ELF Market Value
| ELF Crypto | USD 0.23 0.01 4.17% |
| Symbol | ELF |
ELF '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 ELF's crypto coin 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 ELF.
| 04/25/2025 |
| 07/24/2025 |
If you would invest 0.00 in ELF on April 25, 2025 and sell it all today you would earn a total of 0.00 from holding ELF or generate 0.0% return on investment in ELF over 90 days. ELF is related to or competes with EigenLayer, EUR CoinVertible, Morpho, and DIA. aelf is peer-to-peer digital currency powered by the Blockchain technology.
ELF 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 ELF's crypto coin 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 ELF upside and downside potential and time the market with a certain degree of confidence.
| Information Ratio | (0.06) | |||
| Maximum Drawdown | 17.64 | |||
| Value At Risk | (5.00) | |||
| Potential Upside | 5.26 |
ELF Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for ELF's investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as ELF's standard deviation. In reality, there are many statistical measures that can use ELF historical prices to predict the future ELF's volatility.| Risk Adjusted Performance | 0.0056 | |||
| Jensen Alpha | (0.10) | |||
| Total Risk Alpha | (0.81) | |||
| Treynor Ratio | (0.04) |
ELF Backtested Returns
ELF secures Sharpe Ratio (or Efficiency) of -0.021, which denotes digital coin had a -0.021 % return per unit of return volatility over the last 3 months. ELF exposes twenty-three different technical indicators, which can help you to evaluate volatility embedded in its price movement. Please confirm ELF's standard deviation of 3.44, and Mean Deviation of 2.14 to check the risk estimate we provide. The crypto shows a Beta (market volatility) of 0.42, which means possible diversification benefits within a given portfolio. As returns on the market increase, ELF's returns are expected to increase less than the market. However, during the bear market, the loss of holding ELF is expected to be smaller as well.
Auto-correlation | -0.57 |
Good reverse predictability
ELF has good reverse predictability. Overlapping area represents the amount of predictability between ELF time series from 25th of April 2025 to 9th of June 2025 and 9th of June 2025 to 24th of July 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 ELF price movement. The serial correlation of -0.57 indicates that roughly 57.0% of current ELF price fluctuation can be explain by its past prices.
| Correlation Coefficient | -0.57 | |
| Spearman Rank Test | -0.17 | |
| Residual Average | 0.0 | |
| Price Variance | 0.0 |
ELF lagged returns against current returns
Autocorrelation, which is ELF crypto coin'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 ELF's crypto coin expected returns. We can calculate the autocorrelation of ELF returns to help us make a trade decision. For example, suppose you find that ELF has exhibited high autocorrelation historically, and you observe that the crypto coin 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 |
ELF 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 ELF crypto coin is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if ELF crypto coin is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in ELF crypto coin over time.
Current vs Lagged Prices |
| Timeline |
ELF Lagged Returns
When evaluating ELF's market value, investors can use the concept of autocorrelation to see how much of an impact past prices of ELF crypto coin have on its future price. ELF 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, ELF autocorrelation shows the relationship between ELF crypto coin current value and its past values and can show if there is a momentum factor associated with investing in ELF.
Regressed Prices |
| Timeline |
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Check out ELF Correlation, ELF Volatility and Investing Opportunities module to complement your research on ELF. You can also try the Idea Analyzer module to analyze all characteristics, volatility and risk-adjusted return of Macroaxis ideas.
ELF technical crypto coin 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, crypto market cycles, or different charting patterns.