See you on the other side that prints. π°
Cape
Joined March 2022
- Tweets20.3K
- Following1.7K
- Followers29.9K
- Likes35.7K
Pinned Tweet
The next 6 to 12 months are the ones where you change your life.
But, If you don't understand this little concept on how to prepare yourself for the next bull run, then forget about a 100x....
π§΅
one thing I find interesting about @primus_labs is the problem it's trying to solve.
they raised $7M in a round led by VanEck, with YZi Labs also participating, to develop its zkTLS and zkFHE technology.
the idea is to let applications verify real world data and use it without exposing the underlying information.
- example:
a DeFi protocol could check whether someone meets a financial requirement without needing access to their full account details.
that becomes more relevant as AI agents start handling financial tasks that require trusted data.
but the technology is only half the story.
I'd be watching for actual applications and repeat usage, not just the AI and privacy narrative.
few days left for you to start explore the XP tasks: s.kaito.ai/zJlvAyo
πππ«ππ₯ππππ²π©π δΊΊ retweeted
One thing worth examining with $FLOKI is whether its products can build demand beyond the meme.
There are a few different bets within the ecosystem:
β @ValhallaP2E : gaming
β @tokenfi : asset tokenization
β FlokiHub : Web3 identity
Having several products is not the same as having a working ecosystem.
The advantage is that each product can reach a different audience.
with the FLOKI brand connecting them all.
thus why $FLOKI remains one of my top memecoins to watch..
Some people see a meme. Others find their tribe.
700k Vikings. Gaming, crypto and DeFi. Plenty more on the horizon.
Follow @FLOKI and hear about the next big thing straight from the source. βοΈ
One thing worth examining with $FLOKI is whether its products can build demand beyond the meme.
There are a few different bets within the ecosystem:
β @ValhallaP2E : gaming
β @tokenfi : asset tokenization
β FlokiHub : Web3 identity
Having several products is not the same as having a working ecosystem.
The advantage is that each product can reach a different audience.
with the FLOKI brand connecting them all.
thus why $FLOKI remains one of my top memecoins to watch..
Some people see a meme. Others find their tribe.
700k Vikings. Gaming, crypto and DeFi. Plenty more on the horizon.
Follow @FLOKI and hear about the next big thing straight from the source. βοΈ
πππ«ππ₯ππππ²π©π δΊΊ retweeted
TOKENIZATION + AI AGENTS could be cryptoβs biggest narrative yet.
I just broke down a $332B tokenization market.
But hereβs what I think the market might be missing:
What happens when AI agents start putting tokenized assets to work? And just holding them.
Trading them, moving capital, managing collateral, hunting for yield, executing transactions 24/7.
At scale, the opportunity could be much bigger than putting real-world assets onchain.
It could be building the financial rails for a world where software moves money.
The real question?
Who captures the value: AI agents, stablecoins, DeFi, tokenization platforms, or the blockchains underneath them?
Thatβs the thesis Iβm watching. π
Tokenization is no longer a narrative. Itβs becoming a market structure.
@PanteraCapital just analyzed 671 assets across a $332B tokenization market.
And the most interesting takeaway isnβt how much value is moving onchain.
Itβs where the activity is happening, who is entering, and what people are actually using these assets for.
Letβs break it down. ‡
β€ The biggest action isnβt in tokenized stock spot markets
In June, equity perpetuals on @HyperliquidX and @Lighter_xyz generated $67.8B in volume.
Thatβs roughly 16x the spot volume of onchain tokenized stocks.
The market isnβt waiting for every stock to migrate onchain before trading equities in a crypto-native environment.
β€ Institutions are moving from exploration to execution
J.P. Morgan. HSBC. Fidelity. According to the report, major financial institutions launched onchain products this quarter.
This matters because institutional adoption has always faced a different set of constraints from crypto-native adoption.
Now the next phase is connecting blockchain infrastructure to existing pools of capital.
β€ Robinhood chain is one to watch
The report puts Robinhood Chainβs tokenized value growth at roughly 5x in its first month.
Weekly RWA volume reached $887.5M.
Thatβs a signal worth paying attention to. Distribution has always been one of the biggest advantages in finance.
You can build the best infrastructure in the world, but without users, liquidity, and access to assets, adoption remains theoretical.
β€ Open access is winning the activity war
One of the most revealing statistics in the report:
Open-access products held 41% of tokenized value but generated 99.8% of spot trading.
