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After studying a period of quantitative trading robots, feeding them a large amount of technical indicators and current on-chain data, the trading strategy was summarized by an AI agent.
🚨 BTC latest trading strategy: Buy on dip after pullback (originally waiting for trigger, but now it has already fallen).
💡 Core logic: patiently wait for key support zone confirmation, do not chase high blindly, and place orders in batches after right-side signals are established.
📌 Trigger conditions (all are necessary)
Price touch point: pull back to the 79,500 - 80,000 range.
Candlestick pattern: 4H cycle shows a hammer with a long lower shadow or a bullish engulfing, and must not fall below the previous low of 79,188.
Indicator resonance: 1H StochRSI successfully crosses above 20 from the oversold area.
Derivatives data: Funding rate must not turn deeply negative (must stay above -0.02%, indicating that there is no absolute despair among shorts, and market sentiment remains relatively healthy).
Fundamental news: Warsh's first speech has ended, and the market direction response is clear.
⚙️ Execution parameters (Post Only limit order)
🎯 Batch entry: (This entry point must meet all the above requirements)
79,200 (light position 60%)
78,800 (add position 40%)
🛑 Hard stop loss: 78,200 (below the previous low of 78,613 + ATR buffer, to avoid liquidity hunting at round numbers).
💰 Take profit targets (TP)
TP1: 81,500 (close 50%, remaining position at breakeven)
TP2: 82,000 (close 30%, testing the 200-day moving average resistance)
TP3: 82,500 (leave 20% as a tail position, to play the right-side space after breakout)
Currently, developing a Skill linked to the exchange, allowing one-click order placement via Skill, recording local profit and loss, which can be summarized and reviewed later, and gradually adjusting entry indicators. (Based on current situation, we will observe its subsequent trend, do not open market orders directly).
PS: This article mainly shares technical insights and does not constitute investment advice.
#大漠茶馆 #openclaw #AI #Quantitative Trading