Pyth Network Market Value

PYTH Crypto  USD 0.15  0.01  7.14%   
Pyth Network's market value is the price at which a share of Pyth Network trades on a public exchange. It measures the collective expectations of Pyth Network investors about its performance. Pyth Network is trading at 0.15 as of the 18th of March 2025, a 7.14 percent up since the beginning of the trading day. With this module, you can estimate the performance of a buy and hold strategy of Pyth Network and determine expected loss or profit from investing in Pyth Network over a given investment horizon. Check out Pyth Network Correlation, Pyth Network Volatility and Investing Opportunities module to complement your research on Pyth Network.
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Please note, there is a significant difference between Pyth Network's coin value and its market price as these two are different measures arrived at by different means. Cryptocurrency investors typically determine Pyth 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, Pyth 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.

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.
0.00
12/18/2024
No Change 0.00  0.0 
In 2 months and 31 days
03/18/2025
0.00
If you would invest  0.00  in Pyth Network on December 18, 2024 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 XRP, Solana, Sui, TRON, Staked Ether, Chainlink, and Toncoin. 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.

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.
Hype
Prediction
LowEstimatedHigh
0.010.157.37
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Intrinsic
Valuation
LowRealHigh
0.010.147.36
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Pyth Network Backtested Returns

Pyth Network maintains Sharpe Ratio (i.e., Efficiency) of -0.16, which implies digital coin had a -0.16 % return per unit of risk over the last 3 months. Pyth Network exposes twenty-two different technical indicators, which can help you to evaluate volatility embedded in its price movement. Please check Pyth Network's Risk Adjusted Performance of (0.16), coefficient of variation of (516.10), and Variance of 53.08 to confirm the risk estimate we provide. The crypto holds a Beta of -0.46, which implies possible diversification benefits within a given portfolio. As returns on the market increase, returns on owning Pyth Network are expected to decrease at a much lower rate. During the bear market, Pyth Network is likely to outperform the market.

Auto-correlation

    
  0.56  

Modest predictability

Pyth Network has modest predictability. Overlapping area represents the amount of predictability between Pyth Network time series from 18th of December 2024 to 1st of February 2025 and 1st of February 2025 to 18th of March 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 0.56 indicates that roughly 56.0% of current Pyth Network price fluctuation can be explain by its past prices.
Correlation Coefficient0.56
Spearman Rank Test0.32
Residual Average0.0
Price Variance0.0

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  

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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.
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 Earnings Calls module to check upcoming earnings announcements updated hourly across public exchanges.
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.
A focus of Pyth Network technical analysis is to determine if market prices reflect all relevant information impacting that market. A technical analyst looks at the history of Pyth Network trading pattern rather than external drivers such as economic, fundamental, or social events. It is believed that price action tends to repeat itself due to investors' collective, patterned behavior. Hence technical analysis focuses on identifiable price trends and conditions. More Info...