They accounted for less than half of the value, yet almost all the spot trading activity.
This suggests that capital sitting onchain and capital actively trading onchain are two very different things.
β€ Private credit is starting to do more than sit in a wallet.
The report also points to a maturing collateral market.
Private credit put 45% of its matched value to work in DeFi. The opportunity here isnβt limited to representing real-world assets digitally.
Itβs about making those assets useful inside financial systems that can programmatically recognize and deploy them.
If tokenized assets can reliably move from passive holdings into productive financial applications, the market expands beyond issuance and secondary trading.
β€ The real opportunity is the convergence.
Look at the five signals together:
- Equity perps are attracting enormous trading volume.
- Traditional financial institutions are launching onchain products.
- New blockchain ecosystems are rapidly building tokenized value.
- Open-access products are capturing a disproportionate share of spot activity.
- Private credit is finding uses as DeFi collateral.
β€ Hereβs what I think the market is still underpricing.
The biggest opportunity in tokenization may not be the tokenization of any single asset class.
It may be the infrastructure connecting them.
Issuance is one layer, trading is another.
Settlement, custody, liquidity, collateral, and cross-platform distribution are separate layers again.
The companies and protocols that successfully connect these layers could capture value well beyond the initial act of putting an asset onchain.
But there will be winners and losers.
The Bottom Line
The $332B tokenization market is not one unified market. Itβs a collection of markets developing at different speeds.
Trading is moving toward crypto-native venues.
Institutions are bringing traditional financial products onchain.
Open-access platforms are dominating reported spot activity.
And collateral markets are beginning to connect tokenized assets to DeFiβs financial machinery.
πππ«ππ₯ππππ²π©π δΊΊ retweeted
Tokenized RWAs are finding a home in DeFi lending, and Morpho is ahead of Aave in the figures shared here.
based on the latest figures in this breakdown, out of $31.9B in active onchain RWA assets, just $4.18B is being used in DeFi lending.
That's roughly 12.7%.
Most of that capital still sits outside lending markets.
Here's where that lending sits:
β Morpho Blue: $735.4M
β Aave V3: $438.1M
β Kamino Lend: $412.7M
β Grove Finance: $394.4m
β Pendle V2: $326.6m
β Aave Horizon: $150.8M
Aave V3 and Horizon combined hold $567.9M, still below Morpho Blue alone.
One reason may be how Morpho structures its markets.
Morpho lets curators create separate lending markets for specific collateral.
Aave's Horizon market takes a separate approach for institutional RWA lending.
That gives new RWA assets a way into DeFi without exposing every lender to the same pool of risk.
That flexibility matters when dealing with RWAs, where assets can have different redemption terms and liquidity risks.
Morpho's lead is worth watching
πππ«ππ₯ππππ²π©π δΊΊ retweeted
i thought this was AI cause i had to look it up twice to understand how insane this car is.
i always knew a day like this will come when we will have flying cars but i never expected it to be this quicker..
this shows how possible anything visual can be brought to live.
Elon is a pure genius and big ups to his team as wellβ¦π
i thought this was AI cause i had to look it up twice to understand how insane this car is.
i always knew a day like this will come when we will have flying cars but i never expected it to be this quicker..
this shows how possible anything visual can be brought to live.
Elon is a pure genius and big ups to his team as wellβ¦π
Tokenized RWAs are finding a home in DeFi lending, and Morpho is ahead of Aave in the figures shared here.
based on the latest figures in this breakdown, out of $31.9B in active onchain RWA assets, just $4.18B is being used in DeFi lending.
That's roughly 12.7%.
Most of that capital still sits outside lending markets.
Here's where that lending sits:
β Morpho Blue: $735.4M
β Aave V3: $438.1M
β Kamino Lend: $412.7M
β Grove Finance: $394.4m
β Pendle V2: $326.6m
β Aave Horizon: $150.8M
Aave V3 and Horizon combined hold $567.9M, still below Morpho Blue alone.
One reason may be how Morpho structures its markets.
Morpho lets curators create separate lending markets for specific collateral.
Aave's Horizon market takes a separate approach for institutional RWA lending.
That gives new RWA assets a way into DeFi without exposing every lender to the same pool of risk.
That flexibility matters when dealing with RWAs, where assets can have different redemption terms and liquidity risks.
