Sigma Lithium Resources Stock Volatility Indicators Average True Range
| SGML Stock | 16.04 0.35 2.23% |
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Incorrect Input. Please change your parameters or increase the time horizon required for running this function. The output start index for this execution was zero with a total number of output elements of zero. The Average True Range was developed by J. Welles Wilder in 1970s. It is one of components of the Welles Wilder Directional Movement indicators. The ATR is a measure of Sigma Lithium Resources volatility. High ATR values indicate high volatility, and low values indicate low volatility.
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.| Cycle Indicators | ||
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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 volatility indicators 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 Number | 3.98 | 2.5 | Receivables Turnover | 3.44 | 3.06 |
Some investors attempt to determine whether the market's mood is bullish or bearish by monitoring changes in market sentiment. Unlike more traditional methods such as technical analysis, investor sentiment usually refers to the aggregate attitude towards Sigma Lithium in the overall investment community. So, suppose investors can accurately measure the market's sentiment. In that case, they can use it for their benefit. For example, some tools to gauge market sentiment could be utilized using contrarian indexes, Sigma Lithium's short interest history, or implied volatility extrapolated from Sigma Lithium options trading.
Trending Themes
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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.