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Time Series Analysis of AOL Time Warner Shares

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Classical Time Series Decomposition of Historical Prices

Explanation of Times Series Charts:

The red plot on the top chart is the Mean Monthly Closing Price for the company. Linear Trend is plotted in blue. Note that this trend is derived after the seasonal component is removed from the data.

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. The orange Seasonal Component is based on the seasonality of the entire time series, so it is the same from 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 AOL Time Warner. 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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Classical Time Series Analysis of Past 5 Year's Prices



For Subscribers: Hyper Refined Analysis of AOL Time Warner

Refined Stock Trend Analysis for AOL :


Public Pages : More AOL Technical Analysis Chalk-Talk Subjects

AOL Price Forecasts

Momentum Investing

Multi-Spectral Analysis

Political Season Trends AOL

AOL Transaction Volume Trends

AOL Analysis of Short Term and Long Term Risk

AOL Calendar Seasonality

Investor Sentiment

Back to AOL Index Page


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Next Chapter 2:

Risks associated with short and long period price changes can be understood through Volatility Analysis. Here the impact of the Volatility Curve on the potential profitability positions across different time spans is shown.

Go To Chapter II