How CoinSight AI Works

CoinSight AI aggregates multiple real-time and historical data streams

Data Collection ✅ Market Data: OHLCV (Open, High, Low, Close, Volume) from exchanges like Binance, Coinbase, and CoinGecko. ✅ On-Chain Metrics: Active addresses, whale transactions, exchange inflows/outflows from providers like Glassnode and Nansen. ✅ Sentiment Signals: AI-powered sentiment scoring from Twitter/X, Reddit, news, and Google Trends. ✅ Macro & Derivatives: USD Index, open interest, and funding rates. Feature Engineering Technical indicators: RSI, MACD, moving averages, volatility measures. On-chain activity levels and liquidity flows. Social sentiment trends and volume changes. Market microstructure features from derivatives data. Prediction Models

CoinSightAI uses a layered approach: Baseline Statistical Models: ARIMA & Prophet for trend detection. Machine Learning: Gradient boosting (XGBoost/LightGBM) for non-linear relationships. Deep Learning: LSTM & Transformer architectures for sequential pattern learning. Ensemble Forecasting: Combines multiple models for stability and accuracy.

✅ Output For each selected cryptocurrency: 30, 60, 90-day point forecast Upper & lower prediction bounds (e.g., 90% confidence range) Directional probability (likelihood of positive or negative return) Top influencing factors in plain language