Energy Fuels Stock Price Prediction
| EFR Stock | CAD 9.74 0.16 1.62% |
Oversold Vs Overbought
60
Oversold | Overbought |
Quarterly Earnings Growth (0.97) | EPS Estimate Current Year (0.14) | EPS Estimate Next Year (0.1) | Wall Street Target Price 14.5 | EPS Estimate Current Quarter (0.08) |
Using Energy Fuels hype-based prediction, you can estimate the value of Energy Fuels from the perspective of Energy Fuels response to recently generated media hype and the effects of current headlines on its competitors.
The fear of missing out, i.e., FOMO, can cause potential investors in Energy Fuels to buy its stock at a price that has no basis in reality. In that case, they are not buying Energy because the equity is a good investment, but because they need to do something to avoid the feeling of missing out. On the other hand, investors will often sell stocks at prices well below their value during bear markets because they need to stop feeling the pain of losing money.
Energy Fuels after-hype prediction price | CAD 9.78 |
There is no one specific way to measure market sentiment using hype analysis or a similar predictive technique. This prediction method should be used in combination with more fundamental and traditional techniques such as stock price forecasting, technical analysis, analysts consensus, earnings estimates, and various momentum models.
Energy |
Energy Fuels After-Hype Price Prediction Density Analysis
As far as predicting the price of Energy Fuels at your current risk attitude, this probability distribution graph shows the chance that the prediction will fall between or within a specific range. We use this chart to confirm that your returns on investing in Energy Fuels or, for that matter, your successful expectations of its future price, cannot be replicated consistently. Please note, a large amount of money has been lost over the years by many investors who confused the symmetrical distributions of Stock prices, such as prices of Energy Fuels, with the unreliable approximations that try to describe financial returns.
Next price density |
| Expected price to next headline |
Energy Fuels Estimiated After-Hype Price Volatility
In the context of predicting Energy Fuels' stock value on the day after the next significant headline, we show statistically significant boundaries of downside and upside scenarios based on Energy Fuels' historical news coverage. Energy Fuels' after-hype downside and upside margins for the prediction period are 5.74 and 13.82, respectively. We have considered Energy Fuels' daily market price in relation to the headlines to evaluate this method's predictive performance. Remember, however, there is no scientific proof or empirical evidence that news-based prediction models outperform traditional linear, nonlinear models or artificial intelligence models to provide accurate predictions consistently.
Current Value
Energy Fuels is slightly risky at this time. Analysis and calculation of next after-hype price of Energy Fuels is based on 3 months time horizon.
Energy Fuels Stock Price Prediction Analysis
Have you ever been surprised when a price of a Company such as Energy Fuels is soaring high without any particular reason? This is usually happening because many institutional investors are aggressively trading Energy Fuels backward and forwards among themselves. Have you ever observed a lot of a particular company's price movement is driven by press releases or news about the company that has nothing to do with actual earnings? Usually, hype to individual companies acts as price momentum. If not enough favorable publicity is forthcoming, the Stock price eventually runs out of speed. So, the rule of thumb here is that as long as this news hype has nothing to do with immediate earnings, you should pay more attention to it. If you see this tendency with Energy Fuels, there might be something going there, and it might present an excellent short sale opportunity.
| Expected Return | Period Volatility | Hype Elasticity | Related Elasticity | News Density | Related Density | Expected Hype |
0.76 | 4.05 | 0.04 | 0.01 | 8 Events / Month | 1 Events / Month | In about 8 days |
| Latest traded price | Expected after-news price | Potential return on next major news | Average after-hype volatility | ||
9.74 | 9.78 | 0.41 |
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Energy Fuels Hype Timeline
Energy Fuels is currently traded for 9.74on Toronto Exchange of Canada. The entity has historical hype elasticity of 0.04, and average elasticity to hype of competition of 0.01. Energy is projected to increase in value after the next headline, with the price projected to jump to 9.78 or above. The average volatility of media hype impact on the company the price is over 100%. The price boost on the next news is estimated to be 0.41%, whereas the daily expected return is currently at 0.76%. The volatility of related hype on Energy Fuels is about 28350.0%, with the expected price after the next announcement by competition of 9.75. The company reported the revenue of 37.93 M. Net Income was 99.76 M with profit before overhead, payroll, taxes, and interest of 4.67 M. Assuming the 90 days trading horizon the next projected press release will be in about 8 days. Check out Energy Fuels Basic Forecasting Models to cross-verify your projections.Energy Fuels Related Hype Analysis
Having access to credible news sources related to Energy Fuels' direct competition is more important than ever and may enhance your ability to predict Energy Fuels' future price movements. Getting to know how Energy Fuels' peers react to changing market sentiment, related social signals, and mainstream news is a great way to find investing opportunities and time the market. The summary table below summarizes the essential lagging indicators that can help you analyze how Energy Fuels may potentially react to the hype associated with one of its peers.
