Energy Fuels Stock Market Value
| EFR Stock | CAD 8.51 0.26 2.96% |
| Symbol | Energy |
Energy Fuels Price To Book Ratio
Energy Fuels 'What if' Analysis
In the world of financial modeling, what-if analysis is part of sensitivity analysis performed to test how changes in assumptions impact individual outputs in a model. When applied to Energy Fuels' stock what-if analysis refers to the analyzing how the change in your past investing horizon will affect the profitability against the current market value of Energy Fuels.
| 11/16/2024 |
| 12/16/2024 |
If you would invest 0.00 in Energy Fuels on November 16, 2024 and sell it all today you would earn a total of 0.00 from holding Energy Fuels or generate 0.0% return on investment in Energy Fuels over 30 days. Energy Fuels is related to or competes with Western Copper, Sangoma Technologies, Evertz Technologies, Quorum Information, and CVW CleanTech. Energy Fuels Inc., together with its subsidiaries, engages in the extraction, recovery, exploration, and sale of convent... More
Energy Fuels Upside/Downside Indicators
Understanding different market momentum indicators often help investors to time their next move. Potential upside and downside technical ratios enable traders to measure Energy Fuels' stock current market value against overall market sentiment and can be a good tool during both bulling and bearish trends. Here we outline some of the essential indicators to assess Energy Fuels upside and downside potential and time the market with a certain degree of confidence.
| Downside Deviation | 3.21 | |||
| Information Ratio | 0.0916 | |||
| Maximum Drawdown | 22.39 | |||
| Value At Risk | (4.48) | |||
| Potential Upside | 5.19 |
Energy Fuels Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for Energy Fuels' investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as Energy Fuels' standard deviation. In reality, there are many statistical measures that can use Energy Fuels historical prices to predict the future Energy Fuels' volatility.| Risk Adjusted Performance | 0.0936 | |||
| Jensen Alpha | 0.3529 | |||
| Total Risk Alpha | (0.03) | |||
| Sortino Ratio | 0.1084 | |||
| Treynor Ratio | 0.4622 |
Energy Fuels Backtested Returns
Energy Fuels appears to be slightly risky, given 3 months investment horizon. Energy Fuels secures Sharpe Ratio (or Efficiency) of 0.15, which denotes the company had a 0.15% return per unit of risk over the last 3 months. By reviewing Energy Fuels' technical indicators, you can evaluate if the expected return of 0.57% is justified by implied risk. Please utilize Energy Fuels' Coefficient Of Variation of 847.83, downside deviation of 3.21, and Mean Deviation of 2.81 to check if our risk estimates are consistent with your expectations. On a scale of 0 to 100, Energy Fuels holds a performance score of 11. The firm shows a Beta (market volatility) of 0.95, which means possible diversification benefits within a given portfolio. Energy Fuels returns are very sensitive to returns on the market. As the market goes up or down, Energy Fuels is expected to follow. Please check Energy Fuels' downside variance, day median price, and the relationship between the treynor ratio and kurtosis , to make a quick decision on whether Energy Fuels' price patterns will revert.
Auto-correlation | -0.08 |
Very weak reverse predictability
Energy Fuels has very weak reverse predictability. Overlapping area represents the amount of predictability between Energy Fuels time series from 16th of November 2024 to 1st of December 2024 and 1st of December 2024 to 16th of December 2024. The more autocorrelation exist between current time interval and its lagged values, the more accurately you can make projection about the future pattern of Energy Fuels price movement. The serial correlation of -0.08 indicates that barely 8.0% of current Energy Fuels price fluctuation can be explain by its past prices.
| Correlation Coefficient | -0.08 | |
| Spearman Rank Test | 0.09 | |
| Residual Average | 0.0 | |
| Price Variance | 0.21 |
Energy Fuels lagged returns against current returns
Autocorrelation, which is Energy Fuels stock's lagged correlation, explains the relationship between observations of its time series of returns over different periods of time. The observations are said to be independent if autocorrelation is zero. Autocorrelation is calculated as a function of mean and variance and can have practical application in predicting Energy Fuels' stock expected returns. We can calculate the autocorrelation of Energy Fuels returns to help us make a trade decision. For example, suppose you find that Energy Fuels has exhibited high autocorrelation historically, and you observe that the stock is moving up for the past few days. In that case, you can expect the price movement to match the lagging time series.
