Understanding the crypto "metagame": the core drivers of market narrative and behavior change

原文作者:MIDAS CAPITAL

原文来源：Substack

原文标题：Understanding the Meta-game.

编译：TechFlow，深潮

The concept of meta-game is one of the more esoteric concepts in the crypto space, and it has neither a specific definition nor a fixed structure. It's the kind of thing that "whoever understands understands." However, once you see it, it's hard to turn a blind eye. In today's article, I'm going to try to unravel my thoughts on it, hoping that readers will have a clearer idea of the metagame and how to think about it.

Before we get started, it's important to point out that the concept of metagames was popularized by Cobie in his article. Well-known traders like Light Crypto and CMS Holdings' Dan have also mentioned the concept in various podcasts. The idea is nothing new, but I hope to provide some new insights and build a structure around it.

The best way to understand metagames is through game theory, a branch of behavioral economics. It involves understanding the rules of the game, your opponent's optimal response function, and your optimal response function with all other information at your fingertips. We'll use intuition and look at data to analyze these games and understand how to play each game with the best strategy.

It's important to understand that every metagame is different. There are similarities between them, but none of them are exactly the same. Therefore, it is important to have an overarching framework and develop a strategy based on it. That's what we're going to explore today.

What is a metagame?

I'm not going to define a metagame. It is more useful to explain how its mechanism works and the framework within which we understand it. Metagames have several components, which can be summarized as follows:

1. Basic mechanics
2. Behavioral changes
3. Best response function
4. Reflection cycle

The base mechanics can be thought of as the foundation of the metagame, which can be broken down as follows:

1. The catalyst, often (but not exclusively) is the price movement – this inspires a narrative in which the price moves with the narrative. The cause of the price movement can often be traced back to protocol upgrades, KPIs, or other events/metrics.
2. The essence of the catalyst is the underlying mechanism, which underpins a reflex cycle.

Behavioural change is how market participants express their views on catalysts

The optimal response function is how you as a trader should respond to the catalyst, how the catalyst is perceived by other market participants, and how they will respond to the catalyst. The optimal response function involves considering the position size, entry and exit.

Reflex cycles can be categorized as follows:

• Market participants identify the underlying mechanics → play the game → prices behave in a way that conforms to the rules of the game → rules become more and more obvious → more participants identify the underlying mechanics → more players enter the game → and so on.

The above four components provide a high-level overview of how metagames evolve, evolve, and dissipate.

Theoretical framework

Below is a flowchart detailing how to start by identifying the metagame, to understanding it, and then hoping to extract value from it. Let's work in more detail. Let's start with some theories, and then we'll look at some examples and data.

Step 1: Identify potential metagames, observe/look for the following:

• Developing narratives, sentiment analysis, abnormal price behavior.
• Position yourself as a protocol or department that solves known issues.
• A binary event that is widely known and understood.

Step 2: Identify the underlying mechanism

• Given the catalyst and how it is perceived, how does it drive change in the behavior of market participants?
• There are two types of underlying mechanisms, self-enhancement and self-defeating
• Self-Enhancement: An ongoing base mechanic where the catalyst is continuous, so the metagame will be around for a while. For example, BTC ETF inflows/outflows – given that the data is released daily, this can be seen as a repetitive interactive game.
• Self-defeating: A foundational mechanic that drives a behavior, causing the metagame to quickly dissipate. For example, Facebook changed its name to META – this is a one-time event that can be considered a single interactive game.

Step 3: Assumptions about the duration of the metagame

• The nuances of the underlying mechanics determine the duration of the game, as well as the entry and exit strategies.
• In general, self-reinforcing metagames lead to the creation of sub-metagames, while self-defeating metagames disappear as quickly as they appear.

Step 4: Quantify the persistence of the underlying mechanism

• Assumptions need to be made about whether the game is self-reinforcing or self-defeating, and then find the data that materializes or neutralizes those assumptions
• For example, if we're playing a meme metagame, it's good to look at relative volume (as a proxy for attention).
• For example, if we're playing the BTC ETF metagame, it's helpful to look at ETF money inflows/outflows, sources, and how prices respond to these data points.
• This is largely an intuition dictated by data issues.

Step 5: Use quantifiable metrics and general market strength to guide exits.

• There is no specific or repeatable exit strategy.
• The timing of the exit is different for every metagame, and in general, intuition is key.
• It's helpful to look at the data, market capitalization, relative trading volume, and more – but at the end of the day, it's a discretionary choice.

