This paper proposes a hybrid reinforcement learning trading framework integrating intraday market data with transformer-based financial sentiment signals.
The system extracts sentiment dynamics and semantic event clusters from financial news and incorporates them into a PPO-based trading agent.
Experiments on intraday NSE data demonstrate improved risk-adjusted returns compared to price-only baselines.