K Score - China A-Share

Performance Showcase

To test the performance of the K Score, we constructed two portfolios – Top Picks and Bottom Picks. The Top Picks portfolio is comprised of stocks on the CSI 800 index that are assigned with a K Score of 9, while the Bottom Picks portfolio have stocks in K Score of 1.

Cumulative Return of Portfolios (2013-01-04 to 2020-07-01)

Statistics CAGR Alpha Volatility Beta Sharpe
Top Picks 20.66% 14.25% 23.26% 0.83 0.93
CSI 300 8.53% 0.00% 23.60% 1.00 0.46
Bottom Picks -4.26% -9.59% 27.24% 1.02 -0.02


K Score is a predictive equity rating powered by machine learning (ML) technologies. Kavout takes in vast and diverse datasets including fundamentals, pricing, technical indicators, and alternative data, and then uses a combination of statistical analysis and ML techniques with ranking algorithms to deliver an actionable equity rating score with values ranging 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 in the next month.

China Stock Market at a Glance

The China A-share stock market has two exchanges – Shanghai stock exchange (SSE) and Shenzhen stock exchange (SZSE). The SSE and the SZSE are the world’s 5th largest and 8th largest stock market by market capitalization respectively.

The most important Indices in China A-share are CSI 300, CSI 500 and CSI 800.

CSI 300 Index consists of the 300 largest and most liquid A-share stocks, similar to the largest 500 stocks by market cap in the US.

CSI 500 Index consists of the largest remaining 500 A-Share stocks after excluding the CSI 300 Index, similar to the largest 2,000 US stocks by market cap. CSI 500 Index reflects the overall performance of small-mid cap A-shares.

CSI 800 Index consists of all the constituents of the CSI 300 Index and CSI 500 Index, similar to the largest 3,000 US stocks by market cap.

Data Highlights

  1. For quantitative users, overlay K Score as a signal in investment models.
  2. Generate new equity long/short ideas that weren't on your radar before, or validate research as a screening parameter.
  3. Mitigate risk in portfolio construction by avoiding stocks with low K scores (1-3).