Introductory Remarks by PT

Below we present a recent article by the Mole discussing a number of technical statistics on the behavior of AAPL over time. Since the company has the largest market cap in the US stock market (~ USD 850 billion – a valuation that exceeds that of entire industries), it is the biggest component of capitalization-weighted big cap indexes and the ETFs based on them. It is also a component of the price-weighted DJIA. It is fair to say that the performance of AAPL is not unimportant for the broad market.

 

AAPL, weekly over the past 5 years. The stock has recently hit new highs. In a way this is  quite funny, as it happens just as the company enters maturity; its revenue and earnings growth rates are fated to enter a long term phase of decline from here on out no matter what – this is a mathematical certainty. Many of the darlings of the late 1990s tech bubble eventually faced a similar problem (in early 2000 we patiently explained to a fellow investor why Cisco could not possibly maintain an annual revenue growth rate of 50% for another decade, or even for another few years). This is beside the fact that the company hasn’t introduced any particularly successful innovative products since the iPhone, which remains its biggest revenue generator by far (the times when new generations of the iPhone offered genuine advances in terms of design and technological capability are but a distant memory as well; these days updated versions at best tend to offer a handful of tweaks). We don’t want to detract from the company’s undeniable entrepreneurial success and well-deserved reputation for quality, reliability and cool design. We merely question its current stock market valuation and the sense of timing of those buying the stock here and now. Admittedly, given the market’s effortless climb up the rungs of the greater fools ladder hitherto, recent buyers may well make a profit. We only know that someone will eventually end up holding the proverbial bag. A side note: the blue dotted lines on the chart serve to highlight a typical momentum divergence between RSI and price. The divergence is even more glaring on a daily chart. Sometimes  such divergences turn out not to mean anything, but more often than not they are a short term warning sign worth heeding – click to enlarge.

 

We are not surprised that the long term statistics on AAPL reveal that its performance in September is on average the by far weakest of the entire year. This is in line with the stock market’s overall seasonal patterns (see “The Dangerous Season Begins Now” by Dimitri Speck for the details). It is important to keep in mind that these average data do not mean the stock will always perform badly in September. That is certainly not the case – but the probability that it will perform badly (and the broad market along with it) is fairly high.

Given the current fundamental and technical backdrop this may be particularly important this year. On the fundamental side, we have a sharp decrease in US money supply growth – which is the most important driver of stock prices in a fiat money regime (its effects are subject to a lag, the length of which varies depending on contingent circumstances). Meanwhile, the technical condition of the market looks increasingly dubious. A number of big cap stocks are hitting new highs, but at the same time only 54% of Nasdaq and 61% of NYSE-listed stocks trade above their 200-day moving averages, even after last week’s market rebound.  Indexes have begun to diverge noticeably from each other (e.g. the small cap Russell 2000 has weakened against the SPX all year long, after strengthening against it throughout 2016). There was a recent slew of “Hindenburg omens”, which indicates fraying trend uniformity as well.

It is also noteworthy that realized volatility is extremely low (record low in fact) and implied volatility in options prices has followed suit. The longer such conditions last, the greater the market upheaval tends to be when they end. It is easy to see why: although sellers of volatility have been favored by the trend toward declining volatility so far, they have to sell ever more of it if they want to achieve the same returns. This means they are likely to be at maximum exposure right at the point when their luck finally runs out (the same principle applies to bond buyers using leverage to compensate for extremely low yields). This is certain to exacerbate volatility when it returns.

Without further ado, here is a wealth of statistics on AAPL from the Mole (who picked AAPL for no particular reason, but as far as we are concerned, it was a good choice):

 

Statistical Charts Project – Everything on AAPL

Over the past few days I have been making a lot of progress on my statistical charts project. Today’s milestone was to hook in a python routine to extract data from Yahoo instead of IQ-Feed, as adjusted daily data is more than sufficient for calculating long term statistics – plus of course it is free. The end goal is to integrate the code into a simple web page with a symbol query field on top that accepts all Yahoo Finance symbols. If that works as planned then it will become available around the clock to all my subscribers.

Of course there is still a bit of legwork ahead as I not only will have to set up Django (a python server) but also integrate whatever form I get to work with the rest of the site. So give me a few more weeks but I will keep plugging on this. In the interim I plan on occasionally posting a few stats right here on various symbols of interest. So if you have any particular symbols you are interested in then please make sure to make yourselves heard in the comments section. Yes, the Mole is taking special requests, but don’t overdo it!

Today’s turn is AAPL – for no particular reason and simply because it was my symbol for testing integration of the Yahoo module.

 

Palo Alto Apple Store

Photo credit:Apple

 

Monthly Statistics

Cumulative performance shows pretty pronounced declines in June and September. Good to know if you are holding AAPL today.

