The goal isn’t to provide buy or sell signals, but rather to visualize short-term trends and see how they compare with the actual market movement

Model: The `Kronos-mini` (4M parameters) model is used to autoregressively predict future K-line data.

Data Context: The model uses the last 360 hours (~15 days) of BTC/USDT 1h K-line data from Binance as context for each new prediction.

Probabilistic Forecasting: We employ Monte Carlo sampling (N=30 paths) to generate a distribution of possible future price trajectories, not just a single point forecast.

Derived Insights: The resulting distribution is analyzed to produce the mean forecast (solid line), the uncertainty range (shaded area), and the key probability metrics shown above.