Conducting Valuation Analysis Using Daloopa’s Stock Price Data
Valuation analysis that combines fundamentals with market prices requires pulling data from two places. Analysts running price-based multiples through Daloopa had the financials covered, but stock prices still came from a separate source: a data provider, a web search, or a second API call. That means an extra step, an extra dependency, and data you did not verify. But now, daily open, high, low, close, and volume (OHLCV) stock price data is available directly in Daloopa’s API and MCP, for 2,700+ companies, synced daily.
Any prompt that requires a valuation ratio now triggers a stock price tool call alongside the fundamentals pull. The tool accepts multiple companies in a single call and batches all required dates together automatically, so a multi-company, multi-quarter comparison resolves in one call rather than many.
Valuation Workflows
Whether you are calculating P/E, EV/EBITDA, price to book, or building a DCF, these valuation analyses require both financial data and a current or historical stock price. Stock price data in Daloopa means those calculations now resolve in one place, whether you are running a natural language prompt or using Daloopa Skills that depend on market data.
Comparable company tables and comp sheets are one of the most common analyses in equity research, and every column requires a stock price. Market cap, enterprise value, and every price-based multiple now resolve in one Daloopa query alongside the underlying financials. For sell-side analysts building the standard comp sheet, this is fully automated.
Equity value and net debt calculations require price per share to calculate market cap. Previously that was a separate lookup; now it comes through the same Daloopa call alongside the balance sheet data needed to complete the calculation.
Historical P/E and multiple tracking are where historical prices add the most value. Tracking whether a P/E expanded or compressed over time, and what the fundamentals looked like when it did, requires both historical prices and reported financials in the same place. Pull them together in a single Daloopa query, and the calculation runs period by period.
Price and revenue momentum analysis can now run alongside fundamentals in the same query. Tracking how stock price momentum compares to revenue momentum across a coverage list or peer group no longer requires a separate data source.
Workflows that mix historical prices with reported financials, such as tracking how a multiple compressed or expanded over several quarters, follow the same pattern. Pull the fundamentals and the OHLCV data together, and the calculation runs in a single pass.
Key Benefits
1. Verified Prices from a Single Platform
Stock prices come from Daloopa directly, not from a web search or a third-party scrape. Every price in your analysis traces back to a verified, structured source you can trust alongside your fundamentals.
2. Multiples Without the Manual Step
Ratios that require both financial data and market prices, such as P/E, EV/EBITDA, and price to book, now resolve entirely within a single Daloopa query. No separate data source to configure, no values to reconcile across APIs.
3. Multi-Company Comparisons in One Call
The tool batches multiple tickers and date ranges in a single request. A sector comparison across five companies covering eight quarters is one call. For analysts building comp tables or working through earnings season, that efficiency compounds quickly.
4. Market Data Skills That Run Without Interruption
Daloopa Skills that depend on stock prices now pull directly from the MCP tool rather than an external source. The workflows run end to end without leaving the platform.
See the full API documentation to get started, or access stock price data today in any LLM connected to Daloopa via our MCP.