Metagame example

Let's take a look at some current and past metagame examples, along with the associated logic and data. In this section, we'll look at a self-reinforcing metagame (ETH killer trading), a self-defeating metagame (Facebook rebranded to META), and a currently undergoing metagame (BTC ETF flows).

示例1：ETH Killer 元游戏

I'm assuming this is a metagame that most readers are very familiar with, and it's one of the trades in the 2021 bull market. Below is a table outlining the basic parameters of the metagame.

If the form is not clear, I will take a moment to explain this metagame in detail. Let's recall the bull market of 2021. Retail traders come here to gamble, ETH is expensive, scaling solutions are insufficient, and Solana and Avalanche position themselves as solutions to the problem (i.e., transactions are faster and cheaper), and that's the underlying mechanism.

The underlying mechanism is self-reinforcing (reflexive), and as long as we are in a bull market, ETH fees will remain high, so the case for going long ETH will be carried through the entire bull market. As SOL and AVAX outperformed ETH, trading became clearer and more participants traded. The nature of the underlying mechanism underpins an upward cycle of reflexes.

Given the persistence of metagames, it has given rise to sub-metagames, which are spin-offs of the main game. Specifically, the SOL and AVAX DeFi boom and the emergence of FOAN trading. Market participants are positioning Phantom, Harmony, Cosmos, and Near as new Alt L1 deals. Mechanically, those who feel like they're missing out on the main game find sub-games tangent to the main game to participate in.

In general, sub-games have smaller returns and don't last as long as the main game.

1. Main → main metagame; Minor → sub-meta game
2. Start, End, Duration → Time parameters
3. Mechanism → Description of the underlying mechanism
4. Return vs. Index → A measure of performance relative to a major or underlying mechanism theme
5. Absolute return → a measure of performance in absolute terms

The parameters of the game are largely subjective, and it is objectively clear that X is performing better than Y, but when it starts and ends is subjective. The same subjective logic can be applied to the selection of an index, how do we define outperformance? The function of the table is simply to approach some objective truth.

There are two graphs below - SOL vs. ETH and AVAX vs. ETH. They show the relative trading volume and relative price performance of SOL and AVAX against ETH and are based on the Binance Futures API. The idea is simple, use relative volume as a proxy for relative interest and see how this matches relative price performance.

It is worth noting that in the second half of 2021 find the alpha of this metagame in the long term. I'm assuming it's because of the drop in prices in the summer of 2021, which paused all the games while the narrative attracted more participants. When the market rebounds, the direction of capital allocation becomes clear. This may be motivated reasoning, but I think it's accurate to some extent.

In order to think about exit strategies, we need to revisit the assumptions of the underlying mechanism. This metagame is a solution to the ongoing problem (high ETH fees), a bull-based problem. Therefore, the most basic exit strategy is to sell in the belief that we are close to the end of the bull market.

示例2:Facebook更名为Meta

On October 28, 2021, Facebook changed its name to META, which sparked a speculative frenzy of crypto projects related to the metaverse, which is quite obvious as the underlying mechanism. The difference between this base mechanic and the previous one is the duration. Example 1 is self-reinforcing and example 2 is self-defeating, I mean the catalyst in example 2 is a one-time event. This is a slight game changer, let me explain.

Take a look at the chart below – it shows the change in attention over time. If we assume that each project has some equilibrium share of the attention economy, we have a baseline. After a one-time catalyst, we have a huge re-rating in the metaverse token's share of the attention economy. This drives unusual price swings, which in turn attracts more attention. However, as the catalyst faded away, the metagame began to disintegrate rapidly. This can also be understood from the perspective of vulnerability; Over time, the coordination point became more vulnerable to external forces, namely the price action of major currencies - and for the most part, Bitcoin's -9% drop on November 26 capped off the carnival. Over time, the ability of single-use catalysts to act as coordination points is diminishing – this is reflected in the following diminishing concerns:

Prior to the rebranding, Axie Infinity had already had a semi-closed development, and the concept of the metaverse was gaining traction in Silicon Valley. WITH ALL THE INGREDIENTS IN PLACE, META'S REBRANDING WAS JUST THE SPARK THAT IGNITED THAT FIRE. The main beneficiaries of the metagame are Decentraland ($MANA) and The Sandbox ($SAND) - which are immediately repriced.

Thirdly, in order to consider an exit strategy, we need to revisit the assumptions of the underlying mechanism. That is, the underlying mechanism of one-time catalysts is self-defeating. Therefore, people should actively look for ways to exit the trade. If we look at the chart below, we can see that it reflects the stylized example above, where relative volume can be used as a proxy for the share of the attention economy. In addition, it is important to understand the market structure, and it is impossible for $SAND and $MANA to consistently triple the trading volume of $BTC, which defies the laws of logic.