Morpho's lead is worth watching
πππ«ππ₯ππππ²π©π δΊΊ retweeted
Aave has $18B in TVL globally, but on Base, Morpho is outperforming it by a huge margin.
I think thereβs a lesson here about how lending protocols scale.
Look at the difference.
On Base (TVL):
β’ $Morpho: $4.38B
β’ $Aave: $537M
Weekly lending fees:
β’ $Morpho: $2.51M
β’ $Aave: $248K
Morpho holds roughly 8x more capital and generates 10x more lending fees on the same network.
But I wouldnβt attribute that entirely to better lending products.
A large part of Morphoβs growth comes from how its infrastructure reaches users.
Coinbase and Robinhood Earn products each surpassed $500M in deposits in September, according to Morphoβs October 8 update.
Think about what that means.
Someone can access on-chain lending through an exchange or financial app without knowing which protocol operates underneath.
Morpho gets the lending activity, while the application handles distribution.
Thatβs a pretty efficient way to scale.
However, thereβs something Iβd be careful about when evaluating $MORPHO.
More deposits donβt necessarily mean better economics.
Iβd want to know:
β how much of that activity produces recurring revenue
β how dependent it is on major partners
β whether the token captures any of that value
Because if a few large integrations account for a significant share of deposits, losing one could materially affect growth.
My view is that $Morpho has demonstrated how effective embedded lending can be.
But Iβd rather evaluate the quality of those deposits than celebrate TVL alone.
Growing through distribution is one thing. Building a business that retains value from that distribution is another.
πππ«ππ₯ππππ²π©π δΊΊ retweeted
While you're busy hunting 100x memecoins, DEX Screener is quietly making money from the entire casino.
Just checked DefiLlama, and the numbers are ridiculous.
β 24H revenue: $95.7K
β 30D revenue: $4.59M
β All-time revenue: $148.83M
And apparently, projects are paying around $500 just to update their token's profile picture. π (Haven't verified that fee.)
Your token might never reach a $1M market cap, but at least its $500 profile picture will look good on the way to zero.
I'm starting to think the real winners in this memecoin casino aren't the traders.
It's the platforms collecting fees whether you win or lose.
πππ«ππ₯ππππ²π©π δΊΊ retweeted
Crypto has too many narratives to follow at once, so i broke the market down by sector.
Here are three tokens across each sector I'd keep on the research list:
β£ Revenue: $PUMP Β· $STONK Β· $PONS
β£ Privacy: $ZEC Β· $ZANO Β· $RAIL
β£ AI & Big Data: $NEAR Β· $QUBIC Β· $GRASS
β£ AI Agents: $VVV Β· $VIRTUAL Β· $KITE
β£ Robotics: $PEAQ Β· $GEOD Β· $IOTX
β£ AI Infrastructure: $TAO Β· $NOS Β· $SERV
β£ DePIN: $RENDER Β· $FIL Β· $ZBCN
β£ RWA Infrastructure: $LINK Β· $PLUME Β· $QNT
β£ Tokenized Assets: $ONDO Β· $CHEX Β· $RIO
Perp DEXs: $HYPE Β· $ASTER Β· $LIT
β£ DeFi: $AAVE Β· $UNI Β· $PENDLE
β£ Solana DeFi: $JUP Β· $RAY Β· $JTO
β£ Memecoins: $PENGU Β· $BONK Β· $CASHCAT
The sectors overlap, and these tokens don't all capture value in the same way.
Some have established products and measurable revenue while others depend more heavily on adoption and token incentives.
A sector gaining attention is one thing. A token capturing value from that growth is another.
which sector are currently banking big onβ¦?ππΌ
Crypto has too many narratives to follow at once, so i broke the market down by sector.
Here are three tokens across each sector I'd keep on the research list:
β£ Revenue: $PUMP Β· $STONK Β· $PONS
β£ Privacy: $ZEC Β· $ZANO Β· $RAIL
β£ AI & Big Data: $NEAR Β· $QUBIC Β· $GRASS
β£ AI Agents: $VVV Β· $VIRTUAL Β· $KITE
β£ Robotics: $PEAQ Β· $GEOD Β· $IOTX
β£ AI Infrastructure: $TAO Β· $NOS Β· $SERV
β£ DePIN: $RENDER Β· $FIL Β· $ZBCN
β£ RWA Infrastructure: $LINK Β· $PLUME Β· $QNT
β£ Tokenized Assets: $ONDO Β· $CHEX Β· $RIO
Perp DEXs: $HYPE Β· $ASTER Β· $LIT
β£ DeFi: $AAVE Β· $UNI Β· $PENDLE
β£ Solana DeFi: $JUP Β· $RAY Β· $JTO
β£ Memecoins: $PENGU Β· $BONK Β· $CASHCAT
The sectors overlap, and these tokens don't all capture value in the same way.
