Polygon Market Value
| MATIC Crypto | USD 0.70 0.05 7.69% |
| Symbol | Polygon |
Polygon '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 Polygon'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 Polygon.
| 03/17/2024 |
| 04/16/2024 |
If you would invest 0.00 in Polygon on March 17, 2024 and sell it all today you would earn a total of 0.00 from holding Polygon or generate 0.0% return on investment in Polygon over 30 days. Polygon is related to or competes with Solana, XRP, Open Network, Staked Ether, Ethena, Avalanche, and Chainlink. Polygon is peer-to-peer digital currency powered by the Blockchain technology.
Polygon 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 Polygon'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 Polygon upside and downside potential and time the market with a certain degree of confidence.
| Information Ratio | (0.04) | |||
| Maximum Drawdown | 25.26 | |||
| Value At Risk | (8.77) | |||
| Potential Upside | 7.69 |
Polygon Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for Polygon's investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as Polygon's standard deviation. In reality, there are many statistical measures that can use Polygon historical prices to predict the future Polygon's volatility.| Risk Adjusted Performance | (0.01) | |||
| Jensen Alpha | (0.23) | |||
| Total Risk Alpha | (0.58) | |||
| Treynor Ratio | (0.12) |
Sophisticated investors, who have witnessed many market ups and downs, anticipate that the market will even out over time. This tendency of Polygon'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.
Polygon Backtested Returns
Polygon maintains Sharpe Ratio (i.e., Efficiency) of -0.0115, which implies digital coin had a -0.0115% return per unit of risk over the last 3 months. Polygon exposes twenty-three different technical indicators, which can help you to evaluate volatility embedded in its price movement. Please check Polygon's Variance of 25.26, coefficient of variation of (3,383), and Risk Adjusted Performance of (0.01) to confirm the risk estimate we provide. The crypto holds a Beta of 1.29, which implies 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, Polygon will likely underperform.
Auto-correlation | 0.44 |
Average predictability
Polygon has average predictability. Overlapping area represents the amount of predictability between Polygon time series from 17th of March 2024 to 1st of April 2024 and 1st of April 2024 to 16th of April 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 Polygon price movement. The serial correlation of 0.44 indicates that just about 44.0% of current Polygon price fluctuation can be explain by its past prices.
| Correlation Coefficient | 0.44 | |
| Spearman Rank Test | 0.12 | |
| Residual Average | 0.0 | |
| Price Variance | 0.01 |
Polygon lagged returns against current returns
Autocorrelation, which is Polygon 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 Polygon's crypto coin expected returns. We can calculate the autocorrelation of Polygon returns to help us make a trade decision. For example, suppose you find that Polygon 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 |
Polygon 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 Polygon crypto coin is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if Polygon crypto coin is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in Polygon crypto coin over time.
Current vs Lagged Prices |
| Timeline |
Polygon Lagged Returns
When evaluating Polygon's market value, investors can use the concept of autocorrelation to see how much of an impact past prices of Polygon crypto coin have on its future price. Polygon 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, Polygon autocorrelation shows the relationship between Polygon crypto coin current value and its past values and can show if there is a momentum factor associated with investing in Polygon.
Regressed Prices |
| Timeline |
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Polygon 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.