Energy Fuels Stock Forward View - Polynomial Regression
| EFR Stock | CAD 26.48 0.10 0.38% |
The reference data on this page reflects Polynomial Regression output applied to Energy Fuels's historical daily closing prices. Forecast values and accuracy statistics are presented for informational purposes.
The Polynomial Regression forecasted value of Energy Fuels on the next trading day is expected to be 25.79 with a mean absolute deviation of 1.48 and the sum of the absolute errors of 91.93.A single variable polynomial regression model attempts to put a curve through the Energy Fuels historical price points. Mathematically, assuming the independent variable is X and the dependent variable is Y, this line can be indicated as: Y = a0 + a1*X + a2*X2 + a3*X3 + ... + am*Xm The forecast reference data presented here for Energy Fuels reflects Polynomial Regression model output and is intended as reference material for analytical use. Polynomial Regression Price Forecast For the 19th of March
Given 90 days horizon, the Polynomial Regression forecasted value of Energy Fuels on the next trading day is expected to be 25.79 with a mean absolute deviation of 1.48 , mean absolute percentage error of 3.76 , and the sum of the absolute errors of 91.93 .Please note that although there have been many attempts to predict Energy Stock prices using its time series forecasting, we generally do not suggest using it to place bets in the real market. The most commonly used models for forecasting predictions are the autoregressive models, which specify that Energy Fuels' next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).
Stock Forecast Pattern
| Backtest Energy Fuels | Energy Fuels Price Prediction | Research Analysis |
Forecasted Value
The next-day forecast for Energy Fuels focuses on identifying predictive downside and upside bands that can frame a realistic trading range. At the moment, the model places downside around 19.39 and upside around 32.19 for the forecasting period.
Model Predictive Factors
The below table displays some essential indicators generated by the model showing the Polynomial Regression forecasting method's relative quality and the estimations of the prediction error of Energy Fuels stock data series using in forecasting. Note that when a statistical model is used to represent Energy Fuels stock, the representation will rarely be exact; so some information will be lost using the model to explain the process. AIC estimates the relative amount of information lost by a given model: the less information a model loses, the higher its quality.| AIC | Akaike Information Criteria | 121.2732 |
| Bias | Arithmetic mean of the errors | None |
| MAD | Mean absolute deviation | 1.4828 |
| MAPE | Mean absolute percentage error | 0.0541 |
| SAE | Sum of the absolute errors | 91.9329 |
Other Forecasting Options for Energy Fuels
Understanding Energy Fuels' price movement is a prerequisite for any investor considering Energy as a position. Energy Stock price charts are frequently cluttered with noise that can interfere with accurate interpretation.Energy Fuels Related Equities
The following equities are related to Energy Fuels within the Energy space and can be used for peer comparison, relative valuation, or portfolio diversification. Comparing Energy Fuels against peers on metrics such as P/E, margins, and return on equity helps contextualize its positioning and identify relative strengths or weaknesses.
| Risk & Return | Correlation |
Energy Fuels Market Strength Events
For traders and investors in Energy Fuels, market strength indicators offer a quantitative framework for evaluating the stock's responsiveness to market conditions. These tools help identify when trading Energy Fuels shares is most likely to generate favorable returns.
Energy Fuels Risk Indicators
Analyzing Energy Fuels' risk indicators provides a critical input for price forecasting and investment risk management. By quantifying the risk in Energy Fuels' investment, investors can make more informed decisions about their exposure and hedging strategies.
| Mean Deviation | 4.94 | |||
| Semi Deviation | 5.37 | |||
| Standard Deviation | 6.29 | |||
| Variance | 39.62 | |||
| Downside Variance | 34.27 | |||
| Semi Variance | 28.79 | |||
| Expected Short fall | -5.34 |
Please note, the risk measures we provide can be used independently or collectively to perform a risk assessment. When comparing two potential investments, we recommend comparing similar equities with homogenous growth potential and valuation from related markets to determine which investment holds the most risk.
Story Coverage note for Energy Fuels
Coverage intensity for Energy Fuels matters because narrative visibility can influence sentiment, participation, and volatility around the name. The stronger process compares story flow with performance, theme classification, and the level of short-term market interest.
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Energy Fuels Short Properties
Reviewing short-oriented indicators for Energy Fuels is useful because long and short participants often create very different signals for timing and volatility. The practical goal is to identify when the balance between long and short participation may be changing the quality of the setup.
| Common Stock Shares Outstanding | 224.7 M | |
| Cash And Short Term Investments | 861.8 M |
More Resources for Energy Stock Analysis
Understanding Energy Fuels typically begins with financial statements and long-term trend review. Ratios and trend metrics help frame Energy Fuels' operating context across reporting periods. Key reports that frame Energy Fuels Stock are listed below:Cross-verify projections for Energy Fuels using Historical Fundamental Analysis of Energy Fuels. The historical series provides projection context. Our How to Buy Energy Stock guide explains the steps to invest in Energy Fuels stock.Energy Fuels currently shows ROE of -14.18%, market cap of 6.4 Billion. This analysis of Energy Fuels works best as a complementary layer when evaluating how the security fits in a broader portfolio. Within the Energy space, Energy Fuels peer comparison and risk tools below help frame relative strengths and weaknesses. You can also try the Financial Widgets module to easily integrated Macroaxis content with over 30 different plug-and-play financial widgets.