Are Apple's Publicity Events Hurting The Stock Price? A Statistical Study

Sep. 08, 2015 12:35 PM ETApple Inc. (AAPL)156 Comments


  • A rumor is in place: Apple stock falls after Apple events.
  • I investigate this rumor with a statistical analysis on the stock.
  • The findings support the theory.


I have now run four such studies at the requests of Seeking Alpha readers. In my study on Intel (INTC), I found that their microchip releases have no effect on their stock price. In my study on Microsoft (MSFT), I found that the earnings reports following the release of a new version of Windows tends to be followed by a falling stock price. Finally, in my analysis on Apple (NASDAQ:AAPL), I found that product releases had no effect on stock price but that the earnings reports following those product releases led to increases in stock price - the opposite result of that found in the MSFT study.

Now, at the request of another reader, I look at whether AAPL's events have any effect on stock price. This is an important question, as according to Seeking Alpha reader Barbara Holbrook, an announcement event is set for September 9th (tomorrow). Apparently a theory is floating around:

Description: D:\seeking alpha\images\apple1.gif

I set out to find evidence (or a lack thereof) for this theory. I decided to run the same type of analysis I ran on Apple before. The idea: To look at the changes in stock price prior and after big Apple events. If those changes proved statistically significant, we might have access to a nice method of positioning ourselves for buying and selling AAPL stock, buying the predictable dips and selling at the predictable peaks.

The Study

I focused on the big Apple events and announcements, such as new product announcements and WWDC events. The list of analyzed events and product announcements follows:

Macworld Expo



The New iPad

WWDC 2013

Apple September Special 2013 Event

Apple October Special 2013 Event

WWDC 2014

Apple September Special 2014 Event

Apple October Special 2014 Event

Apple March Special 2014 Event

WWDC 2015

Though many of these were one-day events or announcements, some lasted several days, giving two types of events. However, the meaning of the events are essentially the same: giving the media access to the new developments of AAPL. Thus, I did not categorize the events according to time.

For each event, I recorded the stock price at the closing times for the day of the event. To include the effect of five-day events ending (i.e., to capture the information included in the final day of the event), I also looked at the stock prices five days after the event, for all events. For the sake of symmetry, I did the same for five days before the event. I used the stock price one month before the event as the beginning of the range for analysis, as it is unlikely to include any information regarding the event or announcement. For (1) the sake of symmetry and (2) to include the information of any post-event developments, I also included the stock price 30 days after the event.

The idea of the study is to see whether the change in the stock after an event exceeds or fails to meet the expected growth of AAPL stock during that time. The so-called "expected growth" is that growth explained by the Capital Asset Pricing Model. This allows us to compare a calculated number to zero for our hypothesis tests.

The hypotheses for this study, as per the request, follow:

H0: AAPL's price change minus the expected price change is equal to zero (i.e., events have no influence on stock price)

H1a: AAPL's price change minus the expected price change is above zero (i.e., events help AAPL stock grow)

H1b: AAPL's price change minus the expected price change is below zero (i.e., events hurt AAPL stock)

I will perform a test on all such time ranges, as it's possible that Apple events might only affect one side of the timeline. For example, anticipation might raise anticipation for the company, attracting more investor. Or possibly, Apple events might consistently go swimmingly, causing a stir post-event, which in turn attracts more investors. The opposite effect is also likely: Apple events might be bombs, as Barbara suggests, causing investors to lose faith and sell or even short AAPL stock. In any case, we will see, with an alpha level of 0.05, whether any of these theories have supporting evidence.

The Results

After running the analysis, I came out with two important pieces of information tied to each period. The first is the p-value, which if under 0.05 suggests a relationship, and the second is the direction of that relationship. If the p-value is under 0.05, the direction of AAPL can be rather accurately predicted for the time period to which it is matched.

The results follow:




1 month before the event



5 days before the event



Day of the event (market close)



5 days after the event



1 month after the event



The Implication

The two interesting results of this analysis are those for the day of the event/announcement and for five days after the announcement. It seems as though Barbara has strong evidence for her theory. AAPL falls during an event and continues to fall after the event. The effect weakens and becomes significant after a month.

We also notice no significant changes in the stock prior to the event. This implies that anticipation for the event (or lack thereof) has little-to-no effects on investors' decisions. So why the drop? I would have expected a rise before a fall, implying anticipation met with disappointment (the vice of hype). But because we saw no anticipation, we must find another explanation for the post-event hype.

As I'm not intimately familiar with Apple as a company, I cannot give any expert opinion here, but I can give an opinion based on my background of psychology: the result could just be a strange manifestation of loss aversion. When novel ideas are announced, they indeed attract interest to those not previously interested in the company. But for those with skin in the game, an announcement of a shift in direction or an innovative product might appear to be too risky for long-time Apple investors. Perhaps they sell the stock to sit on the sidelines, ensuring that the new product or announcement goes as planned before reinvesting in the company. I welcome you to suggest your own theory in the comments section.

Using This Info For Investing In AAPL

We saw the strength of the correlation of a drop in AAPL stock the day of an announcement or event to be as strong as it can get in statistical testing: the actual p-value was a decimal followed by 13 zeros. This strongly implies that the drop in AAPL stock after an event is not random but systematic and predictable.

For long-term holders of AAPL, I suggest selling before AAPL events (such as the one tomorrow), and buying back in the following week or two at the dip.

For swing-traders, buying AAPL after an event will usually get you the stock at a discount. Likewise, shorting before an event when you are already bearish on AAPL could give you one of the best entry points.

For day traders, short AAPL at the bell on an event or announcement date; alternatively, open a short position the night before an event.

For options traders, buying puts before events could pay off. Likewise, it's likely you'll get discounted call options a few days after an event.

Request a Statistical Study

If you would like for me to run a statistical study on a specific aspect of a specific stock, commodity, or market, just request so in the comments section below. Alternatively, message me or email me with your request.

This article was written by

Damon Verial profile picture
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Damon Verial is a statistical analyst who uses his skills to research stocks, options, and investment strategies. In addition, Damon is the writer of Copy My Trades, a trade-alert, subscription-based newsletter, available at his personal website. He is also the writer of Exposing Earnings, an in-depth earnings prediction service here on Seeking Alpha.


Damon makes his living as a gap trader, an earnings trader, and an interday trader. In his free time, he writes for Seeking Alpha, where he focuses on seasonal investing, market timing, and earnings analyses.


Damon has written several successful stock analysis algorithms, including algorithms that can predict gap closure, intraday patterns, and news overreactions. They will soon be publically available for subscribers.


Damon’s undergraduate education was in statistics and mathematics at the University of Washington; his graduate education was in psychology at National Taiwan University. He currently lives in Fukuoka, Japan.

Disclosure: I am/we are long INTC. I wrote this article myself, and it expresses my own opinions. I am not receiving compensation for it (other than from Seeking Alpha). I have no business relationship with any company whose stock is mentioned in this article.

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