Daxiapi Financial ROE Analysis

Problem it addresses

In listed-company financial analysis, the difficult part is not just calculating ROE, but explaining why it is high or low: whether it is driven by net profit margin, total asset turnover, or the equity multiplier. The skill also checks whether net profit is distorted by one-off gains, impairments, or restructuring, and whether operating cash flow supports reported earnings. It treats industry differences as a first-order issue, because banks, manufacturers, consumer companies, tech/pharma firms, and utilities should not be compared using the same generic thresholds.

How it works

The skill first fetches structured financial statement data using daxiapi report finance, and when possible cross-checks key fields against the latest annual or quarterly report PDF from Cninfo, covering operating revenue, net profit attributable to the parent company, ROE, and net operating cash flow. It then identifies the company's industry and selects the relevant framework: consumer, manufacturing, tech/pharma, financial services, or utilities. For financial services, it avoids applying the generic DuPont formula directly.

The core analysis is organized around the DuPont framework: net profit margin, total asset turnover, and equity multiplier. It then evaluates earnings quality, cash-flow quality, net-asset quality, operating efficiency, and leverage risk, while flagging abnormal years and possible financial-statement risks. If inputs needed for WACC, Beta, cost of debt, or related EVA analysis are missing, the skill explicitly skips those conclusions instead of assuming values. The final output is a structured report with an executive summary, key metric tables, data sources, notes on missing fields, and risk disclosures.

Boundaries

This skill is suited for single-company financial-quality analysis, fundamentals interpretation, and financial-statement risk screening. It does not provide deterministic buy/sell recommendations or price predictions. If peer data is unavailable, it does not force industry rankings; if key financial fields are missing, it narrows the scope of conclusions; if data retrieval fails, the user must choose to supply data, continue with available data, or retrieve public sources.