$IOST /USDT (1h timeframe on Binance). Here's a quick technical interpretation and a basic neural network-based trade setup idea.

Current Price Summary (1H Chart)

Current Price (C): 0.906

High: 0.912

Low: 0.893

MA 7 Close: Missing (assumed near 0.906)

MA 25 Close: ~0.800

MA 99 Close: ~0.736

Price is currently above all key moving averages, indicating a short-term uptrend.

You can build a simple neural network model (e.g., LSTM) to forecast the next 1–3 candlesticks on the 1H chart. Based on that, you can create a trade trigger like this:

1. INPUT FEATURES

Feed these features into your model:

Close prices (last 50 hours)

MA 7, MA 25, MA 99

Volume (1,200 now)

RSI, MACD (optional for added context)

2. MODEL OUTPUT

Let the model predict the next closing price (or price direction). If prediction > current price by X%, take a long trade.

3. STRATEGY EXAMPLE (If Model Forecasts >0.920 in 2h)

Entry: 0.906

TP1: 0.920 (1.5%)

TP2: 0.935 (3%)

SL: 0.890 (−1.7%)

4. Confirmation with MA Setup

Since price > MA 25 and MA 99, trend bias is bullish.

Look for pullbacks near MA 25 (0.800) to add with lower risk.

Would you like a sample Python code for this LSTM-based trade setup using Keras/TensorFlow?

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