Clean Energy Fuels Stock Market Value

CLNE Stock  USD 1.76  0.01  0.57%   
Clean Energy's market value is the price at which a share of Clean Energy trades on a public exchange. It measures the collective expectations of Clean Energy Fuels investors about its performance. Clean Energy is trading at 1.76 as of the 15th of March 2025, a 0.57% increase since the beginning of the trading day. The stock's lowest day price was 1.72.
With this module, you can estimate the performance of a buy and hold strategy of Clean Energy Fuels and determine expected loss or profit from investing in Clean Energy over a given investment horizon. Check out Clean Energy Correlation, Clean Energy Volatility and Clean Energy Alpha and Beta module to complement your research on Clean Energy.
Symbol

Clean Energy Fuels Price To Book Ratio

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
(0.37)
Revenue Per Share
1.862
Quarterly Revenue Growth
0.023
Return On Assets
(0.01)
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.

Clean Energy '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 Clean Energy's 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 Clean Energy.
0.00
12/15/2024
No Change 0.00  0.0 
In 3 months and 1 day
03/15/2025
0.00
If you would invest  0.00  in Clean Energy on December 15, 2024 and sell it all today you would earn a total of 0.00 from holding Clean Energy Fuels or generate 0.0% return on investment in Clean Energy over 90 days. Clean Energy is related to or competes with Icahn Enterprises, PBF Energy, Delek Logistics, Aemetis, Par Pacific, Delek Energy, and HF Sinclair. Clean Energy Fuels Corp. provides natural gas as an alternative fuel for vehicle fleets and related fueling solutions, p... More

Clean Energy 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 Clean Energy's 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 Clean Energy Fuels upside and downside potential and time the market with a certain degree of confidence.

Clean Energy Market Risk Indicators

Today, many novice investors tend to focus exclusively on investment returns with little concern for Clean Energy's investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as Clean Energy's standard deviation. In reality, there are many statistical measures that can use Clean Energy historical prices to predict the future Clean Energy's volatility.
Hype
Prediction
LowEstimatedHigh
0.081.676.58
Details
Intrinsic
Valuation
LowRealHigh
0.163.108.01
Details
9 Analysts
Consensus
LowTargetHigh
6.607.258.05
Details
Earnings
Estimates (0)
LowProjected EPSHigh
-0.29-0.15-0.02
Details

Clean Energy Fuels Backtested Returns

Clean Energy Fuels secures Sharpe Ratio (or Efficiency) of -0.12, which signifies that the company had a -0.12 % return per unit of standard deviation over the last 3 months. Clean Energy Fuels exposes twenty-two different technical indicators, which can help you to evaluate volatility embedded in its price movement. Please confirm Clean Energy's risk adjusted performance of (0.1), and Mean Deviation of 2.92 to double-check the risk estimate we provide. The firm shows a Beta (market volatility) of 0.86, which signifies possible diversification benefits within a given portfolio. Clean Energy returns are very sensitive to returns on the market. As the market goes up or down, Clean Energy is expected to follow. At this point, Clean Energy Fuels has a negative expected return of -0.6%. Please make sure to confirm Clean Energy's potential upside, day median price, and the relationship between the total risk alpha and accumulation distribution , to decide if Clean Energy Fuels performance from the past will be repeated at some point in the near future.

Auto-correlation

    
  -0.72  

Almost perfect reverse predictability

Clean Energy Fuels has almost perfect reverse predictability. Overlapping area represents the amount of predictability between Clean Energy time series from 15th of December 2024 to 29th of January 2025 and 29th of January 2025 to 15th of March 2025. The more autocorrelation exist between current time interval and its lagged values, the more accurately you can make projection about the future pattern of Clean Energy Fuels price movement. The serial correlation of -0.72 indicates that around 72.0% of current Clean Energy price fluctuation can be explain by its past prices.
Correlation Coefficient-0.72
Spearman Rank Test-0.68
Residual Average0.0
Price Variance0.42

Clean Energy Fuels lagged returns against current returns

Autocorrelation, which is Clean Energy 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 Clean Energy's stock expected returns. We can calculate the autocorrelation of Clean Energy returns to help us make a trade decision. For example, suppose you find that Clean Energy 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  

Clean Energy 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 Clean Energy stock is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if Clean Energy stock is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in Clean Energy stock over time.
   Current vs Lagged Prices   
       Timeline  

Clean Energy Lagged Returns

When evaluating Clean Energy's market value, investors can use the concept of autocorrelation to see how much of an impact past prices of Clean Energy stock have on its future price. Clean Energy 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, Clean Energy autocorrelation shows the relationship between Clean Energy stock current value and its past values and can show if there is a momentum factor associated with investing in Clean Energy Fuels.
   Regressed Prices   
       Timeline  

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When determining whether Clean Energy Fuels is a strong investment it is important to analyze Clean Energy's competitive position within its industry, examining market share, product or service uniqueness, and competitive advantages. Beyond financials and market position, potential investors should also consider broader economic conditions, industry trends, and any regulatory or geopolitical factors that may impact Clean Energy's future performance. For an informed investment choice regarding Clean Stock, refer to the following important reports:
Check out Clean Energy Correlation, Clean Energy Volatility and Clean Energy Alpha and Beta module to complement your research on Clean Energy.
You can also try the Money Managers module to screen money managers from public funds and ETFs managed around the world.
Clean Energy 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.
A focus of Clean Energy technical analysis is to determine if market prices reflect all relevant information impacting that market. A technical analyst looks at the history of Clean Energy trading pattern rather than external drivers such as economic, fundamental, or social events. It is believed that price action tends to repeat itself due to investors' collective, patterned behavior. Hence technical analysis focuses on identifiable price trends and conditions. More Info...