Polygon Alpha and Beta Analysis
| MATIC Crypto | USD 0.55 0.02 3.51% |
This module allows you to check different measures of market premium (i.e., alpha and beta) for all equities such as Polygon. It also helps investors analyze the systematic and unsystematic risks associated with investing in Polygon over a specified time horizon. Remember, high Polygon's alpha is almost always a sign of good performance; however, a high beta will depend on investors' risk tolerance level and may signal increased volatility and potential future overvaluation.
Beta 1.02 | Alpha 0.0115 | Risk 4.95 | Sharpe Ratio 0.0931 | Expected Return 0.46 |
Alpha is a measure of relative performance on a risk-adjusted basis, while beta measures volatility against the benchmark. The goal is to know if an investor is being compensated for the volatility risk taken. The return on investment might be better than its reference but still not compensate for the assumption of the risk.
Polygon |
Polygon Market Premiums
Investors always prefer to have the highest possible return on investment, coupled with the lowest possible volatility. Polygon market risk premium is the additional return an investor will receive from holding Polygon long position in a well-diversified portfolio. The market premium is part of the Capital Asset Pricing Model (CAPM), which most analysts and investors use to calculate the acceptable rate of return on investment in Polygon. At the center of the CAPM is the concept of risk and reward, which is usually communicated by investors using alpha and beta measures. Alpha and beta are two of the key measurements used to evaluate Polygon's performance over market.| α | 0.01 | β | 1.02 |
Polygon Price Momentum Analysis
Polygon Market Price Analysis
Market price analysis indicators help investors to evaluate how Polygon crypto coin reacts to ongoing and evolving market conditions. The investors can use it to make informed decisions about market timing, and determine when trading Polygon shares will generate the highest return on investment. By understating and applying Polygon crypto coin market price indicators, traders can identify Polygon position entry and exit signals to maximize returns.
Polygon Return and Market Media
The median price of Polygon for the period between Tue, Aug 27, 2024 and Mon, Nov 25, 2024 is 0.38 with a coefficient of variation of 12.66. The daily time series for the period is distributed with a sample standard deviation of 0.05, arithmetic mean of 0.39, and mean deviation of 0.03. The Crypto received substential amount of media coverage during this period. Price Growth (%) |
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About Polygon Beta and Alpha
For many years both, Alpha and Beta indicators are used by professional money managers as critical performance measurement tools across virtually all financial instruments including Polygon or other cryptos. Alpha measures the amount that position in Polygon has returned in comparison to a selected market index or another relevant benchmark. In other words, Alpha is the excess return on an investment relative to the performance of your selected benchmark. Beta, on the other hand, measures the relative risk of your investment.
Some cryptocurrency investors attempt to determine whether the market's mood is bullish or bearish by monitoring changes in market sentiment. However, unlike more traditional methods such as technical analysis, investor sentiment usually refers to the aggregate attitude towards Polygon in the overall investment community. So, suppose investors can accurately measure the crypto's market sentiment. In that case, they can use it for their benefit. For example, some tools provided by cryptocurrency exchanges to gauge market sentiment could be utilized to time the market in a somewhat predictable way.
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Check out Polygon Backtesting, Portfolio Optimization, Polygon Correlation, Cryptocurrency Center, Polygon Volatility, Polygon History and analyze Polygon Performance. You can also try the FinTech Suite module to use AI to screen and filter profitable investment opportunities.
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.