Ambassador @Autheo_Network & @tryquantio | Previously @zama | DM for paid promo/Collab.
Joined March 2020
- Tweets52.3K
- Following8.6K
- Followers12.5K
- Likes54.2K
Pinned Tweet
Just checked my Sorsa Score… 612
Quality > quantity.
Feels good to see the real network showing up.
Real growth, no shortcuts
Building in public + open for solid collabs.
What’s yours at?
Drop it below 📷 @SorsaApp
Finally hit 500 @SorsaApp score 🔥
Tier 3 Credible unlocked
Real growth, no shortcuts
Building in public + open for solid collabs.
Share yours 👇
Oliver retweeted
Five research tabs. One platform. Here's how I investigated BTC with Quant AI.
I used to have 5 tabs open for one trade - chart, news, sentiment, signals, risk. Today I did it all inside @tryquantio AI.
Asset: BTC - $80,503
Currently consolidating right above the $80K psychological handle after pulling back from $87K October highs. Neutral setup.
Here is my 5-task workflow inside Quant AI:
1. Market Overview
I asked: What's happening with price, key trends and levels?
Quant AI showed: Range compression $79K - $85K, BTC Dominance 60.04%, Fear & Greed 45 Neutral.
Key levels: Support $79K-$80.5K shelf, major support $75,446 (MicroStrategy avg cost), Resistance $82.7K (50-day MA & ETF cost basis
2. News & Catalysts
I asked: What recent news could move BTC?
Bullish: Strive acquired $511M BTC (now 43K BTC), cumulative ETF inflows $57B-$58B with $301.2M weekly inflow ending Oct 23. CLARITY Act pushing in lame-duck session.
PPI inflation 6.3% sticky, 84.7% odds of Dec Fed hike, choppy ETF flows -$635.6M outflow on Oct 22. Market is waiting for Oct 27-28 FOMC.
3. Market Sentiment
I asked: What's sentiment on X and in Signals?
Quant AI: Cautious neutrality. Traders like Altcoin Sherpa asking how long $79K holds. Crypto Tony: range-bound - pumps for shorting, dumps for longing. BUT top traders on Quant perps leaderboard are 100% short - 9/9 traders, $578.96M short notional.
4. Trading Signals
I asked: What signals support or challenge outlook?
Bullish signals: Q3 ETF inflows +$6.3B, Dominance high, equity tailwind SPY +0.90% QQQ +1.45%.
5. Risk Assessment
I asked: What could go wrong?
Biggest risks Quant AI flagged:
$80K liquidation cascade: dense stops just below $79K, $440M longs liquidated recently
ETF run: multi-day outflows >$500M/day removes bid depth
My Conclusion:
Doing this in one Quant AI session saved me hours. BTC is healthy consolidation, institutionally supported, but technically vulnerable at $79K-$80K until FOMC clears. I'm not chasing mid-range. I'm waiting for $79.2K-$80.5K dip with hard invalidation or breakout above $82.7K.
I researched one market across five areas using Quant AI. Want to simplify your own trading research?
Try it through my link :
app.tryquant.io/?ref=ST8NM9Q…
@tryquantio #QuantAIPioneers
Five research tabs. One platform. Here's how I investigated BTC with Quant AI.
I used to have 5 tabs open for one trade - chart, news, sentiment, signals, risk. Today I did it all inside @tryquantio AI.
Asset: BTC - $80,503
Currently consolidating right above the $80K psychological handle after pulling back from $87K October highs. Neutral setup.
Here is my 5-task workflow inside Quant AI:
1. Market Overview
I asked: What's happening with price, key trends and levels?
Quant AI showed: Range compression $79K - $85K, BTC Dominance 60.04%, Fear & Greed 45 Neutral.
Key levels: Support $79K-$80.5K shelf, major support $75,446 (MicroStrategy avg cost), Resistance $82.7K (50-day MA & ETF cost basis
2. News & Catalysts
I asked: What recent news could move BTC?
Bullish: Strive acquired $511M BTC (now 43K BTC), cumulative ETF inflows $57B-$58B with $301.2M weekly inflow ending Oct 23. CLARITY Act pushing in lame-duck session.
