A network with memory decides
An LSTM is a neural network that carries what it saw before: it does not look at the current candle alone, it looks at the sequence. On 15-minute candles it emits a probability that the price will be higher a few candles ahead.
- Above a threshold it buys; below the mirror threshold, it sells. Between the two it does nothing, and that is most of the time.
- The exit is the model changing its mind. It closes when that probability crosses back, not on reaching a fixed target in points.
- The model decides both ends. Entry and exit come out of the same belief; there is no human rule on top correcting its exit.