As the information age ushered in new technologies in the mid 1940s, it transformed the economic order of the post-industrial revolution. Traditional manufacturing evolved because electromechanics made nearly every operation run at scale more efficiently. That evolution accelerated, as if on steroids, when electromechanical digital computers pushed process efficiency higher than had been possible before.
The Data Age of Investment
The data age, which began roughly at the beginning of the 21st century, has had a similar, yet exponential effect on manufacturing. The Internet of Things (IoT) can synchronise disparate component processes across factory floors, even when they are geographically separated, to further enhance productivity.
Now, think about your investment selection process in a similar vein. Before your personal computer was connected to the internet, investment research was the exclusive domain of Wall Street, namely the big wirehouse brokerage firms and white-shoe investment banks like Goldman Sachs. You had to be a client to get access to their insight, which was typically reserved for their largest institutional clients. The individual investor, especially the self-directed do-it-yourselfer, never had a fair chance.
Today, the internet gives you the ability to link your computer to every investment chatroom from South Florida to South Russia. The investment insight you glean from these sites may just be scams pitched by dubious promoters or the groupthink that morphs hairbrained concepts into reasonably sounding ideas. Artificial intelligence (AI) makes both of these risks hard to identify, but AI has also helped to level the playing field for the individual investor. However, there’s a catch.
Individual investors have to be serious about building long-term wealth. If you have made the decision to go it on your own, without the help of an advisor, take solace in the fact that you have access to every bit of data and information processing that professional investors do. But you need a plan.
Investment Strategy
First, make sure your investment strategy aligns with your long-term consumption goals. Then, try to align specific investment themes with that long-term outlook. Sort investment candidates into the industries and then sectors that match your long-term outlook. This is the case whether you take a top-down approach or a bottom-up approach.
Top-down investing focuses on macroeconomic factors such as GDP growth, inflation, and interest rates in an attempt to identify the industries and sectors that could perform well, regardless of whether your outlook is positive or negative. A bottom-up approach almost ignores short-term macroeconomic forces and relies almost exclusively on good, old-fashioned fundamental securities analysis.
Once you have these pieces in place, it’s time to screen for investment candidates and then begin your research. Most stock screeners deliver the same information. This is the case for most brokerage platforms and subscription-based research services. All the data comes from company regulatory filings. This means that most stock screening applications (online or mobile) are merely aggregating information that is already in the public domain.
For example, earnings per share (EPS), gross margin (GM), earnings before interest and taxes (EBIT), earnings before interest, taxes, depreciation, and amortization (EBITDA). Nearly every screener can sort by these attributes and produce tables, but few are designed to identify meaningful trends in that data or give you the ability to perform side-by-side comparisons. Figuratively, they show you all the trees, heck, all the leaves or needles too. The only thing missing is what all that stuff says about the broader forest. What’s worse is that they rarely offer functionality to compare one tree to the others.
Tracking the Trends
Most stock screening tools are devoid of their own proprietary methodology that helps you cut through the noise by identifying meaningful trends. Because of this, investment research remains the exclusive domain of what is now digital Wall Street. They don’t offer individual investors anything that can help them demystify the markets. This is not to suggest that all stock screening tools are alike. Some do provide meaningful trend analysis to help take the guesswork out of investing and to demystify the markets. It’s a short list, so they are relatively easy to find.
The primary attribute you should look for in a stock screening tool is its use of a proprietary methodology that both identifies and quantifies (produces a score for) trends. For example, a stock screener running on an internal engine focused on earnings would explain to you the momentum of a company’s earnings, up or down. You could then use that EPS momentum score to sort for companies with the highest growth rates.
This isn’t to suggest that you should seek out screeners that exclude data from the public domain. That’s not realistic. The raw data is what it is. It is the input from which a proprietary scoring system may be created, so a screener that can sort by things like market cap as well as its own internal metrics offers a huge bonus.
Look for screeners that take otherwise routine, publicly available information and analyze it to produce meaningful insights that go beyond the basic numbers. For example, the term post-earnings announcement drift is common on Wall Street. It explains the sometimes anomalous price movements a stock makes after the underlying company reports quarterly results.
In Conclusion
Being able to identify price moves (overreaction, underreaction) is one thing. Producing drift analysis that compares the most recent reaction to past price moves, and then illustrating those moves graphically, can have a huge impact on an individual investor’s success. This is an obscure example of the types of filter categories that should be in a robust stock screener.
This being said, a web- or mobile-based stock screener that can automate the routine and analyse it for you to produce meaningful insights is why investing isn’t just for professionals anymore.
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