CHESS Alpha and Beta Analysis
| CHESS Crypto | USD 0.22 0.02 10.00% |
This module allows you to check different measures of market premium (i.e., alpha and beta) for all equities such as CHESS. It also helps investors analyze the systematic and unsystematic risks associated with investing in CHESS over a specified time horizon. Remember, high CHESS'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 (0.02) | Alpha 0.46 | Risk 6.65 | Sharpe Ratio 0.11 | Expected Return 0.72 |
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.
CHESS |
CHESS Market Premiums
Investors always prefer to have the highest possible return on investment, coupled with the lowest possible volatility. CHESS market risk premium is the additional return an investor will receive from holding CHESS 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 CHESS. 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 CHESS's performance over market.| α | 0.46 | β | -0.02 |
CHESS Price Momentum Analysis
CHESS Market Price Analysis
Market price analysis indicators help investors to evaluate how CHESS 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 CHESS shares will generate the highest return on investment. By understating and applying CHESS crypto coin market price indicators, traders can identify CHESS position entry and exit signals to maximize returns.
CHESS Return and Market Media
The median price of CHESS for the period between Sun, Sep 1, 2024 and Sat, Nov 30, 2024 is 0.16 with a coefficient of variation of 11.59. The daily time series for the period is distributed with a sample standard deviation of 0.02, arithmetic mean of 0.16, and mean deviation of 0.01. The Crypto did not receive any noticable media coverage during the period. Price Growth (%) |
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About CHESS 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 CHESS or other cryptos. Alpha measures the amount that position in CHESS 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 CHESS 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 CHESS Backtesting, Portfolio Optimization, CHESS Correlation, Cryptocurrency Center, CHESS Volatility, CHESS History and analyze CHESS Performance. You can also try the Competition Analyzer module to analyze and compare many basic indicators for a group of related or unrelated entities.
CHESS 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.