Trading Squeeth: The Perpetual That Thinks It's an Option

The first time I saw Squeeth, I thought the team had made a typo. "Squared ETH" became "Squeeth" - okay, cute. But then I saw the funding rates and my brain broke. Why were people paying 80% annualized to hold this thing?

The Perpetual That Confused Everyone (Including Me)

When I joined Opyn in early 2022, Squeeth had just launched. Everyone was excited about this "power perpetual" that tracked ETH². I nodded along in meetings, pretending I understood why this was revolutionary. Spoiler: I didn't.

Here's what I thought I knew: it's a perpetual contract, like the ones on dYdX or Binance. You go long, ETH goes up, you make money. Simple, right?

Wrong. So wrong.

My first trade was a disaster. ETH moved up 5%, and I expected my Squeeth position to be up 10% (because, you know, squared). Instead, I was barely breaking even after funding costs. That's when I realized - this thing doesn't behave like a normal perp at all. It behaves like an option.

Squeeth shut down in November 2024 after an incredible run - 18,000+ users, over $1.8 billion in volume, and the Crab strategy delivering 50%+ returns. But the lessons I learned trading it? Those are forever. And with Opyn Markets bringing power perps back, these insights are more relevant than ever.

What Squeeth Actually Was (And Why It Broke My Brain)

Let me save you months of confusion. Squeeth was:

A perpetual contract that tracks ETH²
The first successful power perpetual in DeFi
An option masquerading as a perpetual

The key insight that finally made it click: Squeeth has constant gamma of 2.

In normal-people speak: while regular perpetuals give you linear exposure (ETH up 10% = position up 10%), Squeeth gives you convex exposure. Your gains accelerate as ETH rises, just like an option.

But here's the kicker - unlike options, Squeeth never expires. It's perpetual convexity. Once I understood this, everything else started making sense.

The Black-Scholes Connection That Blew My Mind

Remember when I mentioned those crazy high funding rates? There's a beautiful mathematical reason for it, rooted in the Black-Scholes model (yes, the famous option pricing formula).

Under Black-Scholes assumptions, the theoretical price of a squared exposure is:

Squared ETH future = ETH² * exp(volatility²)

That exp(volatility²) term? That's your funding rate. It's literally the cost of volatility.

When I first saw this derivation, I had to sit down. The funding rate isn't some arbitrary number - it's the market's expectation of ETH variance. Squeeth wasn't just a trading instrument; it was a volatility oracle.

This meant you could look at Squeeth's price and immediately know what the market thought about future volatility. No complex calculations, no option chains to analyze. Just one number.

Volatility: The Puppet Master Behind Everything

Here's what took me way too long to understand: when you trade Squeeth, you're not really trading ETH. You're trading volatility.

Let me show you what I mean. Say ETH is trading at $2,000:

If implied volatility is 50%, Squeeth trades around ETH² * 1.28
If implied volatility jumps to 100%, Squeeth trades around ETH² * 2.72

ETH price didn't change, but Squeeth just doubled in value. This isn't a bug - it's the entire point.

We used to compare Squeeth's implied volatility with Deribit options every morning. When Squeeth IV was 80% and Deribit was showing 70%, that was a signal. Either Squeeth was too expensive, or vanilla options were too cheap.

During the March 2023 banking crisis, I watched Squeeth IV spike to 120% while spot ETH barely moved. The market was screaming "fear" through Squeeth prices before anything else reacted. That's when I truly understood why people called it a volatility oracle.

How We Actually Traded This Beast

The Basis Trade (My Personal Favorite)

The simplest strategy was beautiful:

Buy 1 ETH spot
Short 0.5 Squeeth (because Squeeth delta = 2)
Collect funding while staying market-neutral

During the 2022 bull runs, funding rates hit 0.5% daily. That's 180% annualized! We were basically running a money printer. The catch? You needed to rebalance constantly as ETH moved, and gas fees could eat your profits if you weren't careful.

