Pyth Network Market Value
| PYTH Crypto | USD 0.13 0.01 8.33% |
| Symbol | Pyth |
Pyth 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 Pyth 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 Pyth Network.
| 04/28/2025 |
| 07/27/2025 |
If you would invest 0.00 in Pyth Network on April 28, 2025 and sell it all today you would earn a total of 0.00 from holding Pyth Network or generate 0.0% return on investment in Pyth Network over 90 days. Pyth Network is related to or competes with Staked Ether, EigenLayer, Morpho, and DIA. Pyth Network is peer-to-peer digital currency powered by the Blockchain technology.
Pyth 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 Pyth 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 Pyth Network upside and downside potential and time the market with a certain degree of confidence.
| Information Ratio | (0.04) | |||
| Maximum Drawdown | 42.05 | |||
| Value At Risk | (9.09) | |||
| Potential Upside | 9.09 |
Pyth Network Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for Pyth Network's investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as Pyth Network's standard deviation. In reality, there are many statistical measures that can use Pyth Network historical prices to predict the future Pyth Network's volatility.| Risk Adjusted Performance | 0.0027 | |||
| Jensen Alpha | 0.1504 | |||
| Total Risk Alpha | (1.94) | |||
| Treynor Ratio | 0.0625 |
Pyth Network Backtested Returns
At this point, Pyth Network is unreasonably risky. Pyth Network maintains Sharpe Ratio (i.e., Efficiency) of close to zero, which implies digital coin had a close to zero % return per unit of risk over the last 3 months. We have found twenty-three technical indicators for Pyth Network, which you can use to evaluate the volatility of coin. Please check Pyth Network's Coefficient Of Variation of (12,424), variance of 53.11, and Risk Adjusted Performance of 0.0027 to confirm if the risk estimate we provide is consistent with the expected return of 0.036%. The crypto holds a Beta of -1.1, which implies a somewhat significant risk relative to the market. As the market becomes more bullish, returns on owning Pyth Network are expected to decrease slowly. On the other hand, during market turmoil, Pyth Network is expected to outperform it slightly.
Auto-correlation | -0.71 |
Almost perfect reverse predictability
Pyth Network has almost perfect reverse predictability. Overlapping area represents the amount of predictability between Pyth Network time series from 28th of April 2025 to 12th of June 2025 and 12th of June 2025 to 27th 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 Pyth Network price movement. The serial correlation of -0.71 indicates that around 71.0% of current Pyth Network price fluctuation can be explain by its past prices.
| Correlation Coefficient | -0.71 | |
| Spearman Rank Test | -0.6 | |
| Residual Average | 0.0 | |
| Price Variance | 0.0 |
Pyth Network lagged returns against current returns
Autocorrelation, which is Pyth 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 Pyth Network's crypto coin expected returns. We can calculate the autocorrelation of Pyth Network returns to help us make a trade decision. For example, suppose you find that Pyth 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 |
Pyth 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 Pyth Network crypto coin is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if Pyth 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 Pyth Network crypto coin over time.
Current vs Lagged Prices |
| Timeline |
Pyth Network Lagged Returns
When evaluating Pyth Network's market value, investors can use the concept of autocorrelation to see how much of an impact past prices of Pyth Network crypto coin have on its future price. Pyth 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, Pyth Network autocorrelation shows the relationship between Pyth Network crypto coin current value and its past values and can show if there is a momentum factor associated with investing in Pyth 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 Pyth Network offers a strong return on investment in its stock, a comprehensive analysis is essential. The process typically begins with a thorough review of Pyth 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 Pyth Network Crypto.Check out Pyth Network Correlation, Pyth Network Volatility and Investing Opportunities module to complement your research on Pyth Network. You can also try the Headlines Timeline module to stay connected to all market stories and filter out noise. Drill down to analyze hype elasticity.
Pyth 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.