Soon after screening for particular fundamentals and/or traits we take the specified sub-universe and place those stocks into our proprietary ranking formula. This formula then looks at each stock and ranks them with regard to growth, fundamentals, quality, and value, they are not equally weighted. It was reverse engineered to be optimized with our buy/sell algorithmic program that is used in the next step.
The GROWTH component looks at Earnings per Share and Sales.
The next component FUNDAMENTALS and QUALITY look at Margins, Turnover, Return on Capital and Finances.
While the last component VALUE looks at Income Stream and Assets.
Each of these sub-components is then broken down into even smaller variables. Henceforth we end up analyzing and ranking over 96 variables. Again these variables are not equally weighted.
We then take each of these rankings and multiply them by a specified weight to achieve an overall score. The sub-universe of stocks is then sorted by lowest score (highest average ranking) to highest score (lowest average ranking).
This formula has shown to be a vital part of RAAMPS’ success as portfolios that are not actively traded but rather bought and held seem to regularly outperform the broader market.