Our proprietary methodology employs multi-factor
modeling, filters, and fuzzy-logic scoring to
identify stocks that appear poised to outperform or
under-perform the market. The methodology was
developed by an experienced research team led by
David Brown, former NASA scientist.
Using a scientific approach, the team selects from more than 400 factors to create a library of over 100 multi-factor filters. Each filter targets a key area of traditional stock analysis, including value, growth, momentum, fundamentals, earnings, balance sheet, and group strength.
Sabrient uses an adaptive process to test filters on a continual basis to ensure that only the best performing filters are at work. These top filters are used to extract stocks that exhibit the desirable attributes, but have not yet been sufficiently rewarded. A composite scoring system employs a range of high-performing filters to refine the rankings of the extracted stocks, or to simply rank top-to-bottom any given universe of stocks.
Overview of the Process
First, we build and backtest Smart Filters to determine which attributes are drawing a premium in the current market.
Then we use the best Smart Filters to find stocks that exhibit the "right stuff" but have not yet been fully valued by the market.
Each stock is then measured against others in dozens of categories, verified with external sources, and ranked in order of best opportunities for the current market.
This process results in the long-model SmartRank Scorecards, which are segmented by style and cap. A unique weighting feature allows asset managers to customize the Sabrient rankings on these scorecards to reflect their styles and objectives.
The Sabrient rankings are used to rank 9 Russell indices and the Nasdaq 100 index, and they form the basis for the weekly Sabrient Ratings Reports with their Buy/Hold/Sell ratings on more than 5,800 stocks.
The Smart Filters are also used to create customized portfolio strategies for our institutional clients.