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CitiGroup Pure Technical Analysis





Part1: An Overview of the Analysis



Chapter I:

The Classical Analysis of Time Series establishes a good starting point in the analysis, and provides a high vantage point for viewing patterns of behaviour in the prices over the entire history of CitiGroup. See C Classical Analysis.

Chapter II:

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. See CitiGroup Price Volatility.

Chapter III:

Historical Volume Trends are analyzed here, revealing seasonal patterns and the influence of the Business Cycle. See C Historical Volume.

Chapter IV:

A look at Traditional Seasonal Analysis of CitiGroup Historical Prices identifies the best and worst months to be invested. See C Seasonal Trends.

Chapter V:

One of the most popular indicators, the Moving Average, comes in many variations. Here we test the predictive ability of different averages as applied to prediction of CitiGroup prices. See Running Averages.




Part 2: Traditional Analysis Topics



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:

A different type of Seasonal Analysis is applied to C historical prices. Here the 24 month, November based Political Calendar is the basis for non-standard Seasonal Analysis. See Politics and Prices of C.

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:

Analysis of Market Momentum as the product of Price and Volume drives an interpretation considerably more sophisticated than those that consider Price Momentum alone. See Momentum Investing Indicators.

Chapter X:

Technical Analysis discovers the range of moods of investors toward C. See Market Sentiment.

Chapter XI:

The length of "Runs", (the number of consecutive price movements up or down) reveal some new ways to visualize Price Series Data. 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 CitiGroup

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:

Multi-spectral analysis reveals behavioral features of C prices that may not be apparent to ordinary analysis. See Multi-Spectral Analysis.

Chapter XIV:

Combining the historical behavior surfaces with the geometry of long standing periodic price oscillations yields a behavior surface of more than three dimensions which has an extremely low residual error compared to other methods of analysis. See Price Behavior Surfaces.




Part 3: Synthesis and Forecasting



Chapter XVI:

Predictions and Forecasts. What will happen to C over the next few months? See C Price Predictions.