K Score - US - Non Financial

Coverage

K Score covers all the tradable stock equities on the US stock exchanges, including major securities markets such as NYSE, Nasdaq and Dow Jones Industrial.

On average 3,600 to 3,800 tickers are rated and ranked daily on all the trading days. Investors can look at the historic trends of a company, and evaluate the strength of a company relative to their sector.

Below are the top 10 sector coverage for the US stock market.

Top 10 Sectors Count Type Start Date
Information Technology 551 Equities 2011-12-30
Consumer Discretionary 464 Equities 2011-12-30
Industrials 463 Equities 2011-12-30
Health Care 426 Equities 2011-12-30
Energy 249 Equities 2011-12-30
Materials 190 Equities 2011-12-30
Financials 152 Equities 2011-12-30
Consumer Staples 139 Equities 2011-12-30
Utilities 89 Equities 2011-12-30
Telecommunication Services 62 Equities 2011-12-30

Delivery & Access

  1. K Scores are calculated daily for thousands of stocks around the globe.
  2. Data history goes back to January 2012 (available for back testing).
  3. Data is updated on trading days, and available 3-5 hours before the market opens on the next day.
  4. This data is available via API and CSV download.

Data Example

As a data feed, customers can expect to receive K Scores in the following format.

K Score - US - Non Financial

Trade Date Symbol Company Name Country Sector K Score Value Score Growth Score Quality Score Momentum Score
2018-01-31 MSFT MICROSOFT CORP US Information Technology 3 4 3 8 8
2018-01-31 AMZN AMAZON.COM INC US Consumer Discretionary 2 2 9 6 9
2018-01-31 BA BOEING CO US Industrials 5 6 6 6 9
2018-01-31 JNJ JOHNSON & JOHNS US Health Care 4 5 6 9 6
2018-01-31 XOM EXXON MOBIL CRP US Energy 5 7 1 4 6
2018-01-31 PX PRAXAIR INC US Materials 5 4 3 6 6
2018-01-31 GS GOLDMAN SACHS US Financials 2 4 4 2 7
2018-01-31 WMT WALMART INC US Consumer Staples 9 8 4 7 8
2018-01-31 NEE NEXTERA ENERGY US Utilities 5 4 7 4 4
2018-01-31 T AT&T INC US Telecommunication Services 5 8 2 6 2

Contact Sales if you are interested in accessing historic data for back testing.

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