Two Tech Stocks and a Utility with Bullish Charts and Tail Upside
Preface
Yesterday, we discussed the foundation of tail analysis, what it means, and how to measure it.
We then took it to the real world, showing how even though AAPL and MSFT essentially mirror each other over the last year with outperformance relative to the S&P 500, that tail analysis explains massive differences in option returns.
Today, we look at charts together with tail analysis.
We will repeat definitions but not discuss option skew today.
Definitions
We start with some definitions so we can move quickly forward to actual trading.
Tail Risk: The risk of an extreme event occurring that could drastically change the value of a portfolio or investment. It's called "tail risk" because this kind of event is often at the tail ends (the far left or far right) of a probability distribution, indicating that these events are unlikely but not impossible.
Kurtosis: A statistical measure that essentially measures the "tailedness" of the probability distribution of a real-valued random variable.
Tail analysis is backward looking.
Bullish Charts and Tail Analysis
Today we will make us of Pattern Finder to algorithmically identify bullish directional charts and then we will layer tail analysis on top of it.
We start with screens in the “Directional Charts” category of Pattern Finder and then look to the “Bullish Charts; 3-yr Charts; Nearest Congestion or Trend” screen specifically.
We start with ticker ESTC and we note that this stock has earnings due out in a day, so any analysis here is meant to be used after the coin flip of earnings.
We let Pattern Finder draw in all the goodies algorithmically to mark up our chart, in this case the 3-year chart.
We take a zoomed in view and overlay in the upper right hand side of the chart.
Pattern Finder is plucking out the rising trend support line (red line), which has been built off of two higher lows; one from a double bottom and the other from a cup with handle.
The 18-month chart shows that ESTC is on the verge of forming a new trend resistance line (green line).
That takes several trading days for the Pattern Finder algorithm to confirm and it will be confirmed or it will be rejected likely based on the earnings report in a day.
Alright, that’s the (1) screening, and (2) chart work.
Now we extend the analysis to layer it with tail analysis to try to increase edge, or identify less edge.
We get a lot of analysis from this simple prompt to our integration with ChatGPT, where we broke the data barrier, infused live running code and real-time data, and then added our own advanced stats packages.
But, today we want to focus on the tails, so focus on the parts that are boxed in green for both the 3.5-year and 1-year comparison to the S&P 500.
We see that the “kurtosis of outperformance” is larger than the “kurtosis of underperformance,” and the automatic report that our AI wrote reads this:
This means that there are more frequent extreme positive comparative returns (also known as 'fat tails') compared to negative returns for ESTC than SPY.
In other words, the potential for unusually large daily outperformance returns is higher than large daily underperformance returns.
This type of tail behavior is the opposite of “normal” behavior, where the axiom that the market (and individual stocks) tend to move down faster and in larger amounts than when it moves up, which is usually characterized as small upside tails but realized for longer periods (bull markets last longer than bear markets, but bear markets move more quickly).
So, now we have Pattern Finder identifying a stock with more room to the next upside target than the downside, and a stock with a history of larger upside tail moves than downside.
That’s the agreement between the chart and the realized tail.
With earnings upon us, it’s reasonable for a swing trader to let the day come and go and then reassess.
Next we turn to a tech stock with essentially the same set-up from the same Pattern Finder screen, with similar unusually positive tail behavior, but that has already reported earnings.
This leads us to ticker CFLT. Here is the 3-yearchart with the zoomed in portion in the upper right hand corner:
We see a loooong congestion line (pink line) that was acing as resistance, and CFLT has broken through.
Much like the prior chart we looked at with ESTC, we see that the Pattern Finder algorithm has a breakout over trend resistance (green line) and may well redraw that if CFLT digests this recent move.
The downside target zone is anywhere from 5.7% lower to 10% lower than that, and could be used as stops.
Now we turn to tail analysis to see if we get agreement between the screen, the chart, and the tails.
In this case we will share the actual daily returns comparison chart and have the relevant data overlaid on the chart - this is also automatically drawn and labeled; we haven’t done anything other than save a chart and paste it.
This functionality will be in Pattern Finder soon - call it three weeks.
Note the overperformance kurtosis versus the underperformance kurtosis:
If you back up a little and try to get a bird’s eye view of the chart, you can actually see that the green bars (daily outperformance bars) do show larger extreme moves than the red bars (daily underperformance bars) - that’s the kurtosis we are computing.
So, there you have it - another chart which has a bullish directional tilt since the upside target zone is larger than the downside target zone with a stock through resistance, and… we see bullish tail behavior.
For our last chart and tail analysis, we’ll go away from tech and turn to a utility with ticker CEG.
Constellation Energy Corp. engages in the generation, supply, and marketing of clean energy electricity, and renewable energy products and solutions.
Here is the 18-month chart, as the data only goes back about that long.
We see rising trend support (red line) on a series of higher lows and a stock near a recent top but rising.
Finally the tail analysis and chart:
And here is a snippet from the automatic report written by our AI:
In this case CEG , when compared to SPY , has both larger upside kurtosis versus downside kurtosis (15.51 vs 4.1) but also larger absolute upside skew than downside skew on a daily comparison to SPY (3.07 vs -1.96 ).
This means that there are more frequent extreme positive comparative returns (also known as 'fat tails') compared to negative returns for CEG than SPY .
In other words, the potential for unusually large daily outperformance returns is higher.
OK, that’s it for today.
Conclusion
We hope this was instructive and thank you for reading.
We just released our integration of real-time financial and statistical data into ChatGPT.
A scannable and more advanced version of this analysis, and a lot more, is coming to our three products in the next several weeks (not quite, yet!).
CML Pro is a stock and economic research platform. We’ll put a pin in that product for this post since it is not charting or option related.
TradeMachine is our option backtester. It’s been available since 2015 and tens of thousands of option traders have used it as their secret weapon.
Pattern Finder is our newest product - it is an advanced stock chart platform with our algorithms drawn on top, along with a remarkably robust screener and fundamental analysis data.
The products are going to improve - slowly, and then all at once.
The prices are going to go up too.
But the price for members that join before we integrate our vast libraries of AI over the coming weeks, months, and years, that are in development, like this tail analysis report turned into scannable data, will not go up.
You can learn more about each product in the links below.
Learn about Pattern Finder here.
Learn about TradeMachine here.
Thanks for reading, friends.
The author is long ESTC and CFLT stock as of this writing.
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