Render Network Market Value
| RENDER Crypto | 7.36 0.01 0.14% |
| Symbol | Render |
Please note, there is a significant difference between Render Network's coin value and its market price as these two are different measures arrived at by different means. Cryptocurrency investors typically determine Render Network value by looking at such factors as its true mass adoption, usability, application, safety as well as its ability to resist fraud and manipulation. On the other hand, Render Network's price is the amount at which it trades on the cryptocurrency exchange or other digital marketplace that truly represents its supply and demand.
Render Network '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 Render Network'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 Render Network.
| 05/26/2024 |
| 11/22/2024 |
If you would invest 0.00 in Render Network on May 26, 2024 and sell it all today you would earn a total of 0.00 from holding Render Network or generate 0.0% return on investment in Render Network over 180 days. Render Network is related to or competes with Solana, XRP, Sui, Staked Ether, Toncoin, Worldcoin, and TRON. Render Network is peer-to-peer digital currency powered by the Blockchain technology.
Render Network 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 Render Network'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 Render Network upside and downside potential and time the market with a certain degree of confidence.
| Downside Deviation | 5.08 | |||
| Information Ratio | 0.1033 | |||
| Maximum Drawdown | 42.69 | |||
| Value At Risk | (7.58) | |||
| Potential Upside | 11.79 |
Render Network Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for Render Network's investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as Render Network's standard deviation. In reality, there are many statistical measures that can use Render Network historical prices to predict the future Render Network's volatility.| Risk Adjusted Performance | 0.0967 | |||
| Jensen Alpha | 0.7631 | |||
| Total Risk Alpha | 0.0127 | |||
| Sortino Ratio | 0.1472 | |||
| Treynor Ratio | 1.01 |
Sophisticated investors, who have witnessed many market ups and downs, anticipate that the market will even out over time. This tendency of Render Network'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.
Render Network Backtested Returns
Render Network appears to be unreasonably risky, given 3 months investment horizon. Render Network maintains Sharpe Ratio (i.e., Efficiency) of 0.0874, which implies digital coin had a 0.0874% return per unit of risk over the last 3 months. By analyzing Render Network's technical indicators, you can evaluate if the expected return of 0.62% is justified by implied risk. Please evaluate Render Network's Risk Adjusted Performance of 0.0967, coefficient of variation of 858.28, and Semi Deviation of 4.57 to confirm if our risk estimates are consistent with your expectations. The crypto holds a Beta of 0.82, which implies possible diversification benefits within a given portfolio. As returns on the market increase, Render Network's returns are expected to increase less than the market. However, during the bear market, the loss of holding Render Network is expected to be smaller as well.
Auto-correlation | 0.17 |
Very weak predictability
Render Network has very weak predictability. Overlapping area represents the amount of predictability between Render Network time series from 26th of May 2024 to 24th of August 2024 and 24th of August 2024 to 22nd 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 Render Network price movement. The serial correlation of 0.17 indicates that over 17.0% of current Render Network price fluctuation can be explain by its past prices.
| Correlation Coefficient | 0.17 | |
| Spearman Rank Test | -0.07 | |
| Residual Average | 0.0 | |
| Price Variance | 0.66 |
Render Network lagged returns against current returns
Autocorrelation, which is Render Network 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 Render Network's crypto coin expected returns. We can calculate the autocorrelation of Render Network returns to help us make a trade decision. For example, suppose you find that Render Network 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 |
Render Network 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 Render Network crypto coin is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if Render Network crypto coin is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in Render Network crypto coin over time.
Current vs Lagged Prices |
| Timeline |
Render Network Lagged Returns
When evaluating Render Network's market value, investors can use the concept of autocorrelation to see how much of an impact past prices of Render Network crypto coin have on its future price. Render Network 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, Render Network autocorrelation shows the relationship between Render Network crypto coin current value and its past values and can show if there is a momentum factor associated with investing in Render Network.
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 Render Network offers a strong return on investment in its stock, a comprehensive analysis is essential. The process typically begins with a thorough review of Render Network'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 Render Network Crypto.Check out Render Network Correlation, Render Network Volatility and Investing Opportunities module to complement your research on Render Network. You can also try the Sectors module to list of equity sectors categorizing publicly traded companies based on their primary business activities.
Render Network 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.