The Crab Strategy (Where the Real Money Was)

Opyn built an automated delta-neutral strategy called Crab. It was essentially selling Squeeth and rebalancing to stay delta-neutral - classic gamma trading.

What is gamma trading? This gets to the heart of why Squeeth behaves so differently from normal perps. When you sell Squeeth, you have "negative gamma" - your losses accelerate as ETH moves against you.

Here's why: Squeeth tracks ETH², so small moves become big moves. If ETH goes $2000→$2100 (+5%), Squeeth goes from tracking $4M to $4.41M (+10.25%). But if ETH continues to $2200 (+10% total), Squeeth jumps to $4.84M (+21% total). Notice how each additional ETH move hurts you more than the last?

This creates the rebalancing nightmare: as ETH rises, your Squeeth losses accelerate, forcing you to buy more ETH hedge at higher prices. When ETH falls, you need less hedge, so you sell ETH at lower prices. You're constantly buying high and selling low.

Contrast this with buying Squeeth (positive gamma): Your gains accelerate upward, but your losses decelerate downward. The ETH² relationship protects you - going from $2000 to $1900 hurts less than going from $1900 to $1800.

Crab automated this entire gamma trading process - selling Squeeth (collecting funding), hedging with ETH, and rebalancing constantly. The problem? You're always forced to trade at the worst possible times.

The strategy crushed it, delivering over 50% returns from inception. But here's what the marketing didn't tell you: it wasn't truly market-neutral. You were short volatility.

Why short volatility? This is where things get really interesting. When you sell Squeeth, you're essentially betting that realized volatility will be lower than implied volatility. Think of it like selling insurance - you collect premiums upfront but pay out when bad things happen.

Here's the economics: Crab collected funding from Squeeth longs (around 0.1-0.5% daily during normal times). That's your "premium" for taking on the risk. If ETH moves smoothly, you keep most of that funding. But if ETH gets violent, your rebalancing costs explode.

Real example: Say Crab collects 0.3% daily funding on a $1M position = $3,000 per day.

Scenario 1 - Low volatility: ETH slowly drifts from $2000 to $2050 over a week. Rebalancing costs are minimal, maybe $500 total. Crab keeps $20,500 in funding minus $500 in costs = $20,000 profit.

Scenario 2 - High volatility: ETH whipsaws between $1900-$2100 multiple times per day. Each swing forces expensive rebalancing. Total rebalancing costs hit $25,000 for the week. Crab loses $25,000 - $21,000 funding = $4,000 loss.

This is the short vol trade in a nutshell: you profit when markets are calm and predictable, but violent moves crush you. The funding you collect is compensation for bearing this volatility risk.

The cruel irony: The times when Crab performed worst (high volatility periods) were exactly when people most wanted that convex upside protection that Squeeth provided. You were selling insurance right when people needed it most. When markets got choppy, Crab got hammered.

I remember Black Thursday in May 2022. Crab was down 15% in a day while people in Discord were asking "I thought this was market neutral?" That's when I learned the difference between delta-neutral and market-neutral.

Vol Basis Trading (For the Spreadsheet Warriors)

Before diving into this strategy, let me explain what volatility actually means. Volatility is simply how much and how fast prices move around. High volatility = wild price swings (think crypto in 2022). Low volatility = boring, steady prices (think savings accounts).

In options and derivatives, "implied volatility" is what the market thinks volatility will be in the future. It's baked into prices - if traders expect chaos, they pay more for options and derivatives that benefit from big moves.

How do you actually calculate implied volatility? This is where things get interesting. For traditional options, traders use the Black-Scholes formula backwards. You know the option's market price, so you solve for what volatility assumption would give you that price. It's like reverse-engineering the market's fear level.

For Squeeth, it's more elegant. Remember that funding rate formula I mentioned earlier? The daily funding rate literally equals the daily variance the market expects. So if Squeeth has 0.24% daily funding:

Daily variance = 0.24%
Daily volatility = √0.24% = 1.55%
Annualized volatility = 1.55% × √365 = 29.6%

That's it. Squeeth's funding rate IS the implied volatility. No complex option pricing models needed - the market tells you directly through funding what volatility it's pricing in. This made comparing Squeeth to options incredibly straightforward.