| HypeElasticity | NewsDensity | SemiDeviation | InformationRatio | PotentialUpside | ValueAt Risk | MaximumDrawdown | |||
| IAG | iA Financial | 1.03 | 1 per month | 0.58 | 0.14 | 1.43 | (1.77) | 18.65 | |
| FTU-PB | US Financial 15 | (0.01) | 1 per month | 1.30 | 0.08 | 2.94 | (2.45) | 11.93 | |
| CM-PS | Canadian Imperial Bank | 0.00 | 0 per month | 0.20 | (0.31) | 0.56 | (0.36) | 1.73 | |
| FTN-PA | Financial 15 Split | 0.00 | 0 per month | 0.00 | (0.22) | 0.48 | (0.19) | 1.70 | |
| ISD | iSign Media Solutions | 0.00 | 0 per month | 0.87 | (0.12) | 1.01 | (1.53) | 3.19 | |
| DFY | Definity Financial Corp | (1.23) | 3 per month | 0.90 | 0.11 | 2.23 | (1.31) | 8.70 | |
| WCM-A | Wilmington Capital Management | 0.31 | 3 per month | 0.00 | (0.06) | 0.00 | 0.00 | 12.40 |
Energy Fuels Additional Predictive Modules
Most predictive techniques to examine Energy price help traders to determine how to time the market. We provide a combination of tools to recognize potential entry and exit points for Energy using various technical 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 Indicators
The successful prediction of Energy Fuels stock price could yield a significant profit to investors. But is it possible? The efficient-market hypothesis suggests that all published stock prices of traded companies, such as Energy Fuels, already reflect all publicly available information. This academic statement is a fundamental principle of many financial and investing theories used today. However, the typical investor usually disagrees with a 'textbook' version of this hypothesis and continually tries to find mispriced stocks to increase returns. We use internally-developed statistical techniques to arrive at the intrinsic value of Energy Fuels based on analysis of Energy Fuels hews, social hype, general headline patterns, and widely used predictive technical indicators.
We also calculate exposure to Energy Fuels's market risk, different technical and fundamental indicators, relevant financial multiples and ratios, and then comparing them to Energy Fuels's related companies. | 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 |
Story Coverage note for Energy Fuels
The number of cover stories for Energy Fuels depends on current market conditions and Energy Fuels' risk-adjusted performance over time. The coverage that generates the most noise at a given time depends on the prevailing investment theme that Energy Fuels is classified under. However, while its typical story may have numerous social followers, the rapid visibility can also attract short-sellers, who usually are skeptical about Energy Fuels' long-term prospects. So, having above-average coverage will typically attract above-average short interest, leading to significant price volatility.
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Energy Fuels Short Properties
Energy Fuels' future price predictability will typically decrease when Energy Fuels' long traders begin to feel the short-sellers pressure to drive the price lower. The predictive aspect of Energy Fuels often depends not only on the future outlook of the potential Energy Fuels' investors but also on the ongoing dynamics between investors with different trading styles. Because the market risk indicators may have small false signals, it is better to identify suitable times to hedge a portfolio using different long/short signals. Energy Fuels' indicators that are reflective of the short sentiment are summarized in the table below.
| Common Stock Shares Outstanding | 160.2 M | |
| Cash And Short Term Investments | 190.5 M |
Check out Energy Fuels Basic Forecasting Models to cross-verify your projections. To learn how to invest in Energy Stock, please use our How to Invest in Energy Fuels guide.You can also try the Portfolio Optimization module to compute new portfolio that will generate highest expected return given your specified tolerance for risk.