Sigma Lithium Resources Stock Statistic Functions Pearson Correlation Coefficient

SGML Stock   18.99  0.43  2.21%   
Sigma Lithium statistic functions tool provides the execution environment for running the Pearson Correlation Coefficient function and other technical functions against Sigma Lithium. Sigma Lithium 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 Pearson Correlation Coefficient function function is designed to identify and follow existing trends. Sigma Lithium 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 nine with a total number of output elements of fifty-two. The Pearsons Correlation Coefficient is one of the most common measures of correlation in financial statistics. It shows the linear relationship between price series of Sigma Lithium Resources and its benchmark or peer.

Sigma Lithium Technical Analysis Modules

Most technical analysis of Sigma Lithium 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 Sigma from various momentum indicators to cycle indicators. When you analyze Sigma 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 Sigma Lithium 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 Sigma Lithium Resources. We use our internally-developed statistical techniques to arrive at the intrinsic value of Sigma Lithium Resources based on widely used predictive technical indicators. In general, we focus on analyzing Sigma Stock price patterns and their correlations with different microeconomic environment and drivers. We also apply predictive analytics to build Sigma Lithium'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 Sigma Lithium's intrinsic value. In addition to deriving basic predictive indicators for Sigma Lithium, we also check how macroeconomic factors affect Sigma Lithium price patterns. Please read more on our technical analysis page or use our predictive modules below to complement your research.
 2023 2024 (projected)
Graham Number3.982.5
Receivables Turnover3.443.06
Hype
Prediction
LowEstimatedHigh
14.4918.4222.35
Details
Intrinsic
Valuation
LowRealHigh
13.7217.6421.58
Details
Naive
Forecast
LowNextHigh
15.5119.4423.36
Details
Earnings
Estimates (0)
LowProjected EPSHigh
-0.16-0.1-0.04
Details

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Additional Tools for Sigma Stock Analysis

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