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llm-finance-book
llm-finance-book contiene 15 skills recopiladas de jfimbett, con cobertura ocupacional por repositorio y páginas de detalle dentro del sitio.
Skills en este repositorio
Value a public company's equity end-to-end (FCFE at CAPM cost of equity) with an IB deal team — multi-year EDGAR data, scenario forecasting, Monte-Carlo DCF, dual-source comps, a verification gate, and an investment-committee sign-off. Run `/valuation <cik|ticker>`.
Value a public company end-to-end from its CIK or ticker. Run `/valuation <cik|ticker>`. Orchestrates EDGAR fetch, three parallel valuation lanes (Monte-Carlo DCF, dual-source comparables, qualitative/risk), and reconciliation into a fair-value median + P10–P90, benchmarked against the real market price.
Generate a professional 2-page report on a publicly-traded company as a self-contained HTML website. Given a company name, orchestrates five subagents in order (Generalist, Data Retriever, Data Scientist, Financial Analyst, Report Writer) — pulling the latest 10-K from SEC EDGAR, cleaning the financials, analyzing them, and writing the report. Use when the user asks for a company report, equity write-up, or 10-K-based analysis. Triggers include "write a report on <company>", "company report for <X>", "/company-report".
One sentence on what this command does and when to invoke it. Usage /my-skill "<arg>"
Answer a question about the bundled NovaCorp filings, grounded and graded. Usage /ask "<question>"
Route a research question, gather grounded evidence, and write a cited brief. Usage /brief "<question>"
Run a finance text task through the general and finance-domain classifiers, score both against gold labels, and report which wins and why. Usage /compare
Score the bundled headlines, aggregate them into a daily signal, and write a grounded summary. Usage /sentiment [YYYY-MM-DD]
Screen the bundled transactions for AML red flags and draft a grounded SAR narrative. Usage /screen [--rule <name>]
Explain a credit decision for an applicant and draft a grounded adverse-action notice. Usage /explain <applicant>
Score a bundled model's answers against the gold finance QA set and report honest metrics + calibration. Usage /evaluate [predictions.json]
Extract structured fields from the bundled filing, write a grounded summary, grade it, and save a report. Usage /summarize
Detect and redact PII in the bundled document, then report the privacy/utility tradeoff. Usage /deidentify [path]
Run the end-to-end text-to-signal ML pipeline and save a grounded report. Usage /pipeline
Refine a draft summary until the deterministic target metric is met. Usage /iterate [max_passes]