Energy Fuels Stock Overlap Studies Double Exponential Moving Average
| EFR Stock | CAD 8.51 0.26 2.96% |
| Symbol |
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 Double Exponential Moving Average indicator was developed by Patrick Mulloy. It consists of a single exponential moving average and a double exponential moving average. This indicator is more responsive to Energy Fuels changes than the simple moving average.
Energy Fuels Technical Analysis Modules
Most technical analysis of Energy Fuels 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 Energy from various momentum indicators to cycle indicators. When you analyze Energy 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 | ||
| Math Operators | ||
| Math Transform | ||
| Momentum Indicators | ||
| Overlap Studies | ||
| Pattern Recognition | ||
| Price Transform | ||
| Statistic Functions | ||
| Volatility Indicators | ||
| Volume Indicators |
About Energy Fuels 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 Energy Fuels. We use our internally-developed statistical techniques to arrive at the intrinsic value of Energy Fuels based on widely used predictive technical indicators. In general, we focus on analyzing Energy Stock price patterns and their correlations with different microeconomic environment and drivers. We also apply predictive analytics to build Energy Fuels's daily price indicators and compare them against related drivers, such as overlap studies 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 Energy Fuels's intrinsic value. In addition to deriving basic predictive indicators for Energy Fuels, we also check how macroeconomic factors affect Energy Fuels price patterns. Please read more on our technical analysis page or use our predictive modules below to complement your research.
| 2021 | 2022 | 2023 | 2024 (projected) | Payables Turnover | 0.6 | 4.24 | 18.07 | 10.92 | Days Of Inventory On Hand | 6.2K | 1.8K | 780.31 | 1.3K |
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Check out Investing Opportunities to better understand how to build diversified portfolios, which includes a position in Energy Fuels. Also, note that the market value of any company could be closely tied with the direction of predictive economic indicators such as signals in board of governors. To learn how to invest in Energy Stock, please use our How to Invest in Energy Fuels guide.You can also try the Risk-Return Analysis module to view associations between returns expected from investment and the risk you assume.