Health Care – Kai Enhanced Sector Portfolio (Monthly Rebalance)

Jun 11, 2019 | Portfolio Models and Optimization

Earlier this year we introduced the Kai-ESP, a portfolio that gives full sector exposure and concentrates on the stocks with the highest potential. We built the portfolio based on established trading strategies but augmented with AI signals. Our system dynamically rebalances and optimizes holdings, with the help of machine learning techniques, to seek maximum risk-adjusted returns.

Stocks are selected based on K Scores – stock ratings that are rooted in fundamental rule-based factor investing, and enhanced using machine learning ranking methodology. Stocks ratings take into consideration new information and are updated daily. To seek maximum risk-adjusted returns the portfolio strategy is rebalanced and asset allocation is optimized for both holdings and weights.

This quantamental approach works across sectors and allows us to capture the best growth cycle of any sector.
In this example, we decided to again build a health care portfolio, but with new parameters. In this scenario we used only K Scores of 9, and rebalances every month. This differs from our last portfolio as previously we applied Risk Balanced Allocation, rebalanced weekly, and other elements. We maintained our comparison to XLV, a health care sector ETF.

The average holding in our portfolio over this period was 13 companies. Below are the top holdings and their proportions:

AmerisourceBergen Corporation5.12
Boston Scientific Corporation4.81
Cardinal Health, Inc.4.61
HCA Healthcare Inc4.33
Abbott Laboratories3.43
Edwards Lifesciences Corporation3.28

By looking at the graph below, we see that the Kai-ESP over time has outperformed the XLV ETF.

If you want to see the full-fact sheet with our latest data, please click the button below.

We had so much fun looking into Health Care, we plan to do more sectors. Watch our blog as we release them, and to learn more about Kavout’s other portfolio offerings, please visit our model portfolio page.

Contact us to learn more about how you can incorporate Machine Learning technology into your portfolio construction practice.

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