Clean Energy Pathway Stock Market Value
| CPWY Stock | USD 0.0001 0.00 0.00% |
| 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 pink sheet 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.
| 11/15/2024 |
| 12/15/2024 |
If you would invest 0.00 in Clean Energy on November 15, 2024 and sell it all today you would earn a total of 0.00 from holding Clean Energy Pathway or generate 0.0% return on investment in Clean Energy over 30 days. Clean Energy is related to or competes with AT S, Alps Electric, American Aires, LGL, Eltek, Kopin, and KULR Technology. Clean Energy Pathways, Inc. operates as a multifaceted development-stage alternative energy company 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 pink sheet 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 Pathway 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.Sophisticated investors, who have witnessed many market ups and downs, anticipate that the market will even out over time. This tendency of Clean Energy's price to converge to an average value over time is called mean reversion. However, historically, high market prices usually discourage investors that believe in mean reversion to invest, while low prices are viewed as an opportunity to buy.
Clean Energy Pathway Backtested Returns
We have found three technical indicators for Clean Energy Pathway, which you can use to evaluate the volatility of the firm. The firm shows a Beta (market volatility) of 0.0, which signifies not very significant fluctuations relative to the market. the returns on MARKET and Clean Energy are completely uncorrelated.
Auto-correlation | 0.00 |
No correlation between past and present
Clean Energy Pathway has no correlation between past and present. Overlapping area represents the amount of predictability between Clean Energy time series from 15th of November 2024 to 30th of November 2024 and 30th of November 2024 to 15th 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 Pathway price movement. The serial correlation of 0.0 indicates that just 0.0% of current Clean Energy price fluctuation can be explain by its past prices.
| Correlation Coefficient | 0.0 | |
| Spearman Rank Test | 1.0 | |
| Residual Average | 0.0 | |
| Price Variance | 0.0 |
Clean Energy Pathway lagged returns against current returns
Autocorrelation, which is Clean Energy pink sheet'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 pink sheet 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 pink sheet 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 pink sheet is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if Clean Energy pink sheet is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in Clean Energy pink sheet 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 pink sheet 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 pink sheet current value and its past values and can show if there is a momentum factor associated with investing in Clean Energy Pathway.
Regressed Prices |
| Timeline |
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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.Additional Tools for Clean Pink Sheet 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.