EigenLayer Market Value
| EIGEN Crypto | USD 3.89 0.03 0.78% |
| Symbol | EigenLayer |
EigenLayer '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 EigenLayer'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 EigenLayer.
| 10/29/2024 |
| 11/28/2024 |
If you would invest 0.00 in EigenLayer on October 29, 2024 and sell it all today you would earn a total of 0.00 from holding EigenLayer or generate 0.0% return on investment in EigenLayer over 30 days. EigenLayer is related to or competes with Staked Ether, BLZ, Highstreet, Tokocrypto, and DIA. EigenLayer is peer-to-peer digital currency powered by the Blockchain technology.
EigenLayer 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 EigenLayer'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 EigenLayer upside and downside potential and time the market with a certain degree of confidence.
| Downside Deviation | 7.4 | |||
| Information Ratio | (0) | |||
| Maximum Drawdown | 33.38 | |||
| Value At Risk | (8.93) | |||
| Potential Upside | 16.93 |
EigenLayer Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for EigenLayer's investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as EigenLayer's standard deviation. In reality, there are many statistical measures that can use EigenLayer historical prices to predict the future EigenLayer's volatility.| Risk Adjusted Performance | 0.021 | |||
| Jensen Alpha | (0.12) | |||
| Total Risk Alpha | (0.97) | |||
| Sortino Ratio | (0) | |||
| Treynor Ratio | 0.0553 |
EigenLayer Backtested Returns
EigenLayer is abnormally risky given 3 months investment horizon. EigenLayer secures Sharpe Ratio (or Efficiency) of 0.13, which denotes digital coin had a 0.13% return per unit of risk over the last 3 months. We were able to break down twenty-nine different technical indicators, which can help you to evaluate if expected returns of 15.99% are justified by taking the suggested risk. Use EigenLayer Mean Deviation of 4.14, downside deviation of 7.4, and Coefficient Of Variation of 6282.44 to evaluate coin specific risk that cannot be diversified away. The crypto shows a Beta (market volatility) of 1.77, which means a somewhat significant risk relative to the market. As the market goes up, the company is expected to outperform it. However, if the market returns are negative, EigenLayer will likely underperform.
Auto-correlation | 0.18 |
Very weak predictability
EigenLayer has very weak predictability. Overlapping area represents the amount of predictability between EigenLayer time series from 29th of October 2024 to 13th of November 2024 and 13th of November 2024 to 28th of November 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 EigenLayer price movement. The serial correlation of 0.18 indicates that over 18.0% of current EigenLayer price fluctuation can be explain by its past prices.
| Correlation Coefficient | 0.18 | |
| Spearman Rank Test | 0.22 | |
| Residual Average | 0.0 | |
| Price Variance | 0.33 |
EigenLayer lagged returns against current returns
Autocorrelation, which is EigenLayer 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 EigenLayer's crypto coin expected returns. We can calculate the autocorrelation of EigenLayer returns to help us make a trade decision. For example, suppose you find that EigenLayer 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 |
EigenLayer 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 EigenLayer crypto coin is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if EigenLayer crypto coin is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in EigenLayer crypto coin over time.
Current vs Lagged Prices |
| Timeline |
EigenLayer Lagged Returns
When evaluating EigenLayer's market value, investors can use the concept of autocorrelation to see how much of an impact past prices of EigenLayer crypto coin have on its future price. EigenLayer 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, EigenLayer autocorrelation shows the relationship between EigenLayer crypto coin current value and its past values and can show if there is a momentum factor associated with investing in EigenLayer.
Regressed Prices |
| Timeline |
Also Currently Popular
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.When determining whether EigenLayer offers a strong return on investment in its stock, a comprehensive analysis is essential. The process typically begins with a thorough review of EigenLayer's financial statements, including income statements, balance sheets, and cash flow statements, to assess its financial health. Key financial ratios are used to gauge profitability, efficiency, and growth potential of Eigenlayer Crypto.Check out EigenLayer Correlation, EigenLayer Volatility and Investing Opportunities module to complement your research on EigenLayer. You can also try the Equity Forecasting module to use basic forecasting models to generate price predictions and determine price momentum.
EigenLayer 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.