PPI inflation 6.3% sticky, 84.7% odds of Dec Fed hike, choppy ETF flows -$635.6M outflow on Oct 22. Market is waiting for Oct 27-28 FOMC.
3. Market Sentiment
I asked: What's sentiment on X and in Signals?
Quant AI: Cautious neutrality. Traders like Altcoin Sherpa asking how long $79K holds. Crypto Tony: range-bound - pumps for shorting, dumps for longing. BUT top traders on Quant perps leaderboard are 100% short - 9/9 traders, $578.96M short notional.
4. Trading Signals
I asked: What signals support or challenge outlook?
Bullish signals: Q3 ETF inflows +$6.3B, Dominance high, equity tailwind SPY +0.90% QQQ +1.45%.
5. Risk Assessment
I asked: What could go wrong?
Biggest risks Quant AI flagged:
$80K liquidation cascade: dense stops just below $79K, $440M longs liquidated recently
ETF run: multi-day outflows >$500M/day removes bid depth
My Conclusion:
Doing this in one Quant AI session saved me hours. BTC is healthy consolidation, institutionally supported, but technically vulnerable at $79K-$80K until FOMC clears. I'm not chasing mid-range. I'm waiting for $79.2K-$80.5K dip with hard invalidation or breakout above $82.7K.
I researched one market across five areas using Quant AI. Want to simplify your own trading research?
Try it through my link :
app.tryquant.io/?ref=ST8NM9Q…
@tryquantio #QuantAIPioneers
Oliver retweeted
The automation stopped exactly where the web page started.
Last year, a hardware vendor owed us a credit whenever a software update shipped with a known bug that hit our devices. The bug was public. The amount was a formula.
Someone still had to open the vendor’s security notice, check that our exact version was listed, and declare the credit due. Their reports came late, the wording got disputed, and once they were out sick.
A smart contract, a program that holds and pays out money by fixed rules, could have kept the funds safe. It still would have waited on that person.
In crypto, a middleman like that is called an oracle. I think of it as the last trusted step. Write any rule you like, but the moment it needs a fact from the web, someone outside the contract gets the final say.
@GenLayer’s Intelligent Contracts go and look for themselves instead of waiting to be told, then ask an AI whether the credit is owed. And no single reader gets the last word: one validator proposes an answer, others check it with their own AI models, and it only stands if they agree. If not, it tries again.
A bad notice is still a bad notice. But a sick day stops being a problem, and a wording dispute becomes several readings instead of one person’s opinion.
Who is the last trusted step in your own work? The one person everything waits on?
Oliver retweeted
The grant pays out once the team shows a working demo, but the demo link returns an error.
That tells the protocol the page could not be reached at that moment. It doesn't tell the protocol whether the demo was completed. A binary pass or fail can confuse an access problem with a failed project.
I'd give the team a short retry window, then check a second source approved before funding.
If neither source verifies the demo, put the funds into review rather than automatically rejecting the team or paying without proof. It takes longer, but everyone knows the fallback before a dispute arises.
Rules like this depend on where the contract gets its evidence. Traditional smart contracts often rely on an oracle to report facts from the web.
@GenLayer's Intelligent Contracts can retrieve web evidence for a language model to interpret.
A designated leader proposes a result, and validators assess it using their own models. If their assessments diverge, a different leader gets another attempt, and an accepted result can still be appealed.
What should count as backup evidence: a recorded demo, a reproducible test environment, or an independent reviewer?
Oliver retweeted
Institutions didn’t remove volatility.
They simply became the new source of it.
The smart move isn’t reacting to the headline.
It’s understanding the shift before the next one hits.
That’s what @tryquantio is built for.
Checkout quant ai :
app.tryquant.io/?ref=ST8NM9Q…
@tryquantio #QuantAIPioneers
$635M left US spot Bitcoin ETFs in a single session, reversing three consecutive days of inflows.
A useful reminder that institutional participation doesn't eliminate volatility.
It changes who participates in it.
Stay curious: app.tryquant.io/chat
Institutions didn’t remove volatility.
They simply became the new source of it.
