises the risk

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Why Solana?

In order for all stakeholders to be able to participate in very short termed parimutuel events e.g. minutely events.

Risks and mitigation

Why does Uniswap never use external context?

It is via an oracle service which can be subject to manipulation.(fake)

Click the link below to check out more issues & solutions

Example:

An individual PP could submit an inaccurate probability to fool the SAMM into seeding liquidity in line with these incorrect odds.

A group of high tier PPs which are already earning rewards could collude to fool the AMM into adding liquidity at the wrong odds.

Bibliography:

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https://docs.hxro.network/samm-protocol⁠

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https://news.futunn.com/post/9253014?level=1&data_ticket=1643905654973649⁠

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负数期望值

你已经知道了70%是红球，并且已经选择了胜率高的红球。

这时，你的对手选了黑球。但他提了一个条件：

假如你赢了，他赔你20%；

假如他赢了，你赔他80%。

你要不要和他对赌呢？

用图形来表示，如下，是二维的矩形：

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如上，纵坐标是胜率，横坐标是赔率。（以下略去%）

你若获胜，收益是70✖️20，如上图的橙色面积；

你若失败，损失是30✖️80，如上图的蓝色面积；

期望值=预期收益➖预期损失=-1000，如上图的两个面积差。

所以，对方给出的赔率，会让你即使拥有70%的胜率，期望值也是负数，也不值得参与这个赌局。

反过来想，对手即使胜率较低，如果有好的赔率，还是可以有正的期望值。

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