- Adam Graham, a civil engineer, has been trading stocks on the side since 2001.
- He uses a scanner with eight filters to identify stocks with strong fundamentals.
- His strategy led him to bet on Nvidia in 2016.
Adam Graham is a civil engineer in Georgia who has been trading stocks since 2001. He works as a project manager at Terracon, an engineering firm. While on the job site, he occasionally pulls out his phone and buys shares from companies he believes are set to change the world.
It all started when he was in college. He took a course in engineering economics analysis. The professor, who was also a stock trader, told him about a book called "How I Made $2,000,000 in the Stock Market" by Nicolas Darvas ." Since then, Graham has been hooked on the idea of making money through stocks.
"I went to school for engineering design, and when you design a project, or you're planning a project, you want to see if it's economically viable, is it going to make a profit, and if you build this apartment complex, how much profit you get, your construction costs and how much you can charge for rent," Graham said.
Essentially, it was all about how much money can you make from a project. That understanding trickled into how profits impact stocks and their shareholders.
So, he began trading in 2001 but had no idea what he was doing. The book wasn't exactly a step-by-step textbook guide. He started jumping into stocks but didn't understand technical analysis or enough of the fundamentals.
In 2003, he signed up for Investor's Business Daily, a stock research platform, and read "The Successful Investor" by William O'Neil. He began to learn about key variables impacting stock prices. It took him about 15 years, or until 2016, to get it right, but his persistence wouldn't let him give up.
"I wasn't going to let it beat me. I really saw it as an opportunity to really get ahead in life, and I really enjoyed it because I am kind of a technical person as an engineer," Graham said. "When you lose money in the stock market, you're paying tuition. You're paying to learn."
He had re-read Darvas's book and learned a few things he had missed before. One was that the author was looking for stocks that stirred the imagination of the future. This meant new technology that a company was providing and using to increase its revenue as a result. In the past, these would have been things such as the internet. Today, it's AI, he said. The author was also looking for corresponding stocks within that category that had a sharp price increase, making new highs on big volume, he said.
Understanding key fundamentals and looking for new technology led him to bet on Nvidia as early as 2016. He noticed that the company was a key provider of chips for data centers. At that time, he was unaware of AI but knew that chips powered data centers. He purchased 200 shares of NVDA when it was still trading below $15.
Detecting companies with strong fundamentals that are also betting on leading technologies doesn't take him very long. He resorts to using filters from IBD's MarketSurge trading deck. He combines a few fundamentals with proprietary scoring systems developed by IBD.
He sets up a scanner based on eight layers of filters that take him 15 minutes to review the night before he plans to trade. If the scanner pulls up stocks that fit the fundamental criteria, he asks himself if they are growth-based innovative companies. If he finds a stock that fits his criteria, he buys it from his phone while on the job site the next day. This strategy doesn't mean he's constantly buying and selling stocks, but rather, he finds one or two names that fit the bill and trades them three or four times a year, he said.
Filtering stocks
He begins with stocks that increased their earnings per share (EPS) by at least 20% from the previous quarter. IBD's recommendation is a minimum of 25%, but that makes it too restrictive.
He also filters for stocks that reported 20% or more sales growth from the last quarter. IBD recommends a minimum of 25% increase, but he loosened it slightly because it would filter out too many stocks.
The next layer filters for stocks with price increases on the day that are up by more than 1%. He chose this because it indicates a relevant enough move in the price.
He then includes the relative strength rating (RS rating). This is an IBD proprietary scoring system that measures a stock's trailing 52-week performance relative to the broad market, with "1" being the worst and "99" being the best. He sets it to 80, which means the stock outperformed 80% of US-traded names. IBD recommends 80 or higher.
He includes a filter for earnings per share (EPS) and sets it above 60. This is a company's net income, minus its dividend payments, divided by the weighted average of outstanding shares to determine how much a company is earning relative to outstanding shares. IBD recommends 80, but reducing it allows for more stocks to show up for him to review.
He includes the composite rating and sets it above 80. This refers to an IBD proprietary scale — with "1" being worst and "99" being best — that combines IBD's "SmartSelect Ratings" to come up with a final score. The variables include EPS, RS Rating, industry group RS rating, sales and profit margins, and ROE (SMR) Rating, accumulation divided by distribution rating. It puts more weight on the EPS and relative strength rating. IBD recommends 95 or higher, but he loosened it to see more stocks.
He includes return on equity (ROE) and sets it above 17%. This is an indicator of how profitable a company is relative to investments from its shareholders. IBD recommends 15% to 17%.
He includes an earnings-per-share estimate for the current year (EPS Est Cur Yr %) and sets it above 25% because he has noticed that stocks that have good gains tend to be above this range.
Graham has used this filter for years and told Business Insider that the set up he used in 2016 is similar to what he uses today, with slight variations for the thresholds depending on how many stocks show up at any given time. This approach enabled him to spot Nvidia's potential as early as 2016.