The Next AMZN, AAPL, Etc.


Aug 15

Now, historically I have did a minimal of actual stock investing. However, I have decided that I should have some investments separate from my trading work as an additional way to win.

I wanted to look at what some of the biggest gaining names had in common, and how one might have identified and captured them.

In my 5 minutes of analysis, I identified the following:

  1. IPO date is important. It makes sense that the gains are greater when you buy in earlier.
  2. Momentum and price are important. You cannot get to $500 without going thru $100, $200, $300, first. You want a strong trend.
  3. On point #2, it can hurt if you are too early because it makes it less likely you are to hold long enough to see the big returns. So, you want to be “early” but not “too early”. IPO date and trend analysis thus are the strongest factors
  4. Many of the big name stocks or entities are essentially “market place” plays. Many companies may do well and provide great products and services: but, may not have the structure or business-model to become the next AMZN or AAPL.

Out of all the stocks I analyzed, I found one stock that had a good match to the “factors” I identified as relevant. That stock is TTD, The Trade Desk. It would be a great name for a trading company but my understanding is they are an advertising market place.

As such, I have purchased some TTD. One thing to keep in mind is survivor ship bias. I identified some factors that the best growth stocks had in common– but I did not at all the failed stocks which may have had similar qualities.

At any rate, I have decided to pickup some TTD during this market rout with a long term horizon. In order to make this strategy work statistically, it would make sense to periodically scan for new opportunities and invest in them.

Disclaimer: Not a recommendation to buy or sell.

About the Author

The author is passionate about markets. He has developed top ranked futures strategies. His core focus is (1) applying machine learning and developing systematic strategies, and (2) solving the toughest problems of discretionary trading by applying quantitative tools, machine learning, and performance discipline. You can contact the author at