Computer Modelling Group Stock Price History

Computer Modelling Pink Sheet Price History Chart

Computer Modelling December 11, 2024 Pink Sheet Price Synopsis

Various analyses of Computer Modelling's daily price changes, such as its Balance Of Power or Price Action, are crucial when deciding whether to buy, hold, or sell Computer Pink Sheet. It can be used to describe the percentage change in the price of Computer Modelling from one trading day to the next and could be a valuable metric for traders and investors to gauge the volatility and momentum of Computer Pink Sheet. When benchmark price declines in a down market, there may be an uptick in Computer Stock price where buyers come in believing the asset is cheap or selling overdone. The opposite is true when the market is bullish. You can use Computer Modelling intraday prices and daily technical indicators to check the level of noise trading in Computer Stock and then apply it to test your longer-term investment strategies against Computer.

Computer Pink Sheet Price History Data

The price series of Computer Modelling for the period between Thu, Sep 12, 2024 and Wed, Dec 11, 2024 has a statistical range of 1.92 with a coefficient of variation of 6.81. The prices are distributed with arithmetic mean of 8.23. The median price for the last 90 days is 8.45. The company had 2:1 stock split on 3rd of July 2014. Computer Modelling issued dividends on 2023-03-06.

Computer Modelling investors dedicate a lot of time and effort to gaining insight into how a market's past behavior relates to its future. Access to timely market data for Computer is vital when making an investment decision, and regardless of whether you use fundamental or technical analysis, your return on investment in Computer Modelling will depend on recognizing future opportunities and eliminating past mistakes. Historical data analysis is the study of market behavior over a given time. Recorded market-related data such as price, volatility, and volume can be quantified and studied over a defined period. Through a detailed examination of a market's past behavior, traders and investors can gain perspective on the inner workings of that market. The information obtained throughout analyzing Computer Modelling stock prices may prove useful in developing a viable investing in Computer Modelling

Computer Modelling technical pink sheet analysis exercises models and trading practices based on price and volume transformations, such as the moving averages, relative strength index, regressions, price and return correlations, business cycles, pink sheet market cycles, or different charting patterns.

Predictive indicators are helping investors to find signals for Computer Modelling's price direction in advance. Along with the technical and fundamental analysis of Computer Pink Sheet historical price patterns, it is also worthwhile for investors to track various predictive indicators of Computer to make sure they correctly time the market and exploit it's hidden potentials. Even though most predictive indicators are useful for the short-term horizon, it's virtually impossible to predict the unforeseen market. For traders with a short-term horizon, predictive indicators add value when properly applied. Long-term investors, however, may find many predictive indicators less useful.

When running Computer Modelling's price analysis, check to measure Computer Modelling's market volatility, profitability, liquidity, solvency, efficiency, growth potential, financial leverage, and other vital indicators. We have many different tools that can be utilized to determine how healthy Computer Modelling is operating at the current time. Most of Computer Modelling's value examination focuses on studying past and present price action to predict the probability of Computer Modelling's future price movements. You can analyze the entity against its peers and the financial market as a whole to determine factors that move Computer Modelling's price. Additionally, you may evaluate how the addition of Computer Modelling to your portfolios can decrease your overall portfolio volatility.