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Victor Cheng
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I am a semi-active investor who make weekly trades around a core position. My area of interest is technology. I hope to benefit other investors by conveying my personal analyses of equities and unique situations. I have a PhD in biochemistry. My strengths include project management, data... More
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  • How Good Was My Entry Point Into Apple This Year?

    Last week, I published an article that examined the sentiments of authors on the state of Apple Inc (NASDAQ:AAPL). The study encompassed articles published at Seeking Alpha in 2013 that were specifically written about Apple. The results showed that the number of articles written by investors who were long AAPL shares outnumbered those who held a short position. Not surprisingly then, the number of articles written on the company were significantly skewed towards the buy-side.

    Here I will present additional details from that study. Specifically, I have examined the buy-side and sell-side articles and analyzed their possible yield on investment over a 5-, 20, and 60-trading day period from the day of publication. One question of interest is whether there is a technical or statistical advantage in using buy and sell recommendations from Seeking Alpha as entry and exit signals. In relation to this, one request that I have often seen in the comments section is a ranking system of the authors based on some form of performance metric. Whether this idea has merit will also be examined.

    The reader should be aware of several factors that can influence the interpretations in this study:

    • There is often a 1- or 2-day lag between the submission and publication processes at Seeking Alpha.
    • Although AAPL trades with a beta of 0.63 - relatively low for a technology company - intraday price swings can also influence the results of this study to a small degree.
    • I will also admit that it was sometimes difficult to distinguish between a "neutral" stance versus a "buy" stance for some articles where the author was long the stock but was just reporting news. However, I tried to be as consistent as possible.
    • There are authors who periodically write about Apple Inc., not just during optimal buying or selling opportunities.
    • I did not use specific price targets for entry/exit that were mentioned in the articles.
    • For ease of analysis, I also used "maximum return" as a variable instead of "average return". No one can accurately and consistently time market tops and bottoms, and I think either case will present an interesting topic of study.

    Without further adieu, here are the results.

    5-Day performance:

    • Average of max returns from buy recommendations: 2.02%
    • Median of max returns from buy recommendations: 1.69%
    • Average of max returns from sell recommendations: 1.91%
    • Median of max returns from sell recommendations: 1.67%

    20-Day performance:

    • Average of max returns from buy recommendations: 5.78%
    • Median of max returns from buy recommendations: 5.44%
    • Average of max returns from sell recommendations: 4.77%
    • Median of max returns from sell recommendations: 3.09%

    60-Day performance:

    • Average of max returns from buy recommendations: 9.34%
    • Median of max returns from buy recommendations: 7.80%
    • Average of max returns from sell recommendations: 9.39%
    • Median of max returns from sell recommendations: 9.72%

    The current price of Apple is $555, or 3.5% off the 52-week high of $575. Since AAPL performed quite well in 2H 2013, it was really hard to mess up the buy recommendation during the year. Remember, these charts only show maximum potential gain. We could also do the same exercise for maximum potential loss, and the histogram would be shifted toward the negative scale. Regardless, the most important question that we must ask is: Do these histograms represent true performance based on buy/sell recommendations, or is it just a histogram of noise in the variation of AAPL stock price? To answer this question, I repeated the process on the assumption that there was 1 buy recommendation per trading day. What do the histograms look like under this theoretical condition?

    5-Day performance:

    • Theoretical average of max returns from buy recommendations: 1.97%
    • Theoretical median of max returns from buy recommendations: 1.69%

    20-Day performance:

    • Theoretical average of max returns from buy recommendations: 5.62%
    • Theoretical median of max returns from buy recommendations: 5.30%

    60-Day performance:

    • Theoretical average of max returns from buy recommendations: 10.67%
    • Theoretical median of max returns from buy recommendations: 8.83%

    The reference/theoretical histograms look almost identical to the observed histograms, with the exception that the frequency is on different scales! So what does this tell us? It indicates publication of buy-side articles does not equate a buy signal. Based on this one relatively small study, one would do just as well picking a random date to buy AAPL as following a buy recommendation from Seeking Alpha. In fact, you would do better in a 60-day window if you bought on a random date. Now, this does not imply that Seeking Alpha is a waste of time for readers. In contrast, I would argue that Seeking Alpha does a good job of publishing articles that correctly disseminate company news and financials.

    The second variable that I wanted to examine was the publication strength of the author. Readers have often wondered whether authors who have more publications are more likely to be right than those who seldom publish or have a small track record. In order to respect the authors' privacy rights, I must keep this list anonymous. However, we can examine, using the data above, whether there is a correlation between financial performance and the total number of publications. Let's take a look.

    What is apparent is that there is a general bell-shaped distribution that centers at approximately the theoretical and observed means, indicating that there is no correlation between the variables. In other words, a performance system that judges the performance of authors is without merit. For myself personally, I approach each news article objectively, regardless of who the author is, and I highly recommend you to do the same.

    Concluding remarks

    Although some readers would like to have a ranking system of the authors based on their performances, the data strongly suggests there is no correlation between author recommendations and equity performance (in this small sample size). The experience of the authors also does not dictate how accurate the buy/sell recommendations are. Based on the data presented here, readers of Seeking Alpha are strongly recommended to use the news and financial analyses presented as a source of information only, rather than a recommendation to buy or sell specific stocks.

    Disclosure: I have no positions in any stocks mentioned, and no plans to initiate any positions within the next 72 hours. 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.

    Tags: AAPL, long-ideas
    Dec 18 10:49 AM | Link | Comment!
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