 

AAPL, cumulative mean percentage change 1980 – today – click to enlarge.

 

Next: Monthly returns in percentage terms. June and September clearly suck for Apple.

 

AAPL, average monthly percentage change since 1981 – click to enlarge.

 

The same as measured in terms of the monthly Sharpe ratio:

 

AAPL mean monthly Sharpe ratio since 1981 – click to enlarge.

 

Monthly SKEW. Interestingly, October seems to be slightly negatively shifted despite being a high performing month. Apparently there are a few negative outliers in October.

 

AAPL monthly SKEW since 1981. Note: SKEW is a measure of perceived tail risk, calculated from the prices of far-out-of-the-money options. High SKEW shows a steepening of the implied volatility curve, as demand for options insuring against a rising probability of outlier events surges. We should not be surprised that there are October  outliers, as October can occasionally be a brutal month (see 1987, 2008) and SKEW is driven by perceptions. [PT] – click to enlarge.

 

Next: Average monthly performance. I love this chart and who would have guessed that August is one of the best performing months for AAPL?

 

AAPL, average monthly performance since 1981 – click to enlarge.

 

Next, performance quartiles: Crap: September, June, July.  Sideways: March February, May. Good: November, December, April. Best: August, January, October

 

AAPL performance quartiles (best to worst performing three months) – click to enlarge.

 

Percentage of positive months – very interesting and once again September stands out here as the hands-down loser.

 

Percentage of positive performance per month since 1981 – only 36% of all September performances were positive. This is actually very bad (consider that the market as a whole rises approx. 67% of the time in the fiat money regime). [PT] – click to enlarge.

 

Monthly trading ranges of AAPL. Clearly September and October are by far the most volatile months.

 

Average monthly trading ranges: the worst month is also the most volatile one. This fact is not reflected in current option prices. [PT] – click to enlarge.

 

Standard Deviation: January seems to be not only one of the best performing but also one of the most strongly trending months.

 

AAPL, monthly standard deviation since 1981 – click to enlarge.

 

Here is the historical performance for the month of August only. I know it is over, but I didn’t have time to hack the code to spit out next month. Anyway, note how August performance seems to be leveling off since 2000.

 

AAPL, price change in August for every year since 1981. The strong average performance  in the month of August has become a lot less pronounced since 2000 – click to enlarge.

 

And here is the histogram of all August returns. Historically a great month for AAPL – note how the 0 mark is shifted over quite a bit.

 

Distribution of August returns since 1981 – click to enlarge.

 

Weekly Statistics

Weekly performance in percentage terms. Boy oh boy – September really does suck for AAPL:

 

Average weekly return of AAPL since 1981 – click to enlarge.

 

Percentage of weeks of the year generating positive returns since 1981. The end of the year (Christmas shopping season) clearly is the best performing season.

 

Weeks of the year and the percentage of positive returns generated since 1981 – click to enlarge.

 

Weekly trading ranges. If you hold AAPL after mid September strap on your  helmet!

 

Average weekly trading range in AAPL. Note the 8.58% spike in the third week of September. Did we mention that the options aren’t pricing this in? At least not yet… [PT] – click to enlarge.

 

Standard deviation – that is in percentage terms which I should probably have pointed out on the chart.

 

Weekly standard deviation in percent – click to enlarge.

 

Weekly Sharpe Ratio – which is the mean return divided by standard deviation:

 

AAPL weekly Sharpe ratio – click to enlarge.

 

Weekly SKEW – apparently the last week of September is by far the worst:

 

AAPL, weekly average SKEW since 1981. We have to add to this: if the third week of September is the worst performance-wise, it is logical that the fourth week will exhibit the highest SKEW readings, since options SKEW is driven by perceptions of tail risk. So after investors have experienced the worst performing week, they will tend to bid up far ootm options, because they fear a tail risk event may be underway. If one holds options, or is an options writer, this is on average the best time to sell. [PT] – click to enlarge.

 

Histogram for week #35 (which was last week). It has more outliers on the positive end, which accounts for August being a more favorable month.

 

Return distribution of the last week of August – click to enlarge.

 

I hope you all enjoyed perusing this laundry list of statistical charts as much as I enjoyed building them.

 

Conclusion by PT:

Evidently the month of September has a habit of frequently turning into “interesting times” in the Chinese curse sense (and not just for AAPL). Whether it will happen again this year remains to be seen of course, but as we noted in the introduction, this year is certainly pregnant with potential.

Given the complacency  reflected by volatility premiums, positioning data and sentiment surveys, the road is bound to eventually get more rocky, so this is probably a good time to pay attention to data such as those presented above.

 

Charts by: StockCharts, Evil Speculator

 

Intro, conclusion, edits and chart captions by PT

 

The article by the Mole was originally published at the Evil Speculator.

 

 

 

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