Some have established products and measurable revenue while others depend more heavily on adoption and token incentives.
A sector gaining attention is one thing. A token capturing value from that growth is another.
which sector are currently banking big onβ¦?ππΌ
Prediction markets have a problem that price feeds alone can't solve, some outcomes need interpretation.
Take Polymarketβs $242.2M market on whether Zelenskyy would wear a suit before July.
The photos and videos are public. But deciding whether his outfit qualifies as a βsuitβ under the market rules is a different task.
This is the specific problem @GenLayer is working on with Intelligent Contracts.
Instead of relying on a fixed data feed, the contract can read public sources and assess evidence against written rules.
GenLayerβs process uses five randomly selected validators running different AI models.
If a decision is challenged, the group can expand to 11, then 23.
The project reports a 97.2% resolution rate across addressable Polymarket markets in its public benchmark.
Thatβs worth noting, but Iβd want to understand the test conditions and how disputed cases performed before drawing conclusions from the number.
The use case makes sense.
Prediction markets are expanding into questions about politics, public statements and real-world events where the answer isn't always a simple data point.
But thereβs a difficult part here, getting several models to agree doesn't necessarily make their answer correct.
The rules still need to be clear, and users need a fair way to challenge a bad decision..
πππ«ππ₯ππππ²π©π δΊΊ retweeted
The $600B+ volume by @papertrade_xyz is an impressive number, but volume isn't the same as sustainable demand.
Papertrade's has raised a few questions for me.
β’ Who can actually trade?
Smaller positions appear difficult to fill, while larger traders have an advantage.
Meanwhile, the LP is approaching $2M, with nearly 300M $PAPER reportedly minted.
β’ Are traders here to trade or farm?
The model rewards losses with $PAPER.
Which creates an incentive to focus on token emissions rather than profitable trading.
If enough users are mainly chasing rewards, early activity may not last.
β’ What happens when incentives fade?
Continued token emissions could dilute existing holders, while the incentive structure may also become less attractive once the LP crosses the $2M threshold.
Personally, I'm less interested in the volume numbers than in what happens next.
Can Papertrade attract genuine trading demand, give smaller traders a fair chance?
These answers will tell us more about the model than volume alone.
β¦ @papertrade_xyz has reportedly generated over $600 billion in trading volume since launch.
That's a huge number for a new exchange, but after looking into how Papertrade works, I think the mechanics behind that volume deserve more attention.
Papertrade is a synthetic perpetuals exchange built on HyperEVM.
Unlike traditional perp DEXs, it operates without an order book, funding rates, or external liquidity providers.
And here's where things get different.
β₯ How does @papertrade_xyz work?
Traders deposit USDC and open $BTC or $ETH positions with up to 1,000Γ leverage.
Instead of executing trades on Hyperliquid, Papertrade uses Hyperliquid's live bid/ask midpoint to price positions.
Everything happens inside its own smart contracts.
There's no traditional order-book slippage or funding fee.
But the bigger difference is how it handles liquidity.
β₯ The liquidity pool starts at $0.
No seed capital, no external LPs.
The pool grows entirely from trader losses and liquidations.
For example:
If a trader loses $1,000, that money enters the liquidity pool.
When another trader makes a profit, the payout comes from that same pool.
But what if the pool doesn't have enough liquidity?
The trader gets their original margin back immediately, while unpaid profits enter an on-chain queue.
Future trader losses replenish the pool and settle those claims.
So profits aren't always paid immediately.
β₯ Losing traders receive PAPER tokens.
This is probably the part that caught my attention.
PAPER launched with zero initial supply, no premine, and no team or VC allocation.
Tokens are minted when traders lose money or get liquidated.
While the liquidity pool is below $2M:
$1 in eligible losses = 100 PAPER.
Above that threshold, emissions gradually decline.
PAPER can be staked to earn USDC from two sources:
β 1% of eligible realized PnL when the pool can cover settlements and the profit queue is empty.
β Excess LP gains above the roughly $5M threshold.
