StockFit x InvestDayTip: Daily US Stock Ratings

We are happy to announce StockFit x InvestDayTip. InvestDayTip publishes quantitative ratings for US stocks: every market day it ranks the top 100 and gives each of them a deep-dive page. The company research and the five years of fundamentals on those pages come from the StockFit API, for all 100 tickers, on every run. The site has been in production since October 3, 2026.

InvestDayTip is built by Diego Fernández Domínguez, a StockFit customer who turned a scoring engine into a public product. This post covers what InvestDayTip offers, how its daily stock ratings work, exactly which StockFit endpoints feed it, and why a single developer can run all of it on the Starter plan.

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What InvestDayTip is: daily quantitative stock ratings

The InvestDayTip homepage is a ranked table of US stocks, rebuilt every market day. Each row shows the rank, ticker, sector, price, the 1-day, 1-month and 1-year moves, P/E, dividend yield, RSI, MACD and the InvestDayTip score, plus a label showing how its position changed since the previous run. You can filter, sort and change the level of detail, and the whole site is available in English and Spanish.

Five pillars, one 0 to 100 score

According to the InvestDayTip methodology page, the score is a statistical 0 to 100 rating built from five pillars, each scored 0 to 100 and weighted like this:

Two rules keep it honest. When a data point is unavailable, that pillar scores a neutral 50 instead of a guessed value. And a very low score in a high-impact pillar caps the total at 50, so one great factor cannot hide a broken one. The model is deterministic, there is no manual intervention per ticker, and the ratings are not for sale: nobody can pay to have a security scored, ranked or displayed differently. InvestDayTip is clear that a high score means a company matches the model's factors on that run's date. It is an information service, not a forecast, and not investment advice.

A deep-dive page for every ranked ticker

Click any ticker and you land on its deep-dive, for example the Apple (AAPL) deep-dive. Each page walks from the score down to the business:

• Rank, price, market cap, sector, the 52-week range and the core market data.
• The pillar breakdown: how the ticker scored on Value, Growth, Profitability, Momentum and EPS Revisions.
• A “Why” section with the plain-fact rationale the scoring engine produced.
• Financial health diagnostics: the Piotroski F-Score with all nine checks, and the Altman Z-Score with its zone.
• Risk signals, a deliberate devil's-advocate list of what could go wrong.
• Company research: business overview, market position, key segments, and links to the company and investor-relations sites.
• Five fiscal years of fundamentals: revenue, gross, operating and net margin, FCF to net income, OCF to net income, debt to equity and current ratio.

If the Piotroski and Altman numbers are new to you, our guide to the financial health score API explains both scores and the inputs behind them.

The time machine: replay any past run

The InvestDayTip time machine lets you pick any previous run and see the ranking exactly as it was published, diffed against the run before it: change in position, change in price, and change in score for every ticker. For a ranking site that is the strongest form of transparency there is. Nothing gets quietly rewritten, and you can watch a stock climb or slide through the list day by day.

An open-source engine behind it

The scoring engine is open source under the MIT license on GitHub and installable from PyPI with pip install investdaytip. Beyond what the website shows, the command-line tool scores stocks and ETFs across US, European and Asian markets and a superinvestor-consensus universe, exports self-contained HTML reports, runs per-ticker deep-dives, backtests the model against history, and includes an interactive advisor. The repository documents the full methodology, factor by factor, including the backtest validation behind each model change.

How StockFit powers InvestDayTip

StockFit is a live data source on InvestDayTip, not a demo. Two StockFit feeds run for all 100 ranked tickers on every daily run: the research summary and the fundamental insights. Both are built from SEC EDGAR filings, so the business description and every margin, cash-flow ratio and leverage figure on a deep-dive traces back to a 10-K on SEC EDGAR.

Research summary: company research in one call

/api/company/research-summary returns three things in a single request: the company profile (including a structured business description), an earnings snapshot (margins, ROE and ROIC, free cash flow, growth, financial health scores, next earnings date) and sector-aware key metrics. It replaces three separate API calls, which matters when you are refreshing 100 tickers every day.

curl 'https://api.stockfit.io/api/company/research-summary?symbol=AAPL' \
  -H 'x-api-key: YOUR_KEY'

{
  "profile": {
    "name": "...",
    "description": "## Business Overview ... ## Market Position ... ## Key Segments ...",
    "webUrl": "...",
    "investorRelationsUrl": "..."
  },
  "snapshot": {
    /* grossMargin, operatingMargin, netMargin, roe, roic, freeCashFlow,
       fcfToNetIncome, revenueGrowth, piotroskiFScore, altmanZScore, nextEarningsDate ... */
  },
  "keyMetrics": {
    /* sector-aware metrics: general, sectorMetrics, industryMetrics */
  }
}

On InvestDayTip, the profile becomes the Company research block on each deep-dive: the Business Overview, Market Position and Key Segments sections, plus the company and investor-relations links. The snapshot also backs up the engine's own health diagnostics: when InvestDayTip cannot compute an Altman Z-Score from its own inputs for a ticker, it falls back to the StockFit value, so the risk signals that depend on it never silently disappear.

