Dekos
2.6K posts
Dekos
@PolyDekos
@Polymarket researcher | @zscdao member |
Katılım Mart 2023
322 Takip Edilen679 Takipçiler
@PolyDekos @Polymarket Is this a sign that I’ll be rich from copy trading?
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Dekos retweetledi
I've finally found the perfect option for copy trading - 99% WIN RATE
$752,005 in total revenue. 25,574 forecasts. No interruptions since January 2025 on @Polymarket
No panic. No speculative markets. No big bets.
99% Win Rate. 25,574 deals. This isn't a fluke - it's a system.
His profile - @sharky6999" target="_blank" rel="nofollow noopener">polymarket.com/@sharky6999
For copying, I recommend using Fors: app.fors.market
Dekos@PolyDekos
$739 → $1,817,710 betting on NBA spreads This Polymarket trader entered with $739 in November 2025. No complex models, no insider information, no high-profile bets No setbacks. No panic. Just edge by edge. his profile - @gatorr?via=dekos2911" target="_blank" rel="nofollow noopener">polymarket.com/@gatorr?via=de…
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@0xwhrrari @polyboostxyz It's everyone's dream to sleep and have money dripping into your wallet, cool
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I asked Claude to build me a trading AI agent
It now makes 60-second trades on its own while I sleep
$200 → $2,800 on 1-minute markets alone
@polyboostxyz has Quick Bets
60-second bets on whether an asset goes up or down
BTC, ETH, SOL
Direction, one minute, result
I automated the whole thing
The agent pulls live candle data, runs RSI and momentum checks and if the setup is clean - it enters
No ping, no confirmation, it just trades
Last 3 days:
- BTC dipping at $71,800, momentum flipping. Agent goes UP. 1.50x. Hit
- ETH breaking below support at $2,210. Agent goes DOWN. 1.45x. Hit
- SOL bounce confirmed. Agent re-enters UP. 1.50x. Hit
74 trades, 51 wins, 21 losses
Above 65% hit rate - it prints
It trades at 4 AM when I'm asleep, it doesn't tilt, it doesn't chase, it waits for the next clean setup
Access is FCFS (50 spots)
polyboost.xyz/?ref=rari
And this is just Quick Bets
The main product is parlay stacking - you combine Polymarket events into one express with compounded multipliers
That's where the real money is
Same agent picks those too, scans open markets, finds mispriced events, builds an express
Just stacked 6 events - BTC up, ETH up, +3 more
38.73x multiplier
$99 in → $3,834 if it hits
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@brightdio @stacyonchain It's great that you're helping talented people, I appreciate such actions, well done
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I'm sure you need content kit for your ambassador program
Now you know who is the best in the biz @stacyonchain is here for you
Thank me later
GIF
StacyOnChain@stacyonchain
Most Web3 projects have ambassadors but zero content for them to actually use So everyone posts differently, big moments get lost, and the brand looks fragmented I build content kits that fix this two options: > general kit for the whole community to share > customized content made for each ambassador personally AI video, branded visuals, GIFs, ready-to-post copy your ambassadors just open the folder and post 2 weeks. one folder. starter from $300 Write me and I'll send you the full proposal
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@brightdio @Polymarket I finally found the option that suits me perfectly.
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@PolyDekos @Polymarket That is insane! How is this even possible, a really good one to copy
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While all this quants in the timeline are printing millions with AI, you’re still lost in simulation models and deep research agents.
Don’t worry - I found solution for you. 18k stars on GitHub. Your own financial analyst right in your pocket.
An autonomous financial research agent that thinks, plans, and learns as it works - Dexter.
> 2-command install, 30 seconds to set up
> full Claude skill set + agentic search APIs
> real-time market data straight from financial datasets MCP Server
> text it on WhatsApp for research if u want (financial Jarvis living in your phone)
Just paste GitHub link into ChatGPT/Claude/Grok or any other LLM and it will walk you through the two-click install.
Everything else is handled by Dexter.
It performs analysis using task planning, self-reflection, and real-time market data.
Code is 100% open source and available on GitHub:
github.com/virattt/dexter
Save this post so you don't lose the links.
cvxv666@antpalkin
Chinese quant built a simulation of how SPX price reacts to any global event. He’s already made over $100k - with full blockchain proof. He knows exactly where price will go. More than 40 years of SPX trading history have been loaded into MiroFish simulator (18k stars on GitHub) AI analyzed every single moment in that trading history. Now this guy has a fully functional SPX price prediction system. His wallet: @moisturizer?via=cvxv666" target="_blank" rel="nofollow noopener">polymarket.com/@moisturizer?v…
Dozens of successful SPX price-prediction trades and hundreds of tests across other stock markets. Here’s exactly what you need to replicate his stack: - market data APIs (SPX price, use Alpha Vantage or Quandl) - data pipeline (use Python) - feature engineering (for output signals like RSI, MACD) - seed dataset for MiroFish (convert data into structured context) - multi-agent simulation (macro strategist, earnings analyst, sentiment analyst agents etc.) - probability forecast (run different scenarios) - trading / decision Model (SPX futures ES, SPY ETF) Save this pipeline if you want to run a similar simulation on your own data. You can feed the whole thing to your Claude and build your first (even small) simulation model together. English
@PolyDekos @Polymarket that number draws me in like a magnet
99% damn wins
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His name is bin8888. He integrated his own feed parser directly into his terminal and earned $58,354.54 in 72 hours.
