All the major US stock exchanges, up to 500 tickers
product_id kscore_sp500_us · 500 stocks · daily refresh · since 2011-12-30 · 5 data columns · API/CSV
curl "https://www.kavout.com/api?product_id=kscore_sp500_us&api_key=YourAPIKey"
symbol / trade_date / field to filter · docs →GET · JSON · CSVThis US K Score was trained for the universe of the top 500 stocks by market capitalization, which is different from the US model that covers a broad set of stocks (roughly 3,800). The value of this predictive equity rating score ranges from 1-to-9. A higher K Score (7-9) assigned to a stock indicates a higher probability of outperformance, whereas a lower K Score (1-3) indicates a lower probability of outperformance. The top 500 stocks cover all the major industry sectors.
Please visit K Score's US full coverage to learn more.
The top 500 US stocks by market capitalization that are on all the major US stock exchanges, including major securities markets such as NYSE, Nasdaq and Dow Jones Industrial.
| Sector | Count | Type | Start date |
|---|---|---|---|
| Financials | 95 | Equities | 2011-12-30 |
| Consumer Discretionary | 78 | Equities | 2011-12-30 |
| Information Technology | 77 | Equities | 2011-12-30 |
| Industrials | 66 | Equities | 2011-12-30 |
| Health Care | 60 | Equities | 2011-12-30 |
| Consumer Staples | 32 | Equities | 2011-12-30 |
| Energy | 29 | Equities | 2011-12-30 |
| Utilities | 28 | Equities | 2011-12-30 |
| Materials | 25 | Equities | 2011-12-30 |
| Telecommunication Services | 4 | Equities | 2011-12-30 |
Harnessing years of historical data and a variety of data sources, Kavout takes in structured and unstructured data including fundamental information, pricing and trading volumes, technical signals, and alternative data, to deliver an actionable and easy-to-use equity rating score from 1 to 9.
The development of K Scores apply the best-of-breed learning algorithms, and encompass methods such as regression, classification, model selection, deep learning and more to produce a rating to rank stocks. Our state-of-the-art machine learning (ML) models identify the intrinsic relationships, uncover the dependency structure and calculates predictive analytics for future performance.
Pairing fundamental research with quantitative analysis, our ML model evaluates over 200 factors and signals. Some factor groups include but are not limited to
On any given day, Kavout processes millions of diverse data sets, and runs models encompassing many traditional and advanced financial engineering methods such as regression, classification, deep learning, and reinforcement learning to produce a predictive rating to rank stocks.