Essentially, losing traders help capitalize the pool and receive tokens linked to future protocol revenue.
β₯ But how did it generate $500B+ in volume?
The answer is largely leverage and token incentives.
At 1,000Γ leverage, just $1,000 in margin controls $1M in notional exposure.
So the reported $500B+ isn't actual capital deposited.
It's leveraged trading volume, while actual margin has reportedly been in the tens of millions.
PAPER incentives also encouraged traders to generate losses in exchange for tokens.
Some reportedly used offsetting long/short positions to farm PAPER while limiting directional exposure.
That helps explain the rapid activity.
β₯ There's still a catch.
Papertrade has no opening fees or funding rates, but profitable trades face an asymmetric haircut.
Losses go fully into the pool, while winning traders receive profits after deductions.
Combine that with 1,000Γ leverage, where a roughly 0.1% adverse move can liquidate a position, and the protocol has a structural advantage.
The risks are clear:
β Winning profits can remain unpaid in the queue.
β Extreme leverage makes liquidations easier.
β PAPER rewards depend on continued trading activity and protocol revenue.
β₯ My takeaway
Papertrade is experimenting with a different liquidity model.
Instead of attracting LP capital first, it builds liquidity from trading losses and rewards those losses with PAPER.
The $600B+ volume is impressive, but I wouldn't use that figure alone to judge its success.
I'm more interested in the actual liquidity pool balance, outstanding profit claims, and how much USDC PAPER stakers eventually receive.
Generating volume is one thing. Building a system that can consistently pay profitable traders is another.
β₯ @primus_labs is tackling two different problems with zkTLS and zkFHE.
zkTLS verifies where data came from.
zkFHE lets applications compute on encrypted data without exposing the underlying information.
Think of a DeFi protocol checking whether you hold $10K on Binance.
It could verify your assets and assess your eligibility without needing your full account details.
That opens up potential use cases in private credit, risk assessment, and financial eligibility.
The interesting part isn't just bringing Web2 data onchain.
It's making that data useful without making it public.
Verification is one step.
Private computation is what makes the data actionable.
Make sure you start explore the XP tasks here: s.kaito.ai/zJlvAyo
πππ«ππ₯ππππ²π©π δΊΊ retweeted
Livetrade is worth watching, especially after what we've seen with @papertrade_xyz.
@livetrade_gg whitelist is open and i just entered the whitelist.
$LIVE rewards start at 100 tokens per $1 lost, with the rate decreasing as cumulative losses grow.
Only 4,000 wallets play 2 hours before everyone.
Whitelist closes in 4 days.
folks like us who missed the early days of papertrade @livetrade_gg could be worth keeping your eyes on..
How to get Whitelisted:
- Go to: livetrade.gg/r/023YHZ
and follow up the instruction
I'd be watching this closely, the model is easy to launch.
Whitelist is open. 4,000 seats.
Link: livetrade.gg/quests
Traded on Hyperliquid or played Papertrade? You may already qualify.
1,500 seats each. First come, first served.
How to join:
1. Follow @livetrade_gg
2. Like + repost
3. Sign up on the site
Whitelisted players get 2 hours of early access.
Closes 17 Oct. Link in the next post π
Livetrade is worth watching, especially after what we've seen with @papertrade_xyz.
@livetrade_gg whitelist is open and i just entered the whitelist.
$LIVE rewards start at 100 tokens per $1 lost, with the rate decreasing as cumulative losses grow.
Only 4,000 wallets play 2 hours before everyone.
Whitelist closes in 4 days.
folks like us who missed the early days of papertrade @livetrade_gg could be worth keeping your eyes on..
How to get Whitelisted:
- Go to: livetrade.gg/r/023YHZ
and follow up the instruction
I'd be watching this closely, the model is easy to launch.
Whitelist is open. 4,000 seats.
Link: livetrade.gg/quests
Traded on Hyperliquid or played Papertrade? You may already qualify.
1,500 seats each. First come, first served.
How to join:
1. Follow @livetrade_gg
2. Like + repost
3. Sign up on the site
Whitelisted players get 2 hours of early access.
Closes 17 Oct. Link in the next post π
πππ«ππ₯ππππ²π©π δΊΊ retweeted
Whitelist is open. 4,000 seats.
Link: livetrade.gg/quests
Traded on Hyperliquid or played Papertrade? You may already qualify.
1,500 seats each. First come, first served.