The smart move isn’t reacting to the headline.
It’s understanding the shift before the next one hits.
That’s what @tryquantio is built for.
Checkout quant ai :
app.tryquant.io/?ref=ST8NM9Q…
@tryquantio #QuantAIPioneers
$635M left US spot Bitcoin ETFs in a single session, reversing three consecutive days of inflows.
A useful reminder that institutional participation doesn't eliminate volatility.
It changes who participates in it.
Stay curious: app.tryquant.io/chat
Oliver retweeted
$635M left US spot Bitcoin ETFs in a single session, reversing three consecutive days of inflows.
A useful reminder that institutional participation doesn't eliminate volatility.
It changes who participates in it.
Stay curious: app.tryquant.io/chat
Instead of chasing next week's market moves, I used @tryquantio AI to prepare my watchlist in advance.
I opened Discover inside Quant AI and built my Top 3 watchlist for next week: BTC, BNB, SOL
Opportunity:
BTC is sitting right on a crucial inflection at $80K.
Sol Testing $100 psychological support after major Alpenglow upgrade on Oct 21 finality down to ~150ms from 12.8s. Huge for DeFi throughput.
Key Catalysts:
Spot ETF inflow/outflow trend is the #1 driver. Plus weekly close above/below the 1W 50MA at $82K.
$1.2 BILLION supply burn just executed + bStocks tokenized collateral with zero maker fees pulling capital into BNB ecosystem. AI trading tools rollout increasing gas burn.
Risks:
Daily close below $80K could trigger long liquidations toward $75K - $72K.
Rejection at $750 resistance ceiling = double top risk back to $720. Then deeper to $575.
What to watch:
Reclaim $82K on volume >$25B + positive ETF inflows >$200M/day = bullish toward $85K-$86K.
Defend $100 and reclaim $110 = path to $124-$125. Lose $100 = stay flat.
My Conclusion:
Most interested in BNB. It's showing relative strength, deflationary catalyst, and clear levels. But BTC decides if alts get permission to run. SOL is the highest risk/reward - $100 must hold.
I built this inside Quant AI build your own watchlist through my link:
app.tryquant.io/?ref=ST8NM9Q…
@tryquantio #QuantAIPioneers
Oliver retweeted
The right leverage multiple is not the same for every asset.
At Bitcoin volatility near 60 percent, the safe band closes early. That is why long-horizon products at 2x and 3x BTC decay.
On gold or the S&P 500, the band stretches much further.
I joined 2Factor Finance's Points Program because I kept wondering why 3x BTC products decay, and 2Factor explains it with actual numbers.
It splits volatility into two tranches. The leveraged junior has no liquidation risk, so leverage can survive long-horizon holding.
Season 1 is social activity, education and referrals. Marks come from verified actions only and have no cash value.
When 2Factor launches, the leaderboard freezes. The top 10 accounts share 1 BTC, paid in cbBTC.
2Factor Finance is on Base and works with Coinbase to bring Kelly-optimized leverage onchain, a strong use case for tokenized stocks.
Join and grab your referral link:
points.2factor.finance/r/amk…
@2FactorFinance
Have you ever held a 2x or 3x product for months and watched it decay?
Oliver retweeted
Would you still follow this trader after seeing the historical drawdown?
My selection Which trader?
Trader 0x484bc1...4562f8
But also 24h PnL -$468.94K and volume $0.
Wait, how +23% ROI and -$468K loss and $0 volume at same time?
That's why I investigated.
The performance What makes it interesting?
-$468K PnL = not trading loss it's cashflow artifact. Large withdrawal / transfer. Balance tracker shows as negative delta.
Extremely conservative sizing at account level. But position itself is bleeding.
The drawdown Largest decline?
Account-level drawdown: -$157 on $45.8K = -0.34% nothing. Noise.
Position-level drawdown: -$157 on $366 margin = -43.16% on that trade.
FET dropped -8.63% spot since his entry, but with 5x leverage his margin down -43%.
The impact What would this mean for $1,000?
If you copy his sizing (4% of account in trade): Loss = -$3.45 on $1,000 → $996 left, need +0.35% to recover. Acceptable.
