Investment Signals

TL;DR for operators FinMarBa is a useful reminder that in finance, sentiment is not what a sentence sounds like. Sentiment is what the market does after reading, absorbing, ignoring, overreacting to, or misunderstanding that sentence. Very elegant. Very inconvenient. The paper introduces a 61,252-headline financial sentiment dataset built from Bloomberg Market Wraps covering 2010 to January 2024.1 Instead of asking human annotators whether a headline feels positive, negative, or neutral, the authors use a market-based labelling process: extract headlines, identify relevant tickers with GPT-4, observe the next-day price reaction, compare that reaction with the ticker’s rolling five-year return distribution, and assign a label from that relative move. ...

TL;DR for operators NGAT is useful because it attacks a real modelling mismatch in financial AI: companies do not absorb market information in the same way, yet many graph neural networks treat them as if they do. The paper’s answer is a node-level graph attention layer, where each company learns its own attention mechanism for reading signals from related companies. ...