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ERTS - Effect of Election Cycles on Electronic Arts Inc.

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.


Election Cycle Trends in ERTS Common Stock.



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Presidential Election History of Electronic Arts Inc.

Two theories compete as to the influence of the President's political party on stock prices. One camp holds that the market reacts very to the choice of president, possibly even before election day when the outcome is forseen. Others believe the new president does not begin to materially influence the market until he has been in office for some time.



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ERTS:  Profitability by Presidential Party

Monthly Appreciation is calculated as the percentage change between the mean price of each month compared to the preceding month. Price Periods are assigned to Political Parties three different ways for this calculation.




Best Times in the Election Cycle For Short Term Speculation in Electronic Arts Inc. Common Stock.







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Election Calendar Cycles of Electronic Arts Inc.

You may have seen charts that profile seasonal trends. This is similar, but it is based on the political calendar. The short (Congressional) cycle is 24 months long.






More Political Cycles of Electronic Arts Inc.?

Political Financials with the Influence of Congressional Elections on ERTS. Also, roadmap and Summary of most effective indicators:


Public Pages : More ERTS Technical Analysis Chalk-Talk Subjects

ERTS Price Forecasts

ERTS Traditional Time Series Analysis

Moving Averages and MACD Indicators

Multi-Spectral Analysis

ERTS Transaction Volume Trends

ERTS Analysis of Short Term and Long Term Risk

ERTS Calendar Seasonality

CandleStick Analysis

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Next Chapter 8:

Volume Stratification Analysis (or VSA) follows price behavior in relation to historical volumes of ERTS stock sales. Knowledge of these behaviors gives us a quantitative metric useful for understanding Support or Resistance Levels, and predicting their strength.


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