The scoring model is a strategy described by a set of investing rules defined by you. Based on that, all companies can be assessed according to these rules and rated with high or low scores by our algorithms. 

Think of it as designing your unique vision, a game plan for your investment process, or an individual approach to finding, analyzing, and selecting companies for your portfolio, but that's the easy part. 

The next step is to evaluate what you've designed.

To make the evaluation process as unbiased and comparable as possible, we need to convert every rule to a number and write it down as a logical expression. 

Only then can every criterion from your strategy receive many points (aka high scoring) when the requirements are met but only a few or even no points when the criteria are barely met or not met at all. Thanks to that, SCRAB can score, filter, sort, and compare thousands of companies in seconds. 

For this reason, to make the most of our system, you must define your rules first. Basically, you need to build your scoring model to help SCRAB better understand what you are looking for and which criteria are essential to you. 

Why is it so important to understand the scoring model idea? 

Because at least one scoring model is used across different tools in SCRAB all the time. If you want to see a particular company's scoring on its profile pageyou have to have some criteria defined first, so we can calculate the proper scoring for you. The same applies to comparing companies, monitoring their scoring changes, and doing backtests.

Although it's possible to work with many tools without having a proper scoring model (i.e., all charts and screener), it's recommended to have one in order to use other tools (such as displaying company profiles, comparing different stocks, monitoring your portfolio, or doing backtests).

After all, automating your analytical job is the most powerful feature we've equipped SCRAB with. 

No worries, though, if you're just a beginner. We have a few pre-configured cutting-edge scoring models that you can use without any analytical knowledge. Bear with us to learn more. 

How does the scoring model work?

Go to the Scoring Model support section to see the detailed practical description of how to set up and configure your individual scoring model. Nevertheless, before diving in, read the very idea and the pure concept explained below. 

Your scoring model can be as simple as this one:

Finding companies with high long-term EPS growth prospects, with low P/E ratios, or both. 

In both cases, you need to define two things:

  1. What do the "high" and "low" mean for you? What is the threshold for growth being "high", at least in your opinion?
  2. How important both criteria are relating to each other? Equally important, or maybe one indicator is more important than the other?

Both definitions can (and should) be number based, for example:

  1. High growth means > 30 percent EPS growth per year on average; and low P/E means < 15
  2. Growth is twice as important as P/E, so if the growth is > 30, then give it 66,66 points (66,66% of the total score available), and if the P/E is < 15, then give it 33,33 points more (33,33% of the total score available).

Now we have a simple scoring model with only two different criteria taken into consideration. If SCRAB finds a company that matches your criteria in full (growth > 30 and P/E < 15), then you will see the total company score equal to 100 points (100% of the total score available). That's our scoring.

Now, suppose one of the parameters is not met, for example, growth is equal only to 28 percent a year, but P/E is still lower than 15. In that case, SCRAB would score such a company slightly lower giving it, for example, only 95% of the total score available. 

By the way, all of these parameters – like points and total scores – are, of course, fully customizable.

Anyway, thanks to that mechanism, you can easily find, score, and compare thousands of different companies in seconds and always keep your scoring model up to date because our algorithms monitor the market daily and update your model on the fly in case something changes in the growth rate or the P/E parameter.

How to build a good scoring model?

In real life a proper scoring model should look for and take into consideration dozens of different essential criteria: under or overvaluation of the stock judged by indicators like P/S or P/E; analysts' sentiment like upside or price target revisions; growth estimates like forecasted revenue, net income, or cash from operations for the next few years; or financial stability like solvency and liquidity ratios, level of debt, operating margin or return on invested capital. 

We have more than 500 essential indicators available to build your scoring model with. Still, the first and most important thing is to define which criteria are crucial to you, so SCRAB can understand them and automatically do its analytical job. 

Refer to this article to learn how to build your first simple scoring model: Building your own scoring model.

Using our pre-configured models

Building an advanced scoring model might be a daunting task for an inexperienced investor, so we've already pre-configured a few scoring models on your account that we think make sense. Thanks to that, you can start working with SCRAB immediately after your account is set up. 

Besides that, you can also copy/clone them and use them as a blueprint for creating your own customized model.

If you want to know more, you can find a detailed description in this article: How to use predefined scoring models.