Artificial intelligence that learns to make the best decisions based on signals

I need a fully automated trading robot designed to generate consistent profits while strictly controlling risk and minimizing losses. The robot should use a combination of strategies, including trend-following, scalping, and price action, and must be able to adapt to different market conditions such as trending and ranging markets. It should analyze the market using indicators like Moving Averages, RSI, MACD, and

1. IF price forms: - Higher highs + higher lows → TREND = BUY - Lower highs + lower lows → TREND = SELL ELSE → NO TRADE 2. IF: - Trend = BUY - Price retraces to support zone - Bullish engulfing candle forms - TDI green crosses above red (optional) THEN: - Execute BUY 3. IF: - Trend = SELL - Price retraces to resistance - Bearish engulfing forms - TDI confirms THEN: - Execute SELL 4. Risk per trade = 1% of account Lot

Project Overview ​I am looking for a high-level Algorithmic Trader / Developer to build a sophisticated, fully automated scalping system for the Nasdaq-100 Future (NQ) . The system must integrate institutional order flow logic with market structure analysis. ​The core logic must be written in Python , acting as a central hub that bridges ATAS (as the primary data source for Order Flow) and MetaTrader 5 (as the

have the Beatrix Inventor Expert Advisor (EA) that was profitable in the past but has been losing money recently. I need an experienced EA developer/optimizer to study the trade history (especially Stop Loss hits, drawdown periods, SL/TP behavior, win/loss ratio, etc.) and recommend + implement specific tweaks so it becomes consistently profitable again. Your job: 1. Deep analysis of why the EA is no longer