@NoLimitGains Diese Grafik ist eher viral als faktisch. Der IPO-Float lag bei 555.6 Mio. Aktien zu $135 โ ca. 4.25%, nicht 5โ10%. Bis 13. Juni gab es keinen Insider-Unlock. Die Lock-up-Struktur ist formelbasiert, keine simple 25/32/39/46/60%-Leiter. Hype ok, schlechte Mathematik nicht. $SPCX
@NoLimitGains This chart looks viral, not factual. The IPO was 555.6M shares at $135 (~4.25% float). By Jun 13 there was no insider unlock. The lock-up schedule is formula-basedโnot a clean 25/32/39/46/53/60% float ladder. Hype is fine. Bad math isnโt. $SPCX
There are levels to wealth.
โ 60,000,000 millionaires.
3,428 billionaires.
1 trillionaire.
After SpaceXโs IPO, the pyramid of wealth just got a new top.
@Smart_Money DCA ab jetzt starten, mit grรถsseren Betrรคgen, max. 2x, um den Durchschnitt runterzudrรผcken falls es weiter fรคllt โ wovon ich ausgehe. Die traditionellen Mรคrkte sind noch zu weit oben und drรผcken BTC runter, auch wenn die Korrelation eigentlich nicht mehr da ist.
@0xChainMind "Hold = up, break = down" is just describing a support line. And your text says $1,500 but the chart marks $1,705 โ pick a target. One daily close decides a wick, not ETH's macro. The trendline retest is a fair level, though.
@HenrikZeberg RSI divergence + MACD bear-cross are legit. But '$20-30k / top since 2012' ignores this cycle's new bid: spot ETFs + corporate treasuries. A wave-4 ~$66k pullback is reasonable; an 80% collapse is the tail, not the base case. Respect the risk โ don't anchor on it.
Best performing city for AI weather trading: Seoul
P&L: +$94.25
Why? Asian markets have less competition - more inefficiency to exploit
The bot analyzes 10 cities across 3 continents.
Each has different forecast accuracy patterns.
Overall: +$5.32 P&L, 50% WR
How I built a fully autonomous weather trading system
The architecture behind my AI bot that trades temperature markets on Polymarket:
Data Layer:
- 80 ensemble weather models (GFS + ECMWF)
- Scans 10 cities across 3 continents
- Synced to GFS model runs for latency edge
Execution:
- Quarter-Kelly position sizing
- Boundary filters + liquidity checks
- CLOB orderbook depth analysis
- 4 automated cycles/day via GitHub Actions
Self-Learning:
- Bayesian optimization (72 param combos)
- Monte Carlo stress testing (50 runs)
- Versioned configs with approval workflow
Monitoring:
- Live dashboard on Render (7 tabs)
- Telegram alerts after every cycle
- Automated X posts with stats cards
All open source. $500 starting bankroll. Day 15.
#QuantTrading #Polymarket #AlgoTrading #SystemDesign #Python #TradingBot
Day 15 of building an AI weather trading bot on Polymarket
The system scans 10 cities, 4x daily (synced to GFS model runs)
Stats so far:
- Bankroll: $505.32 (started $500)
- P&L: +$5.32
- ROI: +1.1%
- Win Rate: 50% (3W/3L)
- 6 open trades worth $252
Built with 80 ensemble forecasts (GFS + ECMWF), Optuna optimization, Monte Carlo stress testing, and Purged K-Fold CV.
Fully automated. No manual intervention. All open source.