FinGPT has designed a real-time analytics architecture for high-frequency trading, with a streaming processing engine that enables second-level market response. The system integrates Apache Kafka to process real-time ticker data, and with the customized Sliding Window Transformer model, it is able to process news streams of 5,000+ securities in parallel during the U.S. stock market opening hours. Special optimized GPU memory manager makes the memory leakage rate lower than 0.1%/day for long time running, which guarantees the system stability.
During the 2023 Fed interest rate meeting, FinGPT's real-time analytics system successfully captured the change in tone in the policy statement, generating trading signals 11 seconds earlier than the Reuters terminal. Hedge fund testing data shows that the Sharpe ratio of intraday trading strategies using the system has increased by 2.3 times. The websocket interface provided by the platform supports millisecond latency to meet the demanding requirements of quantitative trading.
This answer comes from the articleFinGPT: Open Source Financial Big Language Modeling Platform for Financial Analytics and PredictionThe
