Green Energy Stock Forward View - Simple Exponential Smoothing
Green Stock outlook is based on your current time horizon. Although Green Energy's naive historical forecasting may sometimes provide an important future outlook for the firm, we suggest always cross-verifying it against solid analysis of Green Energy's systematic risk associated with finding meaningful patterns of Green Energy fundamentals over time.
As of today the relative strength index (rsi) of Green Energy's share price is below 20 . This usually indicates that the stock is significantly oversold. The fundamental principle of the Relative Strength Index (RSI) is to quantify the velocity at which market participants are driving the price of a financial instrument upwards or downwards. Momentum 0
Sell Peaked
Oversold | Overbought |
Quarterly Revenue Growth (0.99) |
Using Green Energy hype-based prediction, you can estimate the value of Green Energy Resources from the perspective of Green Energy response to recently generated media hype and the effects of current headlines on its competitors.
The Simple Exponential Smoothing forecasted value of Green Energy Resources on the next trading day is expected to be 0.00 with a mean absolute deviation of 0.00 and the sum of the absolute errors of 0.00. Green Energy after-hype prediction price | USD 0.0 |
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.
Check out Historical Fundamental Analysis of Green Energy to cross-verify your projections. Green Energy Additional Predictive Modules
Most predictive techniques to examine Green price help traders to determine how to time the market. We provide a combination of tools to recognize potential entry and exit points for Green using various technical indicators. When you analyze Green 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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| Math Transform | ||
| Momentum Indicators | ||
| Overlap Studies | ||
| Pattern Recognition | ||
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| Volatility Indicators | ||
| Volume Indicators |
Green Energy Simple Exponential Smoothing Price Forecast For the 7th of February
Given 90 days horizon, the Simple Exponential Smoothing forecasted value of Green Energy Resources on the next trading day is expected to be 0.00 with a mean absolute deviation of 0.00, mean absolute percentage error of 0.00, and the sum of the absolute errors of 0.00.Please note that although there have been many attempts to predict Green 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 Green Energy's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).
Green Energy Stock Forecast Pattern
| Backtest Green Energy | Green Energy Price Prediction | Research Analysis |
Green Energy Forecasted Value
In the context of forecasting Green Energy's Stock value on the next trading day, we examine the predictive performance of the model to find good statistically significant boundaries of downside and upside scenarios. Green Energy's downside and upside margins for the forecasting period are 0.00 and 0.00, respectively. We have considered Green Energy's daily market price to evaluate the above model's predictive performance. Remember, however, there is no scientific proof or empirical evidence that traditional linear or nonlinear forecasting models outperform artificial intelligence and frequency domain models to provide accurate forecasts consistently.
Model Predictive Factors
The below table displays some essential indicators generated by the model showing the Simple Exponential Smoothing forecasting method's relative quality and the estimations of the prediction error of Green Energy stock data series using in forecasting. Note that when a statistical model is used to represent Green Energy 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 | -9.223372036854776E14 |
| Bias | Arithmetic mean of the errors | None |
| MAD | Mean absolute deviation | 0.0 |
| MAPE | Mean absolute percentage error | 0.0 |
| SAE | Sum of the absolute errors | 0.0 |
Predictive Modules for Green Energy
There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Green Energy Resources. Regardless of method or technology, however, to accurately forecast the stock market is more a matter of luck rather than a particular technique. Nevertheless, trying to predict the stock market accurately is still an essential part of the overall investment decision process. Using different forecasting techniques and comparing the results might improve your chances of accuracy even though unexpected events may often change the market sentiment and impact your forecasting results.Green Energy Stock Price Outlook Analysis
Have you ever been surprised when a price of a Company such as Green Energy is soaring high without any particular reason? This is usually happening because many institutional investors are aggressively trading Green Energy 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 Green Energy, 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 |
0.00 | 0.00 | 0.00 | 0.00 | 1 Events / Month | 1 Events / Month | Very soon |
| Latest traded price | Expected after-news price | Potential return on next major news | Average after-hype volatility | |
0.00 | 0.00 | 0.00 |
|
Green Energy Hype Timeline
Green Energy Resources is currently traded for 0.00. The entity stock is not elastic to its hype. The average elasticity to hype of competition is 0.0. Green is forecasted not to react to the next headline, with the price staying at about the same level, and average media hype impact volatility is insignificant. The immediate return on the next news is forecasted to be very small, whereas the daily expected return is currently at 0.0%. %. The volatility of related hype on Green Energy is about 0.0%, with the expected price after the next announcement by competition of 0.00. The company had not issued any dividends in recent years. Green Energy Resources had 11:10 split on the 14th of November 2007. Given the investment horizon of 90 days the next forecasted press release will be very soon. Check out Historical Fundamental Analysis of Green Energy to cross-verify your projections.Green Energy Related Hype Analysis
Having access to credible news sources related to Green Energy's direct competition is more important than ever and may enhance your ability to predict Green Energy's future price movements. Getting to know how Green Energy's 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 Green Energy may potentially react to the hype associated with one of its peers.
