Dividend Investing Analysis

In my previous article I gave an introduction to my investing strategy, more specifically around:

• gathering the stock market data using R

• manipulate this data to build a consolidated dataset

• use several indicators in order to pick a model portfolio

That’s a relatively good starting point, but no number of financial or value metrics give the complete picture. There are qualitative variables, such as the actual business these companies are in, growth potential or moat that also provide relevant information before making a purchase decision.

This aspect represents a significant challenge from a data analytics perspective: setting up any measurement layer on top of these qualitative variables by definition is going to be biased, plus will require significant maintenance to keep it current. It would undoubtedly be a nice solution to put in place (many stock advisory firms do so, at a price) but the purpose of this project is not yet to create a fully autonomous system. The goal is to streamline the decision-making process, providing investors with the necessary tools to make a more efficient use of their time.

What’s the next step then? In this article I'm going to introduce the qualitative analysis that I usually do. Due to the extent of this topic it would be too large to discuss in just one article so I'll begin by introducing the business cycle, and then I'll explain how my investigation process starts. In a following second article I'll elaborate a little bit more into this investigation phase and provide some other useful resources.

There is not any specific R piece covering this at the moment however. I've got a work stream planned to incorporate some of this information into the R program but that will require some web scraping development I do not have ready yet.

Getting the data

Our starting point is the model portfolio that I just generated with the Dividend Investing in R program. This model portfolio, at the time of the writing, looks like:

Now we’re going to leave data and analytics a little bit behind and focus on other information we can drop into the mix. In this article we’re going to cover:

• the business cycle (source: Fidelity website )

• begin our analysis process with Simply Wall St

The business cycle

Let’s start by the basics, which is getting the idea of the business cycle:

In summary, the fluctuation of the economy can be explained in four main phases. This doesn't mean that each cycle will last for a fixed amount of time nor it means that phases can't repeat or skip in some cases. However, based on historical patterns this reflects the general behaviour of the business cycle and therefore it's an important piece for investors that base their strategy on value. We'll use this information to form an idea of what sectors we may want to allocate more resources to at any given moment. I recommend reading Fidelity’s complete report here.

Personally, since May-June my focus has been on Financials, Real Estate, Industrials and Communication Services. My reasoning for this selection was:

• I invest for the long term so I like to focus on sectors that seem undervalued compared to historical P/E averages, and specially sectors with prospects to grow during the next phase of the business cycle

• Financials and Real Estate are sectors I understand and I like researching. Growth REITs could be a good asset long term as due to the massive quantitative easing policies taken by central banks (particularly in USA and Europe) I think there are chances that inflation will ramp up during the recovery phase

• Industrials are probably going to take some time to get back to 2019 levels of economic activity, but the sellout at the beginning of 2020 has caused some great companies to become good value investing opportunities

• Communication Services are more of a short term safer choice as this sector generally has lower volatility and also high yield. I'm also convinced telecommunications will keep growing in the digital era and particularly with the implementation of 5G technologies

This reasoning is just my own and certainly other people will have different perception about future prospects. It is though still early in the economic phase to forecast how much is left from it, and the end of furloughs in the following months may lead to major unemployment—which could be the true beginning of this recession. Still, this article is more about the process rather than the actual outcome, so investors are encouraged to do their own analysis and take their own decisions.

Research in Simply Wall St.

Simply Wall St. is an excellent website that provides a lot of useful information about many publicly traded companies. The free version only allows to read 10 full reports each month so we need to be very selective before clicking any specific ticker/company. In order to do so it's necessary to register – if you do intensive research the Investor plan might be even something to consider too.

Simply Wall St. uses a snowflake-type rating system based on 5 different metrics:

• Value

• Past performance

• Future performance

• Financial health

• Dividend

You can read in detail about how they compile these metrics here. 

My recommendation is to create a portfolio, let’s name it “Candidates”, and add all the stocks we have in our model portfolio. Adding stocks to a list can be done for free so you’ll be able to see the different ratings of company before deciding to get the full detail report.

This overview is already very informative. We can see most stocks have high scores in Dividend (as expected) and a relatively good score on Value and Financial Health (our R program had several rules that selected good value companies with relatively good financial results).

From this list we can focus on higher rated stocks on the metrics that give more value to our previous data-based analysis: Future Performance would be more important on dividend growth picks and I'd probably select high rated cases on Dividend for high yield picks.

In the end we want to reduce our selection a little bit more so what we could also do is discard the lower rated cases (in this picture for example I would take out LOW, PPG, SNA, CWW, NSP and LIN).

Then we can go ahead and read the complete report for our preferred choices in order to understand better their current financial situation, the management team and the future growth prospects. We'll use this process to get an idea of what companies fit better into our portfolio, our investing style and our own experience.

This concludes the first part of Dividend Investing Analysis. In the next article I'll explain the rest of the investigation process I usually do, and I'll provide also some other useful resources to complement this process. For R fans, it's worth mentioning that ratings from Simply Wall St could probably be scraped having an Investor plan, as I think it's required to access the stock's details page to be able to pick each value.

AMC

Disclosure: I am no financial adviser nor an investing professional, and this article reflects my own opinions. I have no business relationship with any of the websites mentioned here nor I receive any compensation from them.