While retail investors were nervous about delays in macroeconomic news, he launched a Rust-based WebSocket parser on the command line to retrieve OPEC+ insider leaks in fractions of a second.
bin8888 set up a lightweight empirical data processing pipeline to detect changes in the probability of oil supply shocks, converting raw geopolitical chatter into pure alpha returns.
When his terminal generated a hidden consensus change signaling stabilization of oil production, he reacted instantly.
bin8888 aggressively attacked the "No" side of Polymarket's March crude oil contracts.
Having abandoned strike prices of $110, $120, and $105, he bought over 240,000 shares for pennies while the market was still pricing in the supply crunch.
His dashboard lit up: position value $156,000, net profit $58,354.54.
If your terminal doesn't read the news before it's published, you're a source of liquidity for the exit.
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@0xWast3 @journoverax @PolymarketTrade Dude made money for a yacht in 90 minutes, this world never ceases to amaze me
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One guy made +$400k in 2 hours on Polymarket yesterday
Bought Yes on Tottenham win vs Atletico (3:2, $6.1M market)
@journoverax writes about Kyle's Lambda for prediction markets
But the same formula explains why lines move before news even drops
Sharp money hits → line shifts on tiny volume
That's not the bookmaker panicking
λ = σ(true value) / 2σ(noise) doing its job
The more informed the bettor, the more price moves per dollar
Same math, different market
Next time a line moves with zero news - that's informed flow
Someone knows something
The order book told you before the journalists did
smoothmove nailed it
Did you make any preds on UCL?
verax@journoverax
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UCL is currently raking in the cash on Polymarket
one trader made **$3.7 million** in just 72 hours
betting on soccer matches alone (Forbes, March 2026)
and this tweet shows the next level
three AI agents work for you 24/7:
- Claude analyzes UCL matches
- Codex writes and fixes the code
- OpenClaw trades on its own
one thinks, one builds, one earns
set up in 5 minutes → first profit that same evening
zostaff@zostaff
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Dekos retweetledi
$162,906.72 in 3 days on Polymarket sports markets
No crypto. No politics. No distractions.
9 predictions. Positions worth $173,900. Largest win: $35,500.
It’s not the number of deals that matters - it’s the quality of each lead.
His profile - @Oliverdjob?via=OsnO" target="_blank" rel="nofollow noopener">polymarket.com/@Oliverdjob?vi…
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$854,000 in 57 days. Just 10 days left until a million.
The bot quietly prints money while everyone else is still clicking buttons manually
The numbers:
$854,695 in profit
$148,800,000 in volume
40,471 trades - ~650 per day
Started with a $48K drawdown - and recouped it all
How does it work?
It bets on Bitcoin’s price movement - up or down
It sees that the crowd estimates a 55% chance of an uptrend, even though the actual probability is 48%
It bets against it. Closes the position. Repeats. 650 times a day
No need to guess where Bitcoin is headed
You just need to know one thing - the crowd has overpaid again
Manual traders lose not because they’re stupid
They lose because they’re slow
Prediction markets reward not diligence - but speed and math
This bot has both
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@MisterNoComents Oh, I totally get where you're coming from—I probably would have seen it the same way...
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> grinding Uber to afford rent
> one night your friend says 'bro just learn to talk to APIs'
> you clown him, then see his screen: 4 terminals, 2 dashboards, 0 effort
> a bunch of AI agents arguing over which options chain is mispriced
> they place tiny bets all night while he sleeps like a baby
> he checks his phone: +$6,730
> you check yours: +1 new ride request 14 minutes away
m|i|ster@MisterNoComents
A Chinese trader known as "gatorr" made $1,934,731.20 on NBA markets by simulating thousands of autonomous AI agents. While researchers use a demo version of MiroFish to test macroeconomic policies, gatorr has turned the repository into an enhanced MiroFish terminal to hack the sports betting market. Here's an alpha version demonstrating how gatorr's tech stack actually works: The enhanced MiroFish terminal is a next-generation AI-powered prediction system powered by multi-agent technology. By extracting information from the real world, the system automatically creates a highly accurate parallel digital world. The real advantage lies in the execution layer of the architecture: 1. Information and Odds Aggregation: The terminal quickly searches for injury information in real time and aggregates underlying odds from various top quantitative AI models. 2. Size and Execution: By matching simulated agent swarm win probabilities with aggregated bookmaker odds, the enhanced MiroFish terminal provides actionable insights and optimizes bet sizing using dynamic Kelly Criterion formulas. Thousands of agents interacting in over 40 simulation rounds on powerful LLM systems creates incredibly aggressive API token burn. When you combine the enormous computational costs with strict liquidity constraints in betting markets that limit bet sizes based on the Kelly Criterion, scaling beyond $2 million becomes a serious bottleneck. The meta has officially changed. If you're not using multi-agent swarm forecasts for your edge device for 2026, you're not trading --> you're just liquidity.
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@MisterNoComents These figures are striking, assuming this trend continues
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@PolyDekos In 3 days I earned as much as an analyst would receive in a year and a half
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