Monday, May 04, 2015

Return expectations for Twitter $TWTR #notgood

There’s a new social media button: UnLike. Twitter’s stock (TWTR) might be the first click. It’s tumble last week erased much of the first quarter goodwill the market had buffed up, closing at $37.84 on Friday and leaving behind the previous $50 support level in splinters. With any market response of this profile there are hails of panic, as well as resolve. Does an investor see this correction as the beginning of an even nastier fall or an opportunity to take advantage of nervous Nellies?

Technical analysis is, by definition, the study of price and trading activity. It seeks to answer the basic question posed in any market - Do I buy, or do I sell? - by interpreting past market action and prognosticating about future market action. Sometimes the market characteristics of a particular stock (or any trading instrument) are not that distinguishable or distinguishing. And then there are stocks with market activity that is much more categorically defined. Hello, Twitter!

Stock Trends allows us to isolate market characteristics - and especially so when there is a selloff. The 25.5% drop of TWTR last week flushed out many investors, and the usually high volume of trading indicator tells us the scope of this sentiment change is substantial. When we see a change to a Stock Trends Weak Bullish indicator () on this kind of price and volume move the technical aspects of the stock are quite distinguishable.

TWTR’s Stock Trends Report shows a combination of indicators that make this event categorically interesting: the trend indicator is Weak Bullish (), with a minor trend counter of 1, and a major trend counter now at 6, an RSI of 95 - , and an unusually high volume indicator (). The market characteristic described by this Stock Trends indicator combination is of a stock that is relatively early in a Bullish trend but has tripped rather suddenly on significant bad market news. While the drop in price was substantial last week, TWTR is still only underperforming the S&P 500 by 5% measured over the past 13-weeks.

The Stock Trends Inference Model (STIM) analysis is designed to make a statistical evaluation of market conditions - especially those market conditions that are most clearly defined. The Stock Trends Report on TWTR is now a good example. What does the STIM analysis say now about this stock’s future price expectations? Remember that the STIM analysis samples 30-years of Stock Trends data looking for stocks with similar indicator combinations, measuring post-observation statistics of 4-week, 13-week, and 40-week returns. From the samples we infer population parameters of these returns and estimate the probability of the current stock (here TWTR) bettering the estimated future returns of a randomly selected stock.

Here is the current STIM analysis of TWTR:

STIM - returns expectations for Twitter TWTR

What does this analysis tell us? First, we see that the short-term price expectations are relatively neutral, with the mean return expectations near the expected return of a randomly selected stock (0%). There is a 51% probability that the 4-week return of TWTR will be positive (greater than 0%, the expected return of a broad market randomly selected stock). Not much better than the 50% probability that you would see a positive 4-week return in a randomly selected stock.
However, the 13-week and 40-week expected returns of TWTR are much more concerning. The probability of TWTR having a 13-week return better than the expected 13-week return of a randomly selected stock (2.19%) is only 45.2%. Looking further out on the time horizon is even more bleak. The probability of TWTR having a 40-week return greater than the expected 40-week return of a randomly selected stock (6.45%) is just 28.8%. Remember, a randomly selected stock has a 50% probability of having a 40-week return greater than 6.45%.

The STIM analysis tell us that TWTR, as defined by the current Stock Trends indicator combination, has a significantly low probability of delivering positive returns over the intermediate time periods ahead.

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