| HypeElasticity | NewsDensity | SemiDeviation | InformationRatio | PotentialUpside | ValueAt Risk | MaximumDrawdown | |||
| PSPW | 3Power Energy Group | 0.00 | 0 per month | 0.00 | (0.13) | 0.00 | 0.00 | 60.00 | |
| AEPT | American Energy Partners | 0.36 | 6 per month | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | |
| ETRXF | Etrion | 0.00 | 0 per month | 0.00 | 0.16 | 0.00 | 0.00 | 25.00 | |
| TPII | Triad Pro Innovators | 0.00 | 4 per month | 0.00 | 0.05 | 0.00 | 0.00 | 100.00 | |
| GEECF | Global Environmental Energy | 0.00 | 0 per month | 0.00 | (0.13) | 0.00 | 0.00 | 50.00 | |
| NKWFF | Oceanic Wind Energy | 0.00 | 0 per month | 0.00 | 0.12 | 0.00 | 0.00 | 15,350 | |
| CGEI | CGE Energy | 0.00 | 0 per month | 0.00 | 0.12 | 0.00 | 0.00 | 100.00 | |
| NCEN | Nacel Energy Corp | 0.00 | 0 per month | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | |
| USWF | US Wind Farming | 0.00 | 0 per month | 0.00 | 0.05 | 0.00 | 0.00 | 150.00 | |
| ARSC | American Security Resources | 0.00 | 2 per month | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 |
Other Forecasting Options for Green Energy
For every potential investor in Green, whether a beginner or expert, Green Energy's price movement is the inherent factor that sparks whether it is viable to invest in it or hold it better. Green Stock price charts are filled with many 'noises.' These noises can hugely alter the decision one can make regarding investing in Green. Basic forecasting techniques help filter out the noise by identifying Green Energy's price trends.Green Energy Related Equities
One of the popular trading techniques among algorithmic traders is to use market-neutral strategies where every trade hedges away some risk. Because there are two separate transactions required, even if one position performs unexpectedly, the other equity can make up some of the losses. Below are some of the equities that can be combined with Green Energy stock to make a market-neutral strategy. Peer analysis of Green Energy could also be used in its relative valuation, which is a method of valuing Green Energy by comparing valuation metrics with similar companies.
| Risk & Return | Correlation |
Story Coverage note for Green Energy
The number of cover stories for Green Energy depends on current market conditions and Green Energy's risk-adjusted performance over time. The coverage that generates the most noise at a given time depends on the prevailing investment theme that Green Energy 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 Green Energy's long-term prospects. So, having above-average coverage will typically attract above-average short interest, leading to significant price volatility.
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Additional Tools for Green Stock Analysis
When running Green Energy's price analysis, check to measure Green Energy'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 Green Energy is operating at the current time. Most of Green Energy's value examination focuses on studying past and present price action to predict the probability of Green Energy's future price movements. You can analyze the entity against its peers and the financial market as a whole to determine factors that move Green Energy's price. Additionally, you may evaluate how the addition of Green Energy to your portfolios can decrease your overall portfolio volatility.