This was where things got sophisticated. We'd build portfolios that were:

Long Squeeth
Short a carefully weighted basket of Deribit options
Continuously rebalanced to stay delta and vega neutral

The idea: capture the pricing differential between Squeeth vol and vanilla option vol. When Squeeth implied 85% vol and Deribit showed 75%, you'd go long Squeeth and short options.

Here's the arbitrage logic: You're betting that the same risk (ETH volatility) is mispriced between two markets. Say ETH actually realizes 80% volatility:

Your Squeeth (bought at 85% implied): You overpaid by 5% vol = small loss
Your short options (sold at 75% implied): You undersold by 5% vol = small profit
Net result: If sized correctly, the option profit exceeds the Squeeth loss

You're not betting on ETH direction - you're betting the 10% vol spread is too wide and will converge. Either Squeeth vol drops toward 75%, options vol rises toward 85%, or they meet in the middle. All scenarios make you money.

One trader I knew ran this strategy for six months and printed money consistently. His secret? He built a custom spreadsheet that calculated the exact option weights needed for perfect vega neutrality. Pure arbitrage.

The Smile Trade (PhD-Level Stuff)

This one still makes my head hurt. Options don't just have one volatility - they have a whole "smile" of volatilities across different strikes. Squeeth, being a power perp, was sensitive to the entire smile shape.

The real degenerates would trade the shape of the volatility smile. When the options market showed a steep smile (high vol for OTM options) but Squeeth implied a flat smile, they'd construct these complex positions to arbitrage the difference.

I tried this once. Once. The mental overhead of managing smile risk while also handling delta, gamma, and vega nearly broke me.

Understanding the Greeks (Or As We Called Them, "Squeeks")

Let me break down Squeeth's Greeks in human terms:

Delta = 2 * ETH price

Your position's sensitivity to ETH moves
Always positive for longs, always linear
Example: At $2,000 ETH, each Squeeth has 4,000 delta

Gamma = 2 (constant!)

This is the magic
Your delta always changes by 2 for each $1 ETH moves
No gamma decay like options - it's always there

Vega = Sensitivity to volatility

Massive for Squeeth
A 10% increase in IV could mean 20%+ gain
This is why Squeeth was really a vol trade

Theta = -Funding rate

The cost of holding that beautiful gamma
Paid continuously through the normalization factor
Usually 0.1-0.5% daily during normal times

We had this tool called SqueethLab - a spreadsheet where you could plug in your position and see how it would perform under different scenarios. I spent hours playing with it, finally understanding how all these Greeks worked together.

The Funding Rate Revelation

Here's the mind-blowing part: Squeeth's funding rate equals the expected variance of ETH.

Wait, what's variance? Variance is just volatility squared. If ETH has 20% volatility, its variance is 20² = 400 (or 4% in decimal terms). Variance measures the "spread" of price movements - how far prices deviate from their average. Higher variance = wilder price swings.

Why does funding = variance? This comes from the Black-Scholes math. Under the model's assumptions, the theoretical price of a squared exposure (like Squeeth) is:

Squeeth Price = ETH² × e^(variance × time)

That e^(variance × time) term creates a premium above the raw ETH² value. This premium - the extra cost of holding squared exposure - becomes the funding rate. You're literally paying the market's expectation of variance.

Let that sink in. The funding rate - that annoying fee longs pay shorts - is literally the market's prediction of how volatile ETH will be.

Some quick math:

Daily funding of 0.24% = daily variance of 0.24%
Square root of 0.24% = 1.55% daily volatility
Annualized: 1.55% * √365 = 29.6% implied volatility

So when funding was 0.24% daily, the market was pricing in 30% annualized vol. When it spiked to 0.5% daily? That's 44% vol. The market was scared.

The beautiful part: This wasn't just theory - it worked in practice. Squeeth essentially became a pure volatility instrument where the funding rate directly reflected the market's fear level. No complex option pricing models needed.