How to join:
1. Follow @livetrade_gg
2. Like + repost
3. Sign up on the site
Whitelisted players get 2 hours of early access.
Closes 17 Oct. Link in the next post π
The $600B+ volume by @papertrade_xyz is an impressive number, but volume isn't the same as sustainable demand.
Papertrade's has raised a few questions for me.
β’ Who can actually trade?
Smaller positions appear difficult to fill, while larger traders have an advantage.
Meanwhile, the LP is approaching $2M, with nearly 300M $PAPER reportedly minted.
β’ Are traders here to trade or farm?
The model rewards losses with $PAPER.
Which creates an incentive to focus on token emissions rather than profitable trading.
If enough users are mainly chasing rewards, early activity may not last.
β’ What happens when incentives fade?
Continued token emissions could dilute existing holders, while the incentive structure may also become less attractive once the LP crosses the $2M threshold.
Personally, I'm less interested in the volume numbers than in what happens next.
Can Papertrade attract genuine trading demand, give smaller traders a fair chance?
These answers will tell us more about the model than volume alone.
β¦ @papertrade_xyz has reportedly generated over $600 billion in trading volume since launch.
That's a huge number for a new exchange, but after looking into how Papertrade works, I think the mechanics behind that volume deserve more attention.
Papertrade is a synthetic perpetuals exchange built on HyperEVM.
Unlike traditional perp DEXs, it operates without an order book, funding rates, or external liquidity providers.
And here's where things get different.
β₯ How does @papertrade_xyz work?
Traders deposit USDC and open $BTC or $ETH positions with up to 1,000Γ leverage.
Instead of executing trades on Hyperliquid, Papertrade uses Hyperliquid's live bid/ask midpoint to price positions.
Everything happens inside its own smart contracts.
There's no traditional order-book slippage or funding fee.
But the bigger difference is how it handles liquidity.
β₯ The liquidity pool starts at $0.
No seed capital, no external LPs.
The pool grows entirely from trader losses and liquidations.
For example:
If a trader loses $1,000, that money enters the liquidity pool.
When another trader makes a profit, the payout comes from that same pool.
But what if the pool doesn't have enough liquidity?
The trader gets their original margin back immediately, while unpaid profits enter an on-chain queue.
Future trader losses replenish the pool and settle those claims.
So profits aren't always paid immediately.
β₯ Losing traders receive PAPER tokens.
This is probably the part that caught my attention.
PAPER launched with zero initial supply, no premine, and no team or VC allocation.
Tokens are minted when traders lose money or get liquidated.
While the liquidity pool is below $2M:
$1 in eligible losses = 100 PAPER.
Above that threshold, emissions gradually decline.
PAPER can be staked to earn USDC from two sources:
β 1% of eligible realized PnL when the pool can cover settlements and the profit queue is empty.
β Excess LP gains above the roughly $5M threshold.
Essentially, losing traders help capitalize the pool and receive tokens linked to future protocol revenue.
β₯ But how did it generate $500B+ in volume?
The answer is largely leverage and token incentives.
At 1,000Γ leverage, just $1,000 in margin controls $1M in notional exposure.
So the reported $500B+ isn't actual capital deposited.
It's leveraged trading volume, while actual margin has reportedly been in the tens of millions.
PAPER incentives also encouraged traders to generate losses in exchange for tokens.
Some reportedly used offsetting long/short positions to farm PAPER while limiting directional exposure.
That helps explain the rapid activity.
β₯ There's still a catch.
Papertrade has no opening fees or funding rates, but profitable trades face an asymmetric haircut.
Losses go fully into the pool, while winning traders receive profits after deductions.
Combine that with 1,000Γ leverage, where a roughly 0.1% adverse move can liquidate a position, and the protocol has a structural advantage.
The risks are clear:
β Winning profits can remain unpaid in the queue.
β Extreme leverage makes liquidations easier.
β PAPER rewards depend on continued trading activity and protocol revenue.
β₯ My takeaway
Papertrade is experimenting with a different liquidity model.
Instead of attracting LP capital first, it builds liquidity from trading losses and rewards those losses with PAPER.
The $600B+ volume is impressive, but I wouldn't use that figure alone to judge its success.
I'm more interested in the actual liquidity pool balance, outstanding profit claims, and how much USDC PAPER stakers eventually receive.
Generating volume is one thing. Building a system that can consistently pay profitable traders is another.