Part1: An Overview of the Analysis
Chapter I:
An introductory chapter looks at the price history of ADP by applying Classical Time Series Analysis. Some of the patterns seen here will prove to be important in further analysis. See ADP Classical Analysis.
Chapter II:
Understanding Price Volatility behaviour is essential to assessing the risk associated with positions across different time spans. See Automatic Data Processing Price Volatility.
Chapter III:
Historical Volume Trends are analyzed here, revealing seasonal patterns and the influence of the Business Cycle. See ADP Historical Volume.
Chapter IV:
A look at Traditional Seasonal Analysis of Automatic Data Processing Historical Prices identifies the best and worst months to be invested. See ADP Seasonal Trends.
Chapter V:
Moving Averages of various flavours are popular indicators. Here we test the predictive ability of different averages as applied to prediction of Automatic Data Processing prices. See Running Averages.
Part 2: Analysis
Chapter VI:
Some say that modern analysis began with the successful identification of technical oscillators such as the highly effective Wilder RSI. See Technical Oscillators
Chapter VII:
This chapter takes a view somewhat similar to standard analysis of seasonal trends, but it is based on the 4 year or 2 year Political Calendar rather than the 1 year Standard Calendar. Political Seasons work better than Calendar Seasons for predicting prices of many companies. See Politics and Prices of ADP.
Chapter VIII:
A sophisticated method associates price levels with historical volumes. Such semi-abstract concepts as Support and Resistance may then be defined with mathematical precision. See Volumetric Analysis
Chapter IX:
A view of Momentum Analysis that takes Volume into account as well as Price. See Momentum Investing Indicators.
Chapter X:
Technical Analysis discovers the range of moods of investors toward ADP. See Market Sentiment.
Chapter XI:
This section visualizes mappings based on the number of consecutive price movements in a particular direction. A discussion of the "Monte Carlo Fallacy" and it's relevance to Stock Price Prediction leads to a revisionist method of Price Projection using the Bernoulli Analysis. See Bernoulli Analysis of Automatic Data Processing
Chapter XII:
Japanese Candlesticks have a long history, but continue to be used because some of their best concepts are based on universal Investor Psychology. See Candlestick Analysis.
Chapter XIII:
Ordinary analysis does not show the features of the behavioral history underneath the price volume line. Here multi-spectral analysis brings the hidden features to the surface. See Multi-Spectral Analysis.
Chapter XIV:
The combination of multi-spectral and mult-dimensional analysis of Automatic Data Processing historical trends, yields a rich set of behavioral surfaces. See Price Behavior Surfaces.
Part 3: Synthesis and Projections for the Future
Chapter XVI:
Forecasts are gathered from several sources to predict future price movements. See ADP Price Predictions.
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