Clean Energy (Germany) Technical Analysis
| WIQ Stock | EUR 1.91 0.07 3.80% |
As of the 28th of January, Clean Energy shows the risk adjusted performance of (0.06), and Mean Deviation of 2.11. In respect to fundamental indicators, the technical analysis model gives you tools to check existing technical drivers of Clean Energy, as well as the relationship between them. Please confirm Clean Energy Fuels maximum drawdown, and the relationship between the information ratio and potential upside to decide if Clean Energy Fuels is priced correctly, providing market reflects its regular price of 1.91 per share.
Clean Energy Momentum Analysis
Momentum indicators are widely used technical indicators which help to measure the pace at which the price of specific equity, such as Clean, fluctuates. Many momentum indicators also complement each other and can be helpful when the market is rising or falling as compared to CleanClean |
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.
| 10/30/2025 |
| 01/28/2026 |
If you would invest 0.00 in Clean Energy on October 30, 2025 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 BANGCHAK CORP, BANPU PCL, Thai Oil, Superior Plus, Intel, Volkswagen, and Rolls-Royce Holdings. Clean Energy Fuels Corp. provides natural gas as an alternative fuel for vehicle fleets in the United States and Canada 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.
| Information Ratio | (0.11) | |||
| Maximum Drawdown | 25.95 | |||
| Value At Risk | (3.94) | |||
| Potential Upside | 3.8 |
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.| Risk Adjusted Performance | (0.06) | |||
| Jensen Alpha | (0.34) | |||
| Total Risk Alpha | (0.59) | |||
| Treynor Ratio | (0.42) |
Clean Energy January 28, 2026 Technical Indicators
| Cycle Indicators | ||
| Math Operators | ||
| Math Transform | ||
| Momentum Indicators | ||
| Overlap Studies | ||
| Pattern Recognition | ||
| Price Transform | ||
| Statistic Functions | ||
| Volatility Indicators | ||
| Volume Indicators |
| Risk Adjusted Performance | (0.06) | |||
| Market Risk Adjusted Performance | (0.41) | |||
| Mean Deviation | 2.11 | |||
| Coefficient Of Variation | (1,140) | |||
| Standard Deviation | 3.2 | |||
| Variance | 10.25 | |||
| Information Ratio | (0.11) | |||
| Jensen Alpha | (0.34) | |||
| Total Risk Alpha | (0.59) | |||
| Treynor Ratio | (0.42) | |||
| Maximum Drawdown | 25.95 | |||
| Value At Risk | (3.94) | |||
| Potential Upside | 3.8 | |||
| Skewness | (1.00) | |||
| Kurtosis | 8.16 |
Clean Energy Fuels Backtested Returns
Clean Energy Fuels secures Sharpe Ratio (or Efficiency) of -0.13, which signifies that the company had a -0.13 % return per unit of standard deviation over the last 3 months. Clean Energy Fuels exposes twenty-four different technical indicators, which can help you to evaluate volatility embedded in its price movement. Please confirm Clean Energy's risk adjusted performance of (0.06), and Mean Deviation of 2.11 to double-check the risk estimate we provide. The firm shows a Beta (market volatility) of 0.7, which signifies possible diversification benefits within a given portfolio. As returns on the market increase, Clean Energy's returns are expected to increase less than the market. However, during the bear market, the loss of holding Clean Energy is expected to be smaller as well. At this point, Clean Energy Fuels has a negative expected return of -0.39%. Please make sure to confirm Clean Energy's potential upside, daily balance of power, and the relationship between the maximum drawdown and kurtosis , to decide if Clean Energy Fuels performance from the past will be repeated at some point in the near future.
Auto-correlation | 0.39 |
Below average predictability
Clean Energy Fuels has below average predictability. Overlapping area represents the amount of predictability between Clean Energy time series from 30th of October 2025 to 14th of December 2025 and 14th of December 2025 to 28th of January 2026. 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 0.39 indicates that just about 39.0% of current Clean Energy price fluctuation can be explain by its past prices.
| Correlation Coefficient | 0.39 | |
| Spearman Rank Test | -0.15 | |
| Residual Average | 0.0 | |
| Price Variance | 0.0 |
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.
Clean Energy Fuels Technical Analysis
The output start index for this execution was twenty-four with a total number of output elements of thirty-seven. The Normalized Average True Range is used to analyze tradable apportunities for Clean Energy Fuels across different markets.
About Clean Energy Technical Analysis
The technical analysis module can be used to analyzes prices, returns, volume, basic money flow, and other market information and help investors to determine the real value of Clean Energy Fuels on a daily or weekly bases. We use both bottom-up as well as top-down valuation methodologies to arrive at the intrinsic value of Clean Energy Fuels based on its technical analysis. In general, a bottom-up approach, as applied to this company, focuses on Clean Energy Fuels price pattern first instead of the macroeconomic environment surrounding Clean Energy Fuels. By analyzing Clean Energy's financials, daily price indicators, and related drivers such as dividends, momentum ratios, and various types of growth rates, we attempt to find the most accurate representation of Clean Energy's intrinsic value. As compared to a bottom-up approach, our top-down model examines the macroeconomic factors that affect the industry/economy before zooming in to Clean Energy specific price patterns or momentum indicators. Please read more on our technical analysis page.
Clean Energy January 28, 2026 Technical Indicators
Most technical analysis of Clean help investors determine whether a current trend will continue and, if not, when it will shift. We provide a combination of tools to recognize potential entry and exit points for Clean from various momentum indicators to cycle indicators. When you analyze Clean charts, please remember that the event formation may indicate an entry point for a short seller, and look at different 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 |
| Risk Adjusted Performance | (0.06) | |||
| Market Risk Adjusted Performance | (0.41) | |||
| Mean Deviation | 2.11 | |||
| Coefficient Of Variation | (1,140) | |||
| Standard Deviation | 3.2 | |||
| Variance | 10.25 | |||
| Information Ratio | (0.11) | |||
| Jensen Alpha | (0.34) | |||
| Total Risk Alpha | (0.59) | |||
| Treynor Ratio | (0.42) | |||
| Maximum Drawdown | 25.95 | |||
| Value At Risk | (3.94) | |||
| Potential Upside | 3.8 | |||
| Skewness | (1.00) | |||
| Kurtosis | 8.16 |
Clean Energy January 28, 2026 Daily Trend Indicators
Traders often use several different daily volumes and price technical indicators to supplement a more traditional technical analysis when analyzing securities such as Clean stock. With literally thousands of different options, investors must choose the best indicators for them and familiarize themselves with how they work. We suggest combining traditional momentum indicators with more near-term forms of technical analysis such as Accumulation Distribution or Daily Balance Of Power. With their quantitative nature, daily value technical indicators can also be incorporated into your automated trading systems.
| Accumulation Distribution | 4.19 | ||
| Daily Balance Of Power | 0.87 | ||
| Rate Of Daily Change | 1.04 | ||
| Day Median Price | 1.87 | ||
| Day Typical Price | 1.88 | ||
| Price Action Indicator | 0.07 | ||
| Market Facilitation Index | 0.0008 |
Complementary Tools for Clean Stock analysis
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.
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