Recovery is exponential. After -20% you need +25%. After -43% you need +76%. That's why drawdown matters more than return.
My verdict Would I accept this risk?
For me? I wouldn't follow strategy that holds -43% on 5x without volume. Returns look good (+23% ROI) but risk behavior shows no invalidation discipline.
Past drawdown doesn't guarantee max future loss it tells you worst pain trader tolerated before. Could you handle that pain?
Explore risk behind returns:
app.tryquant.io/?ref=ST8NM9Q…
@tryquantio #QuantAIPioneers
Would you still follow this trader after seeing the historical drawdown?
My selection Which trader?
Trader 0x484bc1...4562f8
But also 24h PnL -$468.94K and volume $0.
Wait, how +23% ROI and -$468K loss and $0 volume at same time?
That's why I investigated.
The performance What makes it interesting?
-$468K PnL = not trading loss it's cashflow artifact. Large withdrawal / transfer. Balance tracker shows as negative delta.
Extremely conservative sizing at account level. But position itself is bleeding.
The drawdown Largest decline?
Account-level drawdown: -$157 on $45.8K = -0.34% nothing. Noise.
Position-level drawdown: -$157 on $366 margin = -43.16% on that trade.
FET dropped -8.63% spot since his entry, but with 5x leverage his margin down -43%.
The impact What would this mean for $1,000?
If you copy his sizing (4% of account in trade): Loss = -$3.45 on $1,000 → $996 left, need +0.35% to recover. Acceptable.
Recovery is exponential. After -20% you need +25%. After -43% you need +76%. That's why drawdown matters more than return.
My verdict Would I accept this risk?
For me? I wouldn't follow strategy that holds -43% on 5x without volume. Returns look good (+23% ROI) but risk behavior shows no invalidation discipline.
Past drawdown doesn't guarantee max future loss it tells you worst pain trader tolerated before. Could you handle that pain?
Explore risk behind returns:
app.tryquant.io/?ref=ST8NM9Q…
@tryquantio #QuantAIPioneers
Oliver retweeted
Most people switch off on the weekend.
The ones who stay sharp don’t.
They keep one eye on their high-leverage positions through @tryquantio quiet, focused, always one step ahead.
No drama.
Just discipline.
That’s how real edge is built.
Want to check yours?
Visit : app.tryquant.io/?ref=ST8NM9Q…
@tryquantio #QuantAIPioneers
Saturday plans:
Normal people: Riding roller coasters for the adrenaline rush.
This guy: Checking his 50x leveraged positions on Quant mid-drop.
Be this guy.
bit.ly/3VKPxhE
Most people switch off on the weekend.
The ones who stay sharp don’t.
They keep one eye on their high-leverage positions through @tryquantio quiet, focused, always one step ahead.
No drama.
Just discipline.
That’s how real edge is built.
Want to check yours?
Visit : app.tryquant.io/?ref=ST8NM9Q…
@tryquantio #QuantAIPioneers
Saturday plans:
Normal people: Riding roller coasters for the adrenaline rush.
This guy: Checking his 50x leveraged positions on Quant mid-drop.
Be this guy.
bit.ly/3VKPxhE
Oliver retweeted
Saturday plans:
Normal people: Riding roller coasters for the adrenaline rush.
This guy: Checking his 50x leveraged positions on Quant mid-drop.
Be this guy.
bit.ly/3VKPxhE
Oliver retweeted
This strategy looks profitable. But could you handle its biggest drawdown?
Everyone sees the green PnL.
I used @tryquantio AI to look behind it.
Trader `0x024294...2fffa1` on the Traders Leaderboard. Why?
Pure execution machine.
The Performance:
24h snapshot from Quant AI:
+ $410.54K Net PnL
+ 12.74% ROI in 24h
+ $64.35M Volume traded
+ $23.89M Account Value
+ 2.69x turnover rate
The Drawdown The Part People Skip:
I asked Quant AI:
What does this trader’s historical drawdown tell me about its risk?
What should I investigate before considering this strategy?
Honest answer from Quant AI: Max drawdown and full equity curve are NOT available in chat. You have to check the trader profile directly on the app's Leaderboard.
