Clean Energy Stock Forecast - Naive Prediction
| CLNE Stock | USD 2.14 0.05 2.28% |
The Naive Prediction forecasted value of Clean Energy Fuels on the next trading day is expected to be 2.13 with a mean absolute deviation of 0.07 and the sum of the absolute errors of 4.30. Clean Stock Forecast is based on your current time horizon. Investors can use this forecasting interface to forecast Clean Energy stock prices and determine the direction of Clean Energy Fuels's future trends based on various well-known forecasting models. We recommend always using this module together with an analysis of Clean Energy's historical fundamentals, such as revenue growth or operating cash flow patterns.
At the present time, the relative strength momentum indicator of Clean Energy's share price is approaching 46 suggesting that the stock is in nutural position, most likellhy at or near its support level. The main point of RSI analysis is to track how fast people are buying or selling Clean Energy, making its price go up or down. Momentum 46
Impartial
Oversold | Overbought |
Quarterly Earnings Growth 5.12 | EPS Estimate Next Quarter (0.07) | EPS Estimate Current Year (0.02) | EPS Estimate Next Year (0.04) | Wall Street Target Price 4.7071 |
Using Clean Energy hype-based prediction, you can estimate the value of Clean Energy Fuels from the perspective of Clean Energy response to recently generated media hype and the effects of current headlines on its competitors. We also analyze overall investor sentiment towards Clean Energy using Clean Energy's stock options and short interest. It helps to benchmark the overall future attitude of investors towards Clean using crowd psychology based on the activity and movement of Clean Energy's stock price.
Clean Energy Short Interest
A significant increase or decrease in Clean Energy's short interest from the previous month could be a good indicator of investor sentiment towards Clean. Short interest can provide insight into the potential direction of Clean Energy stock and how bullish or bearish investors feel about the market overall.
200 Day MA 2.1469 | Short Percent 0.0446 | Short Ratio 6.44 | Shares Short Prior Month 8.2 M | 50 Day MA 2.3452 |
Clean Energy Fuels Hype to Price Pattern
Investor biases related to Clean Energy's public news can be used to forecast risks associated with an investment in Clean. The trend in average sentiment can be used to explain how an investor holding Clean can time the market purely based on public headlines and social activities around Clean Energy Fuels. Please note that most equities that are difficult to arbitrage are affected by market sentiment the most.
Some investors profit by finding stocks that are overvalued or undervalued based on market sentiment. The correlation of Clean Energy's market sentiment to its price can help taders to make decisions based on the overall investors consensus about Clean Energy.
Clean Energy Implied Volatility | 1.04 |
Clean Energy's implied volatility exposes the market's sentiment of Clean Energy Fuels stock's possible movements over time. However, it does not forecast the overall direction of its price. In a nutshell, if Clean Energy's implied volatility is high, the market thinks the stock has potential for high price swings in either direction. On the other hand, the low implied volatility suggests that Clean Energy stock will not fluctuate a lot when Clean Energy's options are near their expiration.
The Naive Prediction forecasted value of Clean Energy Fuels on the next trading day is expected to be 2.13 with a mean absolute deviation of 0.07 and the sum of the absolute errors of 4.30. Clean Energy after-hype prediction price | USD 2.22 |
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 Clean Energy to cross-verify your projections. Open Interest Against 2026-03-20 Clean Option Contracts
Although open interest is a measure utilized in the options markets, it could be used to forecast Clean Energy's spot prices because the number of available contracts in the market changes daily, and new contracts can be created or liquidated at will. Since open interest in Clean Energy's options reflects these daily shifts, investors could use the patterns of these changes to develop long and short-term trading strategies for Clean Energy stock based on available contracts left at the end of a trading day.
Please note that to derive more accurate forecasting about market movement from the current Clean Energy's open interest, investors have to compare it to Clean Energy's spot prices. As Ford's stock price increases, high open interest indicates that money is entering the market, and the market is strongly bullish. Conversely, if the price of Clean Energy is decreasing and there is high open interest, that is a sign that the bearish trend will continue, and investors may react by taking short positions in Clean. So, decreasing or low open interest during a bull market indicates that investors are becoming uncertain of the depth of the bullish trend, and a reversal in sentiment will likely follow.
Clean Energy Additional Predictive Modules
Most predictive techniques to examine Clean price help traders to determine how to time the market. We provide a combination of tools to recognize potential entry and exit points for Clean using various technical indicators. When you analyze Clean 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 |
Clean Energy Cash Forecast
Forecasting cash, or other financial indicators, requires analysts to apply different statistical methods, techniques, and algorithms to find hidden patterns within the Clean Energy's financial statements to predict how it will affect future prices.
Cash | First Reported 2005-12-31 | Previous Quarter 132.1 M | Current Value 183 M | Quarterly Volatility 60.6 M |
Clean Energy Naive Prediction Price Forecast For the 8th of January
Given 90 days horizon, the Naive Prediction forecasted value of Clean Energy Fuels on the next trading day is expected to be 2.13 with a mean absolute deviation of 0.07, mean absolute percentage error of 0.01, and the sum of the absolute errors of 4.30.Please note that although there have been many attempts to predict Clean Stock prices using its time series forecasting, we generally do not recommend using it to place bets in the real market. The most commonly used models for forecasting predictions are the autoregressive models, which specify that Clean Energy's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).
