Video yükleniyor...

Video Yüklenemedi

Ana Sayfaya Dön

💬 We get asked Should I pause my active strategies when the market suddenly becomes highly volatile? ❕ Answer from a GT App Trader: Usually, high volatility is where manual traders lose the most due to panic. For automated strategies, however, sharp price swings are the best environment to...

35,584 görüntüleme • 3 ay önce •via X (Twitter)

0 Yorum

Yorum bulunmuyor

Orijinal gönderinin yorumları burada görünecek

Benzer Videolar

I built a custom TradingView indicator with Claude Code & Fable 5. It's called the Storm Gauge and is built off a real quant trading strategy. I open-sourced the full code on GitHub. Free to install, free to fork, yours to improve. Here's how to install a quant indicator on your TradingView chart: What it actually is The Storm Gauge is a live implementation of the GARCH model, a Nobel Prize-winning volatility framework that real quant desks run daily. It forecasts how "violent" tomorrow's market could be by combining three inputs: an asset's baseline volatility, yesterday's shock, and where volatility was already sitting before that shock happened. It doesn't predict market direction. Instead, it measures risk, in real time, on your actual chart. How to install it Method 1. Plugin command Open the GitHub repo: Find the installation section, copy the command, and paste it into Claude Code. It runs the plugin install automatically. Method 2. Manual config Open garchmethod.md in the repo, copy the entire file, and paste it into Claude Code. It fetches the skill files directly and verifies the strategy for you. (you only need one method; I'm just showing both) Getting it onto your TradingView chart Inside the repo, there's a Pine Script folder. Open it, copy the entire file. Go into TradingView's Pine Editor, paste it in, hit Enter, and refresh. That's it. The Storm Gauge now runs live on your chart as a real number. Once it's installed, just talk to it: → "What's the volatility forecast on Bitcoin?" → "Explain what the current volatility forecast means on $BTC and how it should impact my position sizing" → "Help me size my S&P500 position according to current market volatility" Does it actually work? I backtested the same EMA cross strategy two ways across 15 years of BTC data. Same entries, same exits. → Fixed position sizing: $17,957 final equity → Storm Gauge (GARCH) sizing: $21,205 final equity Fewer drawdowns, less risk, better result. Full breakdown of the entire build process in my recent article - pinned on my profile.

Miles Deutscher

56,625 görüntüleme • 1 ay önce

This trader reportedly generated $4M in profit trading on Polymarket with ClawdBot Starting with just $1,000, the script scaled up to millions through automated trading If you trade on Polymarket, be sure to read this to simplify your trading with ClawdBot Without any insider connections or 10 years of programming experience, this trader wrote the script and connected Moltbot (Clawdbot) directly to Polymarket Profile → Copy trading → After reviewing the code, it was surprising how simple the core idea looked The bot runs fully autonomously, without constant human involvement Here is the strategy 1. 15-minute BTC & ETH micro-arbitrage The strategy focuses on very short-term Bitcoin and Ethereum markets with 15-minute contracts. In these rapid markets, brief pricing gaps often appear where the combined cost of YES and NO is below $1. A bot connected directly to Polymarket detects and exploits these gaps instantly, it doesn’t try to predict direction or analyze trends, it simply reacts to pricing inefficiencies. 2. Speed over hesitation During volatile moments, human traders often pause or second-guess. An automated system doesn’t. Orders are executed automatically: no hesitation, no emotional bias, no lag in response. By the time a person evaluates the situation, the opportunity usually no longer exists. 3. Automation enables scale The gains per trade are tiny, often just cents. But constant, uninterrupted execution allows the system to repeat the same edge thousands of times without fatigue, turning small margins into meaningful totals over time. Scale becomes the real edge Nearly 6,000 trades were executed. Individually they seemed minor. Collectively they resulted in close to $100K in net profit. Conclusion A quiet bot race already seems to be happening on Polymarket While people debate entries and opinions, automated systems profit from mechanics and speed. As long as structural inefficiencies remain in the market, autonomous setups will likely continue extracting value quietly and consistently. I’m watching this space closely Follow if you want signal, not noise

winkle.

36,652 görüntüleme • 7 ay önce