Stock Exchange: Are The Bots Winning?

The Stock Exchange is all about trading. Each week we do the following:

  • Discuss an important issue for traders;
  • highlight several technical trading methods, including current ideas;
  • feature advice from top traders and writers; and,
  • provide a few (minority) reactions from fundamental analysts.

We also have some fun. We welcome comments, links, and ideas to help us improve this resource for traders. If you have some ideas, please join in!

Review: How Do You React To A Tough Day In The Market?

Our previous Stock Exchange asked the question: How Do You React To A Tough Day In The Market? We noted that emotional reactions can lead to poor trading results, especially after a rough patch in the market. Further, adjusting your mindset to focus on “the fear of making a bad trade” instead of “the fear of missing a big market move” can help you avoid mistakes. Further still, all human traders have emotions, but using a well-defined process can help reduce the chances of making emotional trading mistakes.

This Week: Are the Bots Winning?

It seems artificial intelligence and algorithms are rapidly evolving into all walks of life, ranging from self-driving vehicles, to internet news, to investing and trading, and everything in between. But the big question is: Are the “Bots” Winning?

Just last week, the CFA Institute put out an excellent article titled: You May Beat an Algorithm Today. What about Tomorrow? And according to the article, technology will absolutely upend the way investment decisions are made, and (according to the article) the real question is how will you respond? It’s worth a read.

And of course, not all machine learning decisions are good ones. For example, did you ever read “I Robot” by Isaac Asimov? (Or at least watch the movie adaptation by Will Smith?).

It involves artificial intelligence robots that were believed to be programmed perfectly, only to later discover a fundamental flaw that threatened the entire human race (at least that’s my recollection of the Will Smith movie). From a psychological standpoint, here is more information about: Why Bad Things Happen to Good Decisions.

And interestingly, there are specific publicly-traded companies that are rapidly developing security systems to battle and defeat the malicious activities of Internet bots. For example, Akamai Technologies (AKAM) is one such company that we will cover later in this report.

And of course, we will also review a few of the technical trading picks from our own non-human trading models later in this report, but first here is a look at the performance of our trading models.

Model Performance:

Per reader feedback, we’re continuing to share the performance of our trading models, as shown in the following table:

We find that blending a trend-following / momentum model (Athena) with a mean reversion / dip-buying model (Holmes) provides two strategies, effective in their own right, that are not correlated with each other or with the overall market. By combining the two, we can get more diversity, lower risk, and a smoother string of returns.

For more information about our trading models (and their specific trading processes), click through at the bottom of this post for more information. Also, readers are invited to write to main at newarc dot com for our free, brief description of how we created the Stock Exchange models.

Expert Picks From The Models:

This week’s Stock Exchange is being edited by Blue Harbinger; (Blue Harbinger is a source for independent investment ideas).

Holmes: This week I bought shares of Akamai Technologies (AKAM). Have you ever heard of this company?

Blue Harbinger: Yes, Holmes—we mentioned it earlier in this report (as an example of a company that is battling nefarious Internet bots). It does a lot more too, but before we get into that, why don’t you give our readers a brief idea of how you select your stocks each week.

Holmes: I am a technical trading model designed to keep investors active in the market while protecting from wild swings. Much like the famous detective, I take a wide range of information and use it to draw conclusions others cannot see. For example, I use a mix of advanced trading techniques (including profit taking, stops, and trailing stops) and technical analysis to avoid significant drawdowns. Perhaps my most identifying characteristic is my ability to identify attractive dip-buying opportunities, such as Akamai Technologies, as you can see in the following chart.

BH: Very interesting, Holmes. Personally, I am a long-term fundamental investor, but I also pay attention to short-term technicals, and I actually agree with you on this dip-buying setup. What is your typical holding period?

Holmes: I typically hold my positions for only about 6-weeks.

