Path Parameters
| Name | Type | Example | Description |
|---|---|---|---|
| symbol | string | AAPL | Stock ticker |
Auth
headers: { 'Authorization': 'Replace with your API token' }
Examples
fetch('https://api.gurufocus.com/data/stocks/AAPL/rankings', { method: 'GET', headers: { 'Authorization': 'Replace with your API token' }})
Responses
Successful response. The exact payload fields depend on this endpoint.
Example Body (Field Reference)
{ "basic_information": { "company": "Apple Inc", "company_id": "GF000003JX", "exchange": "NAS", "stockid": "US01WD", "symbol": "AAPL" }, "guru_focus_rankings": { "gf_score": 97, "gf_score_high": 99, "gf_score_low": 82, "gf_score_med": 94, "gf_score_med_5y": 96, "gf_value": 238.84, "gf_value_est": 251.87, "gf_value_est_12m": 260.52, "gf_value_est_2nd": 269.23, "gf_value_est_3rd": 285.39, "gf_value_pct_change": 1.44, "margin_gf_value": -9.2, "p2gf_value": 1.07, "p2gf_value_est": 1.01, "p2gf_value_high": 2.15, "p2gf_value_low": 0.19, "p2gf_value_med": 0.88, "predictability": 4.5, "rank_balancesheet": 6, "rank_balancesheet_high": 8, "rank_balancesheet_low": 6, "rank_balancesheet_med": 7, "rank_gf_value": 7, "rank_gf_value_high": 10, "rank_gf_value_low": 1, "rank_gf_value_med": 6, "rank_growth": 10, "rank_growth_high": 10, "rank_growth_low": 6, "rank_growth_med": 10, "rank_momentum": 10, "rank_momentum_high": 10, "rank_momentum_low": 3, "rank_momentum_med": 8, "rank_profitability": 10, "rank_profitability_high": 10, "rank_profitability_low": 9, "rank_profitability_med": 10 }}
Introduction
The GuruFocus Ranking Dataset provides exclusive access to our proprietary scoring systems, developed over two decades of research and investment expertise. These rankings distill complex financial data into intuitive, investment-grade signals that support screening, model building, and decision-making at scale.
Whether you're building systematic strategies, ranking equities for selection, or creating your own scoring models, this dataset offers the quantitative edge needed to filter for quality and optimize return potential.
What’s Included
Access robust, proprietary rankings covering financial strength, valuation, profitability, and forward-looking performance metrics:
- GF Score (0–100): A composite ranking combining five key dimensions—Value, Growth, Profitability, Financial Strength, and Momentum
- GF Value Rank (1–10): Measures a stock’s valuation based on historical multiples, future estimates, and performance adjustments
- Financial Strength Rank (1–10): Assesses liquidity, leverage, and balance sheet resilience
- Profitability Rank (1–10): Evaluates margin strength, return consistency, and sustainable profit metrics
- Growth Rank (1–10): Tracks both historical and expected revenue/profit growth rates
- Momentum Rank (1–10): Scores near-term price strength relative to long-term trend health
- Predictability Rank (1–5): Gauges consistency and forecast reliability of a company’s earnings
All rankings are updated regularly, stored historically, and normalized for easy integration across models, platforms, or analytics environments.
Data Coverage
| Regions | Total Company Count | Total Stock Count |
|---|---|---|
| USA | 12,000+ | 35,000+ |
| Asia | 27,000+ | 32,000+ |
| Europe | 10,000+ | 47,000+ |
| UK/Ireland | 2,600+ | 12,000+ |
| Canada | 3,500+ | 4,700+ |
| Oceania | 2,400+ | 4,700+ |
| Africa | 1,300+ | 1,500+ |
| Latin America | 2,000+ | 6,500+ |
| India/Pakistan | 5,900+ | 8,100+ |
Use Cases
This dataset’s ideal for:
- Investment platforms - Power recommendation engines and equity rankings
- Fintech developers - Integrate proprietary rankings into screeners and algorithms
- Data teams - Build or backtest scoring-based models
- Institutional analysts - Add quantitative signals to qualitative investment processes
Academic researchers - Explore performance correlations using historical rank data
Extend Your Capabilities
Combine the XYZ Dataset with other GuruFocus data offerings:
- Fundamental Dataset – 20+ years of financial statement history for in-depth analysis
- Guru Trades Dataset – Aggregated buying and selling by top fund managers
- Segment Dataset – Company revenue breakdowns by product and geography
All datasets follow a consistent structure and are accessible through unified API endpoints.