But the current risk is clear: $0 overnight risk, zero liquidation risk right now. That's the pro move.
The Impact - What would this mean for $1,000?
If you mirrored a -12.74% move (same size as his daily gain):
Your $1,000 -> $872.60. You need +14.6% just to get back to breakeven.
If it was a -20% historical drawdown: $1,000 -> $800. Need +25% to recover.
If -30%: $1,000 -> $700. Need +42.86% to recover.
Returns look sexy, but recovery math is brutal.
My Verdict:
Would I accept a 12.7% drawdown? For an aggressive perps scalper with 2-4x effective leverage, it's normal operational variance IF you have strict stops.
For a conservative portfolio?
Absolutely not.
My hard stop is 5%.
Don't just chase ROI.
Check the pain behind the profit.
I checked this inside Quant AI.
You should too.
Want to check yours?
👉 app.tryquant.io/?ref=ST8NM9Q…
@tryquantio #QuantAIPioneers
Oliver retweeted
Hours spent scrolling through wallets.
Only to ape into the wrong move and watch it go the other way.
That’s the old way.
With @tryquantio AI, whale tracking actually makes sense.
Clear signals.
Less noise.
Better context before you follow.
No more full-time investigation just to stay in the game.
Want to check yours?
Visit : app.tryquant.io/?ref=ST8NM9Q…
@tryquantio #QuantAIPioneers
Copy trading used to be a full-time detective job.
Hours of digging through wallets just to ape into the wrong trade. 💀
Anyway, whale tracking is a lot easier with Quant.
bit.ly/3VKPxhE
This strategy looks profitable. But could you handle its biggest drawdown?
Everyone sees the green PnL.
I used @tryquantio AI to look behind it.
Trader `0x024294...2fffa1` on the Traders Leaderboard. Why?
Pure execution machine.
The Performance:
24h snapshot from Quant AI:
+ $410.54K Net PnL
+ 12.74% ROI in 24h
+ $64.35M Volume traded
+ $23.89M Account Value
+ 2.69x turnover rate
The Drawdown The Part People Skip:
I asked Quant AI:
What does this trader’s historical drawdown tell me about its risk?
What should I investigate before considering this strategy?
Honest answer from Quant AI: Max drawdown and full equity curve are NOT available in chat. You have to check the trader profile directly on the app's Leaderboard.
But the current risk is clear: $0 overnight risk, zero liquidation risk right now. That's the pro move.
The Impact - What would this mean for $1,000?
If you mirrored a -12.74% move (same size as his daily gain):
Your $1,000 -> $872.60. You need +14.6% just to get back to breakeven.
If it was a -20% historical drawdown: $1,000 -> $800. Need +25% to recover.
If -30%: $1,000 -> $700. Need +42.86% to recover.
Returns look sexy, but recovery math is brutal.
My Verdict:
Would I accept a 12.7% drawdown? For an aggressive perps scalper with 2-4x effective leverage, it's normal operational variance IF you have strict stops.
For a conservative portfolio?
Absolutely not.
My hard stop is 5%.
Don't just chase ROI.
Check the pain behind the profit.
I checked this inside Quant AI.
You should too.
Want to check yours?
👉 app.tryquant.io/?ref=ST8NM9Q…
@tryquantio #QuantAIPioneers
Hours spent scrolling through wallets.
Only to ape into the wrong move and watch it go the other way.
That’s the old way.
With @tryquantio AI, whale tracking actually makes sense.
Clear signals.
Less noise.
Better context before you follow.
No more full-time investigation just to stay in the game.
Want to check yours?
Visit : app.tryquant.io/?ref=ST8NM9Q…
@tryquantio #QuantAIPioneers
Copy trading used to be a full-time detective job.
Hours of digging through wallets just to ape into the wrong trade. 💀
Anyway, whale tracking is a lot easier with Quant.
bit.ly/3VKPxhE
Oliver retweeted
Copy trading used to be a full-time detective job.
Hours of digging through wallets just to ape into the wrong trade. 💀
Anyway, whale tracking is a lot easier with Quant.
bit.ly/3VKPxhE