get_filing_language_diff

io.github.quantustik/mcp · Verify this server

Get the "Lazy Prices" 10-K/10-Q language diff for one ticker. Compares the two most recent 10-K (year-over-year, default) or 10-Q (quarter-over-quarter) filings' Risk Factors (Item 1A) and MD&A (Item 7 for 10-K, Item 2 for 10-Q) sections, pre-chewed so you don't have to parse raw filing HTML yourself: a real TF-IDF cosine similarity score between the two extracted section texts, plus the top added/removed sentences from a real sentence-level diff, plus a one-line AI summary grounded strictly in those diffed sentences (`summary_source: "llm"`), or a factual sentence built purely from the computed similarity/counts when no LLM is available (`summary_source: "computed"`) — never fabricated either way. Every result links to BOTH source filings via `filings[].accession_url` — verify anything before acting. Cites a known academic finding: Cohen, Malloy & Nguyen (2020), "Lazy Prices", Journal of Finance — YoY changes in 10-K Risk Factors/MD&A language are historically return-predictive. This is a third-party academic result cited for context, NOT a claim or backtest result of this app. An empty `sections` dict is a valid, honest answer when the ticker has fewer than 2 filings of the requested form on file, or a section couldn't be reliably extracted from both filings (known gap: this extractor targets the common modern EDGAR HTML filing format used by large-cap names; older/non-standard filing formats may not extract). Read-only surfacing: this is information, NOT a buy/sell recommendation, and it does NOT feed the quantum model's conviction/verdict logic — this is a candidate signal still pending backtest validation. Args: ticker: Stock ticker (e.g. "AAPL"). Case-insensitive. form: "10-K" (year-over-year, default) or "10-Q" (quarter-over-quarter). Returns: ticker, form, filings (the two compared filings with accession_url), sections (keyed by "risk_factors"/"mda", each with similarity, added_sentences, removed_sentences, summary, summary_source), generated_at, disclaimer.