I have developed an application that predicts the price movements of Solana (SOL) against the US Dollar (USD) using a combination of technical analysis and sentiment analysis. The model uses logistic regression to classify whether prices are likely to rise or fall.

Key Features:

  • Relative Strength Index (RSI)
  • Moving Average Convergence Divergence (MACD)
  • Bollinger Bands
  • Extracts sentiment scores from news headlines to assess market mood

Application Workflow:

  • Generates synthetic price data
  • Calculates technical indicators from the data
  • Incorporates sentiment scores derived from headlines
  • Trains a logistic regression model to classify price movement
  • Evaluates model accuracy
  • Visualizes buy/sell signals with corresponding sentiment data