The Next 10, an introduction, part 1

As of writing this, on Tuesday 29th of January 2019, the next 10 companies to invest in are:

These 10 companies were picked by us over the weekend, and made available on Saturday, so this list naturally changes over time. Depending on when you’re reading this, the list might look very different, as we update it each weekend. How different depends on what’s happening in the market and how old this post is.

In this blog post I’ll introduce how to use the list to see how companies we rank place themselves for their near term future outlook.

Picking the next 10 from the list

Now the thing about the list is that it shows all the companies we follow in ranked order, from high to low, by default. The top 10 in that list are companies we assume have become too risky and will not be able to outperform going forward. We therefore go for the next 10, or top 11-20, which represent companies we believe have potential to continue to outperform.

Selecting sections of the list

Clicking on the various selectors allow you to easily pick what part of the list to select. You can also select or deselect individual companies by clicking on them in the list itself. The bar chart just above displays the rank values of the companies in the list below, with those selected showing up as white.

One interesting aspect of the bar chart is the quick summary snapshot it represents, giving you a feel for the distribution of rank values.

Selecting companies changes the top chart which show the ranking values of the selected companies over time. Selecting 5 or less will show you the individual ranking values, while selecting more produces ranking summary statistics instead, to avoid cluttering.

Picking companies from the list

The final thing we’re going to mention about the list is how you can click the first chart to change what date you want to view ranking values for, and how you can lock columns to view multiple together. This can then also be exported to CSV for further analysis.

Changing the list date and exporting to CSV

Individual companies

Now lets change focus to viewing individual companies. We’ll use Netflix as an example.

Netflix indicator example

It should be obvious that the top part of the chart show the stock price, so we’ll focus our attention to the bottom part with the added arrows. We have two elements of interest:

  • The white line represents the rank value of the company
  • The blue band represents the rank range among the top 11-20

When the white line is within the blue rank range, Netflix is part of the top 11-20 in the rank list. This happened during February, March and April 2018. Prior to that the Netflix rank was below the top 11-20 range, and after that period above. You can also view other ranges by selecting these from the selection list, including the bottom rank ranges.

Being below a top 11-20 range means we think there are other companies that will perform better, i.e., those actually in the top 11-20. And being above makes it rank in the top 10, which we think will struggle to continue to outperform. The list dynamics are reversed on the bottom end, where we’d expect the bottom 11-20 to underperform, and the bottom 10 would be what we could call oversold. Selecting one of the bottom ranges then allow you to also compare the rank value against these ranges in addition. We’ll write more about the bottom part of the list in the future, when we look at long/short strategies.

Netflix ranges

For the company stock price performance in isolation, it is a good thing that the company rank value is approaching the top 11-20 range from below. We do not here concern ourselves too much about the absolute value of neither the white rank line nor the blue rank band, but instead focus on the distance between them. This distance and the growing or shrinking of this distance tells us something about their relationship. We’re here primarily focused on the relative performance and ranking of the company, compared to all the other companies we rank, and the market overall.

We’ll end part 1 here. In part 2 we will see what sort of performance characteristics the various rank value produce in our portfolio view.


This blog post was written by Christian, the main portfolio curator here at AgoraOpus. With a background from FinTech, he holds a MSc in Quantitative Finance and a BSc in Computer Science and Industrial Automation.

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