General Electric: Get Ready For Abnormal Upside

Aug. 5.12 | About: General Electric (GE)

Throughout this year, General Electric (GE) has rallied, and at the time of this writing, it is up around 14% for the year. Not only has growth been excellent, but according to statistics, GE may have a strong continued upside in store before year end. Through this report, I will show how statistics and volatility support upward price movement. And I will follow-up with how the future stock returns may unfold through December of this year.

Upside Confidence

The first element we will examine is volatility. Volatility is essentially a measure of risk or uncertainty, so when volatility is rising, uncertainty is rising as well. Through studying volatility, we can qualitatively describe a stock or financial asset as increasing or decreasing in uncertainty or risk. In the chart below, the daily returns for GE for the past 18 months are shown. In order to put the percent price change into perspective, I have included a one-month standard deviation upper and lower boundary to define what is normal.

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The above chart can be confusing at first, but if an investor spends a little time conceptualizing what is going on, the picture will make sense. The middle, gray line is the daily percent change in price. This number fluctuates on a day to day basis with the ebb and flow of capital through GE's stock. The upper green band is two standard deviations of the previous month's price changes, and the red line is the mirror image of the green line. In statistical theory, two standard deviations give the user a 95% confidence in the normality of their results. What this means practically is that as long as the price change is within the two colored bands above, the day's price change was normal. When prices move such that its percent change is outside of the bands, this is an abnormal price move, or something which can give us an idea of changing dynamics within the stock.

The first thing we should note in the chart above is that on occasion prices do change more than what is normal. Typically, this only occurs once every month. Since we have a 95% chance of being confident that our daily percent changes are normal, we have a 5% chance that any given day's price change will be abnormal. With 5% of 20 trading days being abnormal, it is expected that once a month we will have abnormal price movements. With this reasoning firmly in place, we should keep our eyes open for truly abnormal price movements - or periods of time in which several days in a month have moved more than 2 standard deviations. In the above chart, I have marked one of these time periods. In the past two months, GE has experienced 5 unusually strong upward moves. What this tells investors is that there is a statistically unusual buying interest in the stock. This buying interest is verified by the fact that across these past two months, the stock price has surged up around 10%. This is very interesting in that it lets us see that the market has taken a turn for the upside, and unusual moves will more than likely be to the upside.

Historically Speaking

In order to validate this bullish forward-looking analysis, I have completed a study of the price change in GE for the past 50 years. In the study, I examined how stock price has changed from August through each month between now and the end of the year. In the table below, each time period can be examined.

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The first row shows how prices behaved from August to December while the last row shows how prices behaved from August through September. This analysis allows us to examine if any statistical seasonality exists in the stock, so that we can potentially make an informed investment using this information. For example, history tells us that between now and the end of the year, GE has rallied in 74% of all years studied. Additionally, we known that during the years that price rallied, it moved on average 13.2% in these 5 months. A further thing to note is that the likelihood of an increase in stock price decreases as we decrease our holding time. In other words, buying now and holding until the end of the year is the highest probability investment we can make!

Building Confidence

The main message of this historical research is that between now and the end of the year, we stand a strong chance of rallying. This coupled with our previous analysis of an increasing abnormal buying interest in the stock at present shows us that there is a likelihood of further upward movement. There is one more element which draws this research together and that is certainty.

In the first chart I posted, notice the black line I have drawn beneath the graph. I have drawn the trend of the actual width of the standard deviation bands. As the bands widen, larger and larger price swings become normal. When this happens, fear or uncertainty is more and more prevalent in the market. As fear increases, investor confidence decreases. The opposite is true for when the bands draw closer to each other - uncertainty and fear decrease and confidence increases. This is the element which brings the entire analysis together. I have previously argued that abnormal upside moves are becoming more frequent and that historically we are due for a rally. From a statistical perspective, the market is now becoming progressively more confident in this current price direction. What this means is that we may be in for continued upside momentum in the immediate future. I see it as entirely possible that the historic average of 13% plays out and that we end the year with another strong rally.

While I believe that statistically we are in for a strong rally, I believe that we investors can benefit from examining technical analysis to supplement our research. As seen in the chart below, I believe that $18 per share is support for our analysis and a good fail-safe point to exit the investment. I believe we are in an uptrend and this momentum will continue through the rest of the year.

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