BH: Well then I do like this short-term trade (even though I personally only invest for the longer-term, and good fundamentals are required). However, here is what I like about your trade. First of all, the reason these shares sold off (i.e. the dip that has you salivating, you Pavlovian hound) is due to a downward revision to guidance by management at AKAM’s most recent analyst day near the end of June. What’s more, this company has a history of beating earnings expectations, and they are expected to announce earnings again within less than your typical 6-week holding period. So yes, I can see these shares popping upward at the next earnings announcement (especially considering they raised full year guidance, even though they lowered Q2 guidance). And from a purely technicals standpoint, this looks like a good trade.

However, from a fundamentals standpoint, I am only luke-warm on this company for the long-term because I don’t think its total addressable market (TAM) is big enough, considering AKAM is already up to $2.6 billion in annual sales, and it’s growing, but just not fast enough for my taste.

A large TAM is one of the three important things to look for when assessing a growth stock, although AKAM is sort of a combination between growth and value because they are trying to be an innovative leader to generate growth, but they’re also working hard to achieve improved operating margin goals, which is more of a value play, in general. I think this is a decent long-term investment (not my absolute favorite), and it also looks like a smart short-term (6-week) technicals trade (although I personally never invest on technicals alone).

Holmes: Thanks for that overview, but what about the AKAM Bot battle we discussed earlier?

BH: Battling Bots is only one part of AKAM’s business. It falls under “web security” in the TAM graphic above, and here is a look at how AKAM views the Bot Landscape, for your information.

Holmes: That is a lot of information, but all extraneous in my view. I am sticking to my short-term technical trading approach, because it works!

BH: Suit yourself. How about you Felix, any trades this week?

Felix: I sold my shares of Avis Budget Group (CAR) this week for around $32. I originally bought them in February for around $40.

BH: That is very transparent of you to share one of your losers. Remind us all, what is your trading process?

Felix: I am a technical model, and I embrace the most durable and successful trend in trading – momentum. I look for uncrowded trades, and I typically hold for about 66-weeks, on average.

BH: That is interesting, and I am not even going to give you too much flack considering your track record over the last year (as shown in our earlier table) is strong. I will point out that even Avis Budget Group has a relation to artificial intelligence (you know, the “Bots” that are taking over the world). Specifically, Waymo (which has pilot autonomous vehicles on the roads in Phoenix), has a partner that takes care of the less glamorous sides of running a self-driving fleet: the rental car company Avis Budget Group, which owns about 580,000 vehicles and 11,000 locations in 180 countries.

Felix: Interesting. Anyway, this week I also ran the 30 stocks of the Dow Jones through my technical model, and the top 20 rankings are listed below.

BH: I like these rankings—thank you. An how about you, Oscar—any trades this week?

Oscar: This week I ran the High Liquidity ETFs with price-volume multiple over 100 million through my model, and the top 20 rankings are listed below.

BH: Thanks, Oscar. I recognize you are also a momentum trader, you typically hold for 6-weeks, and then you rotate into a new sector or ETF. How about you, Athena—any trades this week?

Athena: This week I bought Chipotle (CMG).

BH: It seems like everyone is a burrito expert these days, Athena. But before you explain this trade, why don’t you share a little information on your trading process, please.

Athena: I combine two successful trading methods: momentum and rotation. The rotation occurs each week, when I re-evaluate the entire universe (my universe is roughly 750 stocks). My strategy is reminiscent of the kids’ game called King of the Mountain. No more than ten stocks can be the “winners” each week, and all the others are contenders. Surprisingly, this does not create high turnover. The strongest stocks have a lot of staying power. However, my typical holding period is about 17-weeks.

BH: Thanks for that Athena—very helpful. As for Chipotle, from a fundamental standpoint, it’s been a “broken growth” story. Chipotle was growing like wildfire, opening new stores left and right, with a large total addressable market, until that whole e.coli out break hit almost three years ago. If I recall, they had multiple multi-store food related illnesses and outbreaks that totally crushed this growth story as it crushed everyone’s appetite for burritos. Arguably, things are back on track now (heck, I even had a delicious Chipotle burrito this week). This company has been doing a lot to grow its comps (multiple food lines, online ordering, delivery), and who knows—maybe Chipotle is back for good this time. Here is a look at the fundamental Fast Graph.

