Clean Energy (Germany) Market Value
| WIQ Stock | EUR 2.91 0.03 1.02% |
| Symbol | Clean |
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.
| 06/05/2024 |
| 12/02/2024 |
If you would invest 0.00 in Clean Energy on June 5, 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 180 days. Clean Energy is related to or competes with Marathon Petroleum, Neste Oyj, ENEOS Holdings, and PTT OIL+RETBUS-FOR-B. 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.
| Downside Deviation | 3.37 | |||
| Information Ratio | 0.0016 | |||
| Maximum Drawdown | 19.44 | |||
| Value At Risk | (5.02) | |||
| Potential Upside | 6.1 |
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 | 0.036 | |||
| Jensen Alpha | 0.0995 | |||
| Total Risk Alpha | (0.52) | |||
| Sortino Ratio | 0.0019 | |||
| Treynor Ratio | 0.4953 |
Clean Energy Fuels Backtested Returns
Clean Energy appears to be very risky, given 3 months investment horizon. Clean Energy Fuels secures Sharpe Ratio (or Efficiency) of 0.0693, which signifies that the company had a 0.0693% return per unit of standard deviation over the last 3 months. We have found twenty-nine technical indicators for Clean Energy Fuels, which you can use to evaluate the volatility of the firm. Please makes use of Clean Energy's risk adjusted performance of 0.036, and Mean Deviation of 3.12 to double-check if our risk estimates are consistent with your expectations. On a scale of 0 to 100, Clean Energy holds a performance score of 5. The firm shows a Beta (market volatility) of 0.27, which signifies not very significant fluctuations relative to the market. 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. Please check Clean Energy's standard deviation, treynor ratio, downside variance, as well as the relationship between the total risk alpha and value at risk , to make a quick decision on whether Clean Energy's price patterns will revert.
Auto-correlation | -0.03 |
Very weak reverse predictability
Clean Energy Fuels has very weak reverse predictability. Overlapping area represents the amount of predictability between Clean Energy time series from 5th of June 2024 to 3rd of September 2024 and 3rd of September 2024 to 2nd of December 2024. 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 -0.03 indicates that only 3.0% of current Clean Energy price fluctuation can be explain by its past prices.
| Correlation Coefficient | -0.03 | |
| Spearman Rank Test | 0.29 | |
| Residual Average | 0.0 | |
| Price Variance | 0.02 |
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 |
Currently Active Assets on Macroaxis
Additional Information and Resources on Investing in Clean Stock
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 CEOs Directory module to screen CEOs from public companies 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.