Clean Energy Stock Forecast Pattern
| Backtest Clean Energy | Clean Energy Price Prediction | Buy or Sell Advice |
Clean Energy Forecasted Value
In the context of forecasting Clean 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. Clean Energy's downside and upside margins for the forecasting period are 0.02 and 5.58, respectively. We have considered Clean 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 Naive Prediction forecasting method's relative quality and the estimations of the prediction error of Clean Energy stock data series using in forecasting. Note that when a statistical model is used to represent Clean 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 | 113.441 |
| Bias | Arithmetic mean of the errors | None |
| MAD | Mean absolute deviation | 0.0706 |
| MAPE | Mean absolute percentage error | 0.0278 |
| SAE | Sum of the absolute errors | 4.3046 |
Predictive Modules for Clean 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 Clean Energy Fuels. 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.Other Forecasting Options for Clean Energy
For every potential investor in Clean, whether a beginner or expert, Clean Energy's price movement is the inherent factor that sparks whether it is viable to invest in it or hold it better. Clean Stock price charts are filled with many 'noises.' These noises can hugely alter the decision one can make regarding investing in Clean. Basic forecasting techniques help filter out the noise by identifying Clean Energy's price trends.Clean 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 Clean Energy stock to make a market-neutral strategy. Peer analysis of Clean Energy could also be used in its relative valuation, which is a method of valuing Clean Energy by comparing valuation metrics with similar companies.
| Risk & Return | Correlation |
Clean Energy Fuels Technical and Predictive Analytics
The stock market is financially volatile. Despite the volatility, there exist limitless possibilities of gaining profits and building passive income portfolios. With the complexity of Clean Energy's price movements, a comprehensive understanding of forecasting methods that an investor can rely on to make the right move is invaluable. These methods predict trends that assist an investor in predicting the movement of Clean Energy's current price.| Cycle Indicators | ||
| Math Operators | ||
| Math Transform | ||
| Momentum Indicators | ||
| Overlap Studies | ||
| Pattern Recognition | ||
| Price Transform | ||
| Statistic Functions | ||
| Volatility Indicators | ||
| Volume Indicators |
Clean Energy Market Strength Events
Market strength indicators help investors to evaluate how Clean Energy stock reacts to ongoing and evolving market conditions. The investors can use it to make informed decisions about market timing, and determine when trading Clean Energy shares will generate the highest return on investment. By undertsting and applying Clean Energy stock market strength indicators, traders can identify Clean Energy Fuels entry and exit signals to maximize returns.
Clean Energy Risk Indicators
The analysis of Clean Energy's basic risk indicators is one of the essential steps in accurately forecasting its future price. The process involves identifying the amount of risk involved in Clean Energy's investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting clean stock prices, we also provide a set of basic risk indicators that can assist in the individual investment decision or help in hedging the risk of your existing portfolios.
| Mean Deviation | 2.35 | |||
| Standard Deviation | 3.39 | |||
| Variance | 11.46 |
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.
Also Currently Popular
Analyzing currently trending equities could be an opportunity to develop a better portfolio based on different market momentums that they can trigger. Utilizing the top trending stocks is also useful when creating a market-neutral strategy or pair trading technique involving a short or a long position in a currently trending equity.| JBL | Jabil Circuit | |
| MRK | Merck Company | |
| AMGN | Amgen Inc |
Check out Historical Fundamental Analysis of Clean Energy to cross-verify your projections. You can also try the Funds Screener module to find actively-traded funds from around the world traded on over 30 global exchanges.
Is Oil & Gas Refining & Marketing space expected to grow? Or is there an opportunity to expand the business' product line in the future? Factors like these will boost the valuation of Clean Energy. If investors know Clean will grow in the future, the company's valuation will be higher. The financial industry is built on trying to define current growth potential and future valuation accurately. All the valuation information about Clean Energy listed above have to be considered, but the key to understanding future value is determining which factors weigh more heavily than others.
Quarterly Earnings Growth 5.12 | Earnings Share (0.94) | Revenue Per Share | Quarterly Revenue Growth 0.012 | Return On Assets |
The market value of Clean Energy Fuels is measured differently than its book value, which is the value of Clean that is recorded on the company's balance sheet. Investors also form their own opinion of Clean Energy's value that differs from its market value or its book value, called intrinsic value, which is Clean Energy's true underlying value. Investors use various methods to calculate intrinsic value and buy a stock when its market value falls below its intrinsic value. Because Clean Energy's market value can be influenced by many factors that don't directly affect Clean Energy's underlying business (such as a pandemic or basic market pessimism), market value can vary widely from intrinsic value.
Please note, there is a significant difference between Clean Energy's value and its price as these two are different measures arrived at by different means. Investors typically determine if Clean Energy is a good investment by looking at such factors as earnings, sales, fundamental and technical indicators, competition as well as analyst projections. However, Clean Energy's price is the amount at which it trades on the open market and represents the number that a seller and buyer find agreeable to each party.