Paragon Technologies Stock Statistic Functions Linear Regression Intercept

PGNT Stock  USD 7.65  0.05  0.65%   
Paragon Technologies statistic functions tool provides the execution environment for running the Linear Regression Intercept function and other technical functions against Paragon Technologies. Paragon Technologies value trend is the prevailing direction of the price over some defined period of time. The concept of trend is an important idea in technical analysis, including the analysis of statistic functions indicators. As with most other technical indicators, the Linear Regression Intercept function function is designed to identify and follow existing trends. Paragon Technologies statistical functions help analysts to determine different price movement patterns based on how price series statistical indicators change over time. Please specify Time Period to run this model.

Function
Time Period
Execute Function
The output start index for this execution was thirty-five with a total number of output elements of twenty-six. The Linear Regression Intercept is the expected mean value of Paragon Technologies price seriese where values of its benchmark or peer price series are zero.

Paragon Technologies Technical Analysis Modules

Most technical analysis of Paragon Technologies help investors determine whether a current trend will continue and, if not, when it will shift. We provide a combination of tools to recognize potential entry and exit points for Paragon from various momentum indicators to cycle indicators. When you analyze Paragon charts, please remember that the event formation may indicate an entry point for a short seller, and look at other indicators across different periods to confirm that a breakdown or reversion is likely to occur.

About Paragon Technologies Predictive Technical Analysis

Predictive technical analysis modules help investors to analyze different prices and returns patterns as well as diagnose historical swings to determine the real value of Paragon Technologies. We use our internally-developed statistical techniques to arrive at the intrinsic value of Paragon Technologies based on widely used predictive technical indicators. In general, we focus on analyzing Paragon Pink Sheet price patterns and their correlations with different microeconomic environment and drivers. We also apply predictive analytics to build Paragon Technologies's daily price indicators and compare them against related drivers, such as statistic functions and various other types of predictive indicators. Using this methodology combined with a more conventional technical analysis and fundamental analysis, we attempt to find the most accurate representation of Paragon Technologies's intrinsic value. In addition to deriving basic predictive indicators for Paragon Technologies, we also check how macroeconomic factors affect Paragon Technologies price patterns. Please read more on our technical analysis page or use our predictive modules below to complement your research.
Hype
Prediction
LowEstimatedHigh
4.037.6511.27
Details
Intrinsic
Valuation
LowRealHigh
2.536.159.77
Details
Naive
Forecast
LowNextHigh
3.136.7510.37
Details
Bollinger
Band Projection (param)
LowerMiddle BandUpper
5.046.868.69
Details

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Additional Tools for Paragon Pink Sheet Analysis

When running Paragon Technologies' price analysis, check to measure Paragon Technologies' 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 Paragon Technologies is operating at the current time. Most of Paragon Technologies' value examination focuses on studying past and present price action to predict the probability of Paragon Technologies' future price movements. You can analyze the entity against its peers and the financial market as a whole to determine factors that move Paragon Technologies' price. Additionally, you may evaluate how the addition of Paragon Technologies to your portfolios can decrease your overall portfolio volatility.