Data Sources

Where our financial data comes from and how it is used

Primary Data Sources

Modelvix aggregates financial data from two trusted providers: Finnhub — Our primary data provider for financial statements (income statement, balance sheet, cash flow statement) and real-time market data including stock prices, market capitalization, and trading volume. Finnhub covers over 40,000 publicly traded companies across 90+ global exchanges. Financial Modeling Prep (FMP) — A supplementary source for fundamental financial data including key ratios, historical financial summaries, and industry-specific metrics. FMP helps validate and cross-reference the primary data for greater accuracy.

API Endpoints

Modelvix exposes three core API endpoints that power the dashboard: GET /api/simulate/{ticker} — The primary simulation endpoint. It runs the full analysis pipeline: financial statement import, fundamental data update, daily price refresh, sector-neutral DCF valuation, 10,000-iteration Monte Carlo simulation, and final investment-grade classification. POST /api/simulate/{ticker}/sensitivity — Sensitivity analysis endpoint. Allows users to test how changes in key assumptions (WACC, terminal growth rate, revenue growth) affect the intrinsic value estimate, producing a sensitivity matrix. GET /api/reverse-dcf/{ticker} — Reverse-DCF endpoint. Instead of deriving a value from assumptions, it solves for the market-implied growth rate that justifies the current stock price, enabling comparison between market expectations and actual historical performance.

Update Frequency

Financial data is refreshed on a daily basis. Stock prices are updated each trading day after market close. Fundamental data (financial statements, key ratios) is synchronized whenever new filings become available. To ensure consistent performance and fair comparison across users, all calculation results are cached for 24 hours. This means that repeated analyses of the same ticker within a single day will return the same cached result rather than recomputing from scratch.

Data Limitations

While we strive for accuracy, users should be aware of the following limitations: Data quality depends on the source providers (Finnhub and Financial Modeling Prep). Occasionally, financial statements may be delayed, restated, or missing for certain companies, particularly smaller or international firms. Some companies — especially those recently listed, delisted, or undergoing restructuring — may not have sufficient financial history for a reliable DCF analysis. Modelvix is an analytical tool designed to aid investment research. It is not investment advice. All outputs should be independently verified and used as part of a broader decision-making process.

Transparency

Modelvix is built on a transparent computation model. All DCF, Monte Carlo, and Reverse-DCF calculations are performed server-side using the same methodology for every user. The full source of every assumption — WACC, terminal growth rate, revenue projections, margin estimates — is displayed in the analysis report, and you can adjust each assumption interactively using built-in sliders to see how changes affect the valuation in real time.