Athena: Thanks for that story, but I am an objective trading model, and I’ll be out of this trade before the long-term fundamental story play out.


Whether it is battling evil Internet Bots, managing self-driving vehicles, using artificial intelligence to improve your food order line, or using algorithms and trading models to buy and sell stocks, the “Bots” are rapidly becoming a more prevalent part of the world. But do you think they are winning? And whether you love or hate the robots, you’re going to have to deal with them. In fact, the better you learn to work with the bots, the better you may be able to pick your investments and your trades.

Background On The Stock Exchange:

Each week, Felix and Oscar host a poker game for some of their friends. Since they are all traders, they love to discuss their best current ideas before the game starts. They like to call this their “Stock Exchange.” (Check out Background on the Stock Exchange for more background). Their methods are excellent, as you know if you have been following the series. Since the time frames and risk profiles differ, so do the stock ideas. You get to be a fly on the wall from my report. I am usually the only human present and the only one using any fundamental analysis.

The result? Several expert ideas each week from traders, and a brief comment on the fundamentals from the human investor. The models are named to make it easy to remember their trading personalities.

Stock Exchange Character Guide:

Character Universe Style Average Holding Period Exit Method Risk Control
Felix NewArc Stocks Momentum 66 weeks Price target Macro and stops
Oscar “Empirical” Sectors Momentum Six weeks Rotation Stops
Athena NewArc Stocks Momentum 17 weeks Price target Stops
Holmes NewArc Stocks Dip-buying Mean reversion Six weeks Price target Macro and stops
RoadRunner NewArc Stocks Stocks at bottom of rising range Four weeks Time Time
Jeff Everything Value Long term Risk signals Recession risk, financial stress, Macro

Getting Updates:

Readers are welcome to suggest individual stocks and/or ETFs to be added to our model lists. We keep a running list of all securities our readers recommend, and we share the results within this weekly “Stock Exchange” series when feasible. Send your ideas to “etf at newarc dot com.” Also, we will share additional information about the models, including test data, with those interested in investing. Suggestions and comments about this weekly “Stock Exchange” report are welcome.

Trade Alongside Jeff Miller: Learn More.

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  • Ian Jobling July 8, 2018  

    This article poses an interesting question and then fails to address it. Given that technical analysis in all its forms uses price, it is entirely quantifiable, and computers ought to be better at everything quantifiable than humans. They should be able to see patterns more quickly and precisely than humans can and also to see patterns that our eyes cannot. Therefore, if there is anything in technical analysis (and I’m not convinced there is), all the gains ought to belong to whoever has the best computers. So anyone who is trying to sell his technical approach to me has to first explain to me why he can beat the data centers used by many funds, and you’re not doing that.

    • oldprof July 8, 2018  

      Ian — Our methods do not succeed by speed alone, although improved computers helped greatly with the testing. We’ll send you something explaining our model development process. It is the conception, the testing, and careful implementation that creates an advantage.

      And of course, we are not providing investment advice. These are ideas worth considering in the context of your own methods. We are also not selling a system, since we trade the models better than than would a buyer of the system.

      People who become clients often include one or more of the models — if it fits their needs and risk profile. The number of readers is more than 100 times my number of clients.

      But mostly, speed is less important than system.

      Thanks for the question, which perhaps others have as well.


      • Ian Jobling July 10, 2018  

        I haven’t gotten anything from you and will read it when I do. I wasn’t just saying that computers were faster than humans at trading and pattern recognition, but that they would seem to be better at the whole range of activities involved in building a system. For example, you cite testing as one of your advantages, but surely computers can do any kind of test more quickly and effectively than humans can. If humans are to win, a trading methodology must involve some type of human judgment that isn’t easily quantified, but as far as I can see finding patterns in price data involves no such judgment.