This relationship held remarkably well. We'd calculate Squeeth IV every morning and compare it to Deribit. When they diverged significantly, it was trading time.

Market Making: A Special Kind of Torture

Market making Squeeth was not for the faint of heart. You needed to:

Understand gamma exposure
Hedge using a combination of spot and options
Account for funding in your pricing
Handle the 10,000x price scaling confusion

I watched market makers struggle with this. One MM told me: "I can handle complex options books, but Squeeth broke all my models. The constant gamma plus continuous funding plus that weird scaling... it was like learning to trade all over again."

The successful MMs built entirely new systems just for Squeeth. They couldn't just plug it into their existing infrastructure.

The Shutdown: End of an Era

November 4, 2024, 16:00 UTC. Squeeth shut down.

Final settlement: ~0.032719 ETH per oSQTH. All positions force-closed with zero price impact. Just like that, the experiment ended.

But what an experiment it was:

First successful power perpetual in DeFi
Proved you could create non-expiring convex exposure
Pioneered in-kind funding mechanisms
Showed that DeFi could innovate beyond copying TradFi

The shutdown wasn't a failure - it was a graduation. Squeeth proved the concept. Now Opyn Markets is taking those lessons and building something bigger.

The Future: Everything Is a Perp

Opyn Markets is bringing power perps back, but bigger. Imagine:

Squared exposure to any token (Squitcoin for BTC!)
0.5-perps that track Uniswap LP positions
0-perps for pure funding trades
All composable, all on-chain

The insight that drove all of this: everything in DeFi is a perp. Your LP position? That's a 0.5-perp. Your lending position? 0-perp. Once you see it, you can't unsee it.

What Squeeth Taught Me

Trading Squeeth taught me more about options than actually trading options ever did. It forced me to understand:

How volatility drives derivative prices
Why gamma is the most important Greek
How funding mechanisms create equilibrium
That the best trades are often the most confusing ones

But more than that, it taught me that DeFi can genuinely innovate. We're not just recreating TradFi on-chain. We're building things that couldn't exist anywhere else.

Squeeth might be gone, but power perps are just beginning. And this time, I actually understand why they're revolutionary.

Miss you, Squeeth. Thanks for the education, the profits, and the endless confusion that finally turned into clarity. See you again soon on Opyn Markets.

Summary: The Key Takeaways

If you made it this far, here's what matters most:

Squeeth wasn't really a perpetual - it was an option in disguise. With constant gamma of 2, it gave you perpetual convexity. Your gains accelerated as ETH rose, but unlike options, it never expired.

It was actually a volatility trade. The funding rate literally equaled expected variance. When you traded Squeeth, you were betting on how volatile ETH would be, not just its direction.

The strategies fell into two camps:

Long vol plays: Buy Squeeth when you think realized vol will exceed implied vol (funding rate)
Short vol plays: Sell Squeeth (like Crab) to collect funding, betting vol stays low

The math was beautiful: Funding rate = daily variance. No complex option models needed - the market told you directly what volatility it was pricing in.

The key insight: Everything in DeFi can be viewed as a power perpetual. Your LP position? That's a 0.5-perp. Your lending position? 0-perp. Once you see it, you can't unsee it.

For traders: Understanding gamma and volatility is crucial. Negative gamma forces you to buy high and sell low. Being short volatility means you profit in calm markets but get crushed when things get choppy.

Squeeth proved you could create genuinely innovative derivatives in DeFi. Now Opyn Markets is taking those lessons and building the next generation of power perps.

References

Squeeth Shutdown Announcement - Official announcement of Squeeth's shutdown in November 2024
How to Think About Squeeth Returns - Deep dive into SqueethLab and return analysis
Gamma Transforms: How to Hedge Squeeth Using Uni V3 - Advanced hedging strategies using Uniswap V3
Squeeth Insides Volume 1: Funding and Volatility - Technical deep dive into Squeeth's funding mechanisms