Example 3: BTC ETF metagame

Note that this section was originally written in late March, and updated thoughts on this metagame in this section can be found later in this section.

This is an example of a metagame that is currently underway; Most cryptocurrency market participants are engaged in this type of trading. The basic mechanism is that ETF inflows are bullish for the following reasons:

1. We are approaching halving, with the number of coins flowing into ETF products being several times the new supply. This makes the narrative of limited supply + tokens more compelling.
2. The approval of ETF products gives crypto assets legitimacy as an asset class and provides access to a whole new investor base to buy BTC.

Similar to the ETH Killer metagame (example 1), this metagame is self-reinforcing. ETF products are traded seven days a week, so the price of BTC is (loosely) traded as the β value of these ETF flows. Given the underlying mechanism, we can make some assumptions about ETF flows and prices:

1. ETF inflows are positive for BTC prices
2. ETF outflows are negative for BTC prices

The above is a basic model, which is a fairly straightforward game. However, as with all things in life, the devil is in the details. Given that GBTC was originally a closed-end fund, the vast majority of the outflows came from GBTC – and the flow of these funds is expected to slow down as we enter the second half of the year. = All other things being equal, GBTC outflows will be reduced, so net inflows should be boosted – bullish.

Current thoughts on this metagame:

I guess this will serve as a reflection on my original BTC ETF metagame paper. A lot has happened since I originally wrote this section, especially the halving has happened and ETF flows have been reduced and occasionally negative. I think this metagame is still ongoing, but reflexivity is working in the opposite direction, i.e., ETF inflows have turned into outflows, and prices have responded. The relationship between ETF flows and BTC price performance seems fairly clear in both directions.

It's important to note that ETF flows and prices are not mechanically correlated, and like all metagames, this is somewhat of a common illusion. As ETF flows find a balance, most likely with 0 daily flows, I expect this metagame to dissipate. It's important to note that the level of attention paid to ETF flows is related to their size, with days of both large and low flows making headlines, while average days go largely unnoticed. As this metagame moves further and further in the rearview mirror, I expect only outliers to get noticed.

In the near future, we may get an ETH ETF metagame similar to the BTC ETF metagame. Other things being equal, I expect:

1. As the likelihood of ETF approval becomes more apparent, ETH trading will increase, and we can use the approval odds and rhetoric of our Bloomberg ETF brethren as a proxy for this.
2. The risk is reduced after the approval of the ETF as the market analyzes the inflow of the ETF and the outflow of the EHE (Grayscale product).
3. If the inflow is comparable to BTC (which I doubt it), this is bullish. The lack of inflows is bearish and may be bullish for Solana.

Assuming that the fees for the ETH ETF product will be similar to those for the BTC ETF, I'm not entirely sure what the outcome of the higher fees will be, and Occam's Razor suggests that this will be bearish. BTC price action and BTC ETF inflows set the stage for ETH ETFs to perform well, which is somewhat of a logical reality, and when we start trading the ETF ETF metagame, I think the market will price it based on the performance of BTC ETFs. If there is a massive outflow of BTC ETFs between and after the approval of ETH ETFs, I think ETH ETFs will die. Other interesting things to keep an eye on include whether the ETH in the ETF will be staked and whether the ETF holders will get that yield, which seems unlikely because of "um, securities laws, Howie testing, etc.", but it would be a surprise if that were.

Some general thoughts

There are certain laws or logics in market behavior, and assets that violate these laws will quickly revert to the mean. Logic/law is largely dynamic, but the Overton window (i.e., the policy window) is changing more slowly than most people think. In addition, there are some laws that cannot be violated like gravity.

Metagames aren't just an investment framework, it's more of a mental model, and it's hard to build a solid structure around the development, evolution, and behavior of these games because they're all different. Identifying these games and theorizing about how they will develop requires a level of intuition, which is honed through market time and fundamental thinking.

I've detailed a self-defeating, self-reinforcing, and currently ongoing metagame, with other examples including:

• Meme, 2021
• ETH 合并,2022(自我挫败)
• Crypto x AI, 2024 (Self-Enhanced)
• SOL killers, 2024 (unknown)
• Meme, 2024 (ego frustration)
• RWA, 2024 (Self-Enhanced)
• New Currencies, 2024 (Variable)
• BTC ETF beta, 2024 (self-enhanced)

There are many types of metagames, and each one is different. However, the basic formula is the same: identify the metagame, understand its basic mechanics, infer the duration of the metagame, and then plan how to capture value in the best possible way.