Unstable - A Game Theory Approach
In clean models, equilibrium rules.
In real life? Chaos wins.
That’s where unstable strategies come in -- and why, paradoxically, they often outperform the “safe” ones.
Let’s break it down.
1. Predictability Gets Punished
In game theory, a “pure strategy” i.e. always playing the same move, is easy to counter. That’s why optimal players use mixed strategies: randomizing their moves to remain unreadable.
- In poker: bluff just enough to stay unpredictable.
- In boxing: fighters randomize strikes: high/low, fast/slow, left/right to stay unpredictable and survive.
- In markets: rotate narratives, shift bets, obscure edge.
Randomness isn’t weakness.
It’s strategic opacity as a shield against exploitation.
2. Volatility is Survival in Asymmetric Games
Crypto is messy. Information is uneven. Signals are reflexive.
You’re not playing chess; you’re playing poker in a hurricane.
In this environment:
- “Safe” strategies like stablecoin farming look smart up until the system cracks.
- “Unstable” strategies like memecoin rotation or barbell bets look dumb, until they deliver 100x'es.
This isn’t gambler’s fallacy.
It’s math: in convex systems, optionality > certainty.
The edge lives in fat tails,
and unstable strategies keep you exposed to them.
3. Unstable as Meta-Aware Posture
Unstable isn’t just a coin, it’s a signal.
It knows:
- Stability is usually simulated
- Safety is often yield-chasing theater
- The game rewards the ones who adapt
It wears the volatility on its sleeve.
Not because it wants chaos,
but because it knows it’s already here.
Conclusion
In dynamic games, rigid strategies break.
Flexible ones bend and stay in play.
Unstable doesn’t pretend to be safe.
It doesn’t fake predictability.
It’s the strategy that accepts the game as it is, not how we wish it to be.
Don’t optimize for comfort.
Optimize to survive.
Play the unstable meta.