Fundamental insights: five years of margins, cash quality and leverage

The five-year fundamentals table on every deep-dive comes from three StockFit chart endpoints, called with annual periods:

• /api/financials/chart/revenue-profitability for revenue and gross, operating and net margin.
• /api/earnings/chart/quality for earnings quality: FCF to net income and OCF to net income.
• /api/financials/chart/balance-sheet-health for debt to equity and the current ratio.

All three return the same chart-ready shape: one periods array plus named series (absolute values) and rates (ratios). That uniformity is why the integration stays small. Merging the three into one row per fiscal year takes a dozen lines of Python, roughly the pattern InvestDayTip uses:

import os
import requests

BASE = "https://api.stockfit.io/api"
HEADERS = {"x-api-key": os.environ["STOCKFIT_API_KEY"]}
CHARTS = (
    "financials/chart/revenue-profitability",  # Revenue, Gross/Operating/Net Margin
    "earnings/chart/quality",                  # FCF / Net Income, OCF / Net Income
    "financials/chart/balance-sheet-health",   # Debt to Equity, Current Ratio
)

def five_year_fundamentals(symbol: str) -> dict[str, dict[str, float]]:
    rows: dict[str, dict[str, float]] = {}
    for path in CHARTS:
        chart = requests.get(
            f"{BASE}/{path}",
            params={"symbol": symbol, "period": "annual", "limit": 5},
            headers=HEADERS,
            timeout=25,
        ).json()
        for block in ("series", "rates"):
            for s in chart.get(block, []):
                for period, value in zip(chart["periods"], s["data"]):
                    rows.setdefault(period, {})[s["name"]] = value
    return rows

# rates are decimals: a "Gross Margin" of 0.4691 means 46.91%
fundamentals = five_year_fundamentals("AAPL")

The chart endpoints work on every StockFit plan. Free returns the latest fiscal year, and Starter returns the full five years you see on InvestDayTip, so you can rebuild the same table for your own watchlist.

More StockFit in the open-source engine

The engine goes further than the website. Its deep-dive reads StockFit's revenue and business segmentation footnotes to flag revenue concentration in the risk signals. Its backtester has an opt-in point-in-time mode that uses the SEC filing date StockFit attaches to every fiscal period, so a simulation on a past date only sees statements that had actually been filed by then. That is the look-ahead-bias problem we cover in point-in-time data for backtesting. The integration is also tier-aware: it detects which StockFit plan a key is on, unlocks the features that plan covers, and leaves a section out with a clear note rather than inventing data when it cannot fetch it.

Built on the StockFit Starter plan

InvestDayTip runs on the StockFit Starter plan, and the fit is a good one:

• Research summary is included in Starter. That single endpoint is what fills the Company research block.
• Five years of history on Starter matches the five-fiscal-year fundamentals table exactly.
• A commercial license is included from Starter up, which is what a public website needs.
• 20,000 requests per day at 300 requests per minute. A daily run over 100 tickers takes a few hundred calls, and caching keeps repeat calls down, so there is plenty of headroom.

In Diego's own words, Starter is exactly what made StockFit a live source on InvestDayTip. We love that story: a single developer, a deterministic model, and SEC-sourced fundamentals behind a public product that rebuilds itself every market day.

Why we are excited about this partnership

StockFit and InvestDayTip share a rule: never fabricate a number. InvestDayTip scores a missing data point as neutral instead of guessing, publishes its methodology and code, and keeps every past run replayable. StockFit traces every value back to the SEC filing it came from. A ranking you can audit, built on data you can audit, is exactly the kind of product we built StockFit for.

So go have a look at today's InvestDayTip ranking, open a few deep-dives, and replay a past run in the time machine. And if you are building something of your own, whether a ranking, a screener or an AI research agent like the one in our guide to building a stock research agent with SEC citations, you can get a free StockFit API key and start with the same endpoints InvestDayTip uses.

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