FinLLM

In the world of financial AI, where speed meets complexity, most systems are either too slow to adapt or too brittle to interpret the nuanced messiness of real-world finance. Enter FinKario, a new system that combines event-enhanced financial knowledge graphs with a graph-aware retrieval strategy — and outperforms both specialized financial LLMs and institutional strategies in real-world backtests. The Retail Investor’s Dilemma While retail traders drown in information overload, professional research reports contain rich insights — but they’re long, unstructured, and hard to parse. Most LLM-based tools don’t fully exploit these reports. They either extract static attributes (e.g., stock ticker, sector, valuation) or respond to isolated queries without contextual awareness. ...

The idea of merging language models and financial algorithms isn’t new — but HARLF takes it a step further by embedding them in a hierarchical reinforcement learning (HRL) framework that actually delivers. With a stunning 26% annualized ROI and a Sharpe ratio of 1.2, this isn’t just another LLM-meets-finance paper. It’s a blueprint for how sentiment and structure can be synergistically harnessed. From FinBERT to Fortune: Integrating Text with Tickers Most financial LLM pipelines stop at score generation: classify sentiment and call it a signal. But HARLF builds a full sentiment pipeline using FinBERT, generating monthly sentiment scores from scraped Google News articles for each of 14 assets. These scores aren’t just inputs — they form a complete observation vector that includes: ...

General-purpose language models can solve math puzzles and explain Kant, but struggle to identify a ticker or classify earnings tone. What the financial world needs isn’t more reasoning—it’s better reading. Over the past year, large language models (LLMs) have surged into every corner of applied AI, and finance is no exception. But while the promise of “reasoning engines” captivates headlines, the pain point for financial tasks is much simpler—and more niche. ...