Chapter I: Classical Analysis provides a good overview of the data for CACI Intl, and reveals patterns that will be explored with detail in later sections. |
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Explanation of Times Series Charts: The first chart contains the original date, in this case, the monthly average closing prices for CAI over history. Blue marks the de-seasonalized trend, which is a least squares linear regression applied to the CAI prices after seasonal variations have been filtered out. The first step of the classical analysis determines seasonal indexes. The decomposition above bases the seasonality on the ordinary 12 month calendar from one January to the next, but it is also possible to extract interesting results from the 24 or 48 month political election based on November elections, as we shall see shortly. Here the seasonal component is plotted in orange. Because it is based on the seasonality of the entire time series, it is regular from one year to the next. Once the global seasonal is known, it is possible to subtract its influence from the original input to produce so called deseasonalized data. The trend line in the top chart comes about from this processes. Further refinement removes the trend from the deseasonalized data. What remains is the unfiltered cyclical component. Broadly speaking, the refined cyclical data represents the effect of the general business cycle in addition to the private business cycle of CACI Intl. On this chart, the global and private cyclical components are mingled. We will separate them in a later refinement. Purple traces the residual of the process so far. Traditionally this is called the Irregular Component, but this seems to be a poor name since it may exhibit a great deal of regularity. It represents the variations that have not been explained by the refinement process up to this step. One of the more interesting series to be derived in this manner is the red trace on the bottom chart. The residue that is left when all components other than Seasonal and Un-Explained are filtered away, shows how the strongly regular Seasonal effects actually change from one year to the next. When a seasonal pattern becomes well know, the market may anticipate, causing the date of the seasonal peak to occur earlier. This component show how that anticipation moves over time, unlike the static pattern in the second chart. While the full history analysis is of enduring interest, it may also be misleading. An issue may have the same name for 20 or more years, but it may be a very different company, and economic fundamentals have surely changed. For this reason, we want to look at patterns established in more recent times. |
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Refined Stock Trend Analysis for CAI : |
| Friday, March 12, 2010: We have news on ConAgra Foods, Inc., ticker symbol CAG. Signs of an over-bought condition have become noticable. Also, there are breaking events concerning Texas Instruments Incorporated and Convergys Corporation. From the News Archive: (3/11/2010 ) A favorable event happened at Amgen, Inc.. Meanwhile, bad news came from Coach, Inc., Fluor Corporation (NEW), and Automatic Data Processing. |