Clean Energy Fuels Stock Price Prediction

Intrinsic Valuation Low Real High 1.08 4.34 7.60 Details

Naive Forecast Low Next High 0.06 3.20 6.46 Details

9 Analysts Consensus Low Target High 7.91 8.69 9.65 Details

Earnings Estimates (0) Low Projected EPS High -0.01 -0.005 0 Details

Clean Energy After-Hype Price Prediction Density Analysis

Clean Energy Estimiated After-Hype Price Volatility

Clean Energy Stock Price Prediction Analysis

Expected Return	Period Volatility	Hype Elasticity	Related Elasticity	News Density	Related Density	Expected Hype
0.16	3.26	0.01	0.01	11 Events / Month	6 Events / Month	In about 11 days

Latest traded price	Expected after-news price	Potential return on next major news	Average after-hype volatility
3.08	3.09	0.32	4,657   Notes

Clean Energy Hype Timeline

Clean Energy Fuels is currently traded for 3.08. The entity has historical hype elasticity of 0.01, and average elasticity to hype of competition of -0.01. Clean is estimated to increase in value after the next headline, with the price projected to jump to 3.09 or above. The average volatility of media hype impact on the company the price is over 100%. The price growth on the next news is projected to be 0.32%, whereas the daily expected return is currently at 0.16%. The volatility of related hype on Clean Energy is about 10030.77%, with the expected price after the next announcement by competition of 3.07. The company reported the previous year's revenue of 425.16 M. Net Loss for the year was (99.5 M) with profit before overhead, payroll, taxes, and interest of 112.42 M. Given the investment horizon of 90 days the next estimated press release will be in about 11 days. Check out Clean Energy Basic Forecasting Models to cross-verify your projections.

Clean Energy Related Hype Analysis

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.

The successful prediction of Clean Energy 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 Clean 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 Clean Energy based on analysis of Clean Energy hews, social hype, general headline patterns, and widely used predictive technical indicators.

The number of cover stories for Clean Energy depends on current market conditions and Clean 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 Clean 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 Clean Energy's long-term prospects. So, having above-average coverage will typically attract above-average short interest, leading to significant price volatility.

Clean Energy's future price predictability will typically decrease when Clean Energy's long traders begin to feel the short-sellers pressure to drive the price lower. The predictive aspect of Clean Energy Fuels often depends not only on the future outlook of the potential Clean Energy's 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. Clean Energy's indicators that are reflective of the short sentiment are summarized in the table below.

When running Clean Energy's price analysis, check to measure Clean 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 Clean Energy is operating at the current time. Most of Clean Energy's value examination focuses on studying past and present price action to predict the probability of Clean 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 Clean Energy's price. Additionally, you may evaluate how the addition of Clean Energy to your portfolios can decrease your overall portfolio volatility.