Current and Lagged Values |
| Timeline |
Energy Fuels regressed lagged prices vs. current prices
Serial correlation can be approximated by using the Durbin-Watson (DW) test. The correlation can be either positive or negative. If Energy Fuels stock is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if Energy Fuels stock is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in Energy Fuels stock over time.
Current vs Lagged Prices |
| Timeline |
Energy Fuels Lagged Returns
When evaluating Energy Fuels' market value, investors can use the concept of autocorrelation to see how much of an impact past prices of Energy Fuels stock have on its future price. Energy Fuels autocorrelation represents the degree of similarity between a given time horizon and a lagged version of the same horizon over the previous time interval. In other words, Energy Fuels autocorrelation shows the relationship between Energy Fuels stock current value and its past values and can show if there is a momentum factor associated with investing in Energy Fuels.
Regressed Prices |
| Timeline |
Pair Trading with Energy Fuels
One of the main advantages of trading using pair correlations is that every trade hedges away some risk. Because there are two separate transactions required, even if Energy Fuels position performs unexpectedly, the other equity can make up some of the losses. Pair trading also minimizes risk from directional movements in the market. For example, if an entire industry or sector drops because of unexpected headlines, the short position in Energy Fuels will appreciate offsetting losses from the drop in the long position's value.Moving together with Energy Stock
Moving against Energy Stock
| 0.8 | MFC-PC | Manulife Finl Srs | PairCorr |
| 0.67 | SLF-PC | Sun Life Financial | PairCorr |
| 0.66 | SLF-PD | Sun Life Financial | PairCorr |
| 0.58 | SAGE | Sage Potash Corp | PairCorr |
| 0.45 | SLF-PG | Sun Life Non | PairCorr |
The ability to find closely correlated positions to Energy Fuels could be a great tool in your tax-loss harvesting strategies, allowing investors a quick way to find a similar-enough asset to replace Energy Fuels when you sell it. If you don't do this, your portfolio allocation will be skewed against your target asset allocation. So, investors can't just sell and buy back Energy Fuels - that would be a violation of the tax code under the "wash sale" rule, and this is why you need to find a similar enough asset and use the proceeds from selling Energy Fuels to buy it.
The correlation of Energy Fuels is a statistical measure of how it moves in relation to other instruments. This measure is expressed in what is known as the correlation coefficient, which ranges between -1 and +1. A perfect positive correlation (i.e., a correlation coefficient of +1) implies that as Energy Fuels moves, either up or down, the other security will move in the same direction. Alternatively, perfect negative correlation means that if Energy Fuels moves in either direction, the perfectly negatively correlated security will move in the opposite direction. If the correlation is 0, the equities are not correlated; they are entirely random. A correlation greater than 0.8 is generally described as strong, whereas a correlation less than 0.5 is generally considered weak.
Correlation analysis and pair trading evaluation for Energy Fuels can also be used as hedging techniques within a particular sector or industry or even over random equities to generate a better risk-adjusted return on your portfolios.Check out Energy Fuels Correlation, Energy Fuels Volatility and Energy Fuels Alpha and Beta module to complement your research on Energy Fuels. To learn how to invest in Energy Stock, please use our How to Invest in Energy Fuels guide.You can also try the Pattern Recognition module to use different Pattern Recognition models to time the market across multiple global exchanges.
Energy Fuels technical stock analysis exercises models and trading practices based on price and volume transformations, such as the moving averages, relative strength index, regressions, price and return correlations, business cycles, stock market cycles, or different charting patterns.