arXiv:2607.14174v1 study extends supervised lexicon-learning to 10-K filings and Item 1A risk-factor sections; trains sentiment scores on return and volatility labels at multiple aggregation levels
Read the original at arxiv.org→arXiv:2607.14174v1 Announce Type: new Abstract: Financial sentiment extraction has largely relied on news text and supervised extraction against return labels alone, leaving 10-K filings -- and volatility, the...
Original headline: "How Much of a 10-K Matters? Aggregation-Dependent Value of Full-Text versus Risk-Factor Sentiment"