Gigachad Market Value
GIGA Crypto | USD 0.09 0 3.24% |
Symbol | Gigachad |
Gigachad '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 Gigachad'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 Gigachad.
12/07/2024 |
| 01/06/2025 |
If you would invest 0.00 in Gigachad on December 7, 2024 and sell it all today you would earn a total of 0.00 from holding Gigachad or generate 0.0% return on investment in Gigachad over 30 days. Gigachad is related to or competes with XRP, Solana, Sui, Staked Ether, Toncoin, Worldcoin, and Chainlink. Gigachad is peer-to-peer digital currency powered by the Blockchain technology.
Gigachad 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 Gigachad'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 Gigachad upside and downside potential and time the market with a certain degree of confidence.
Downside Deviation | 10.61 | |||
Information Ratio | 0.1681 | |||
Maximum Drawdown | 59.06 | |||
Value At Risk | (13.15) | |||
Potential Upside | 23.92 |
Gigachad Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for Gigachad's investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as Gigachad's standard deviation. In reality, there are many statistical measures that can use Gigachad historical prices to predict the future Gigachad's volatility.Risk Adjusted Performance | 0.1473 | |||
Jensen Alpha | 1.86 | |||
Total Risk Alpha | 1.7 | |||
Sortino Ratio | 0.1748 | |||
Treynor Ratio | 4.78 |
Gigachad Backtested Returns
Gigachad is abnormally risky given 3 months investment horizon. Gigachad holds Efficiency (Sharpe) Ratio of 0.18, which attests that digital coin had a 0.18% return per unit of risk over the last 3 months. We were able to break down twenty-nine different technical indicators, which can help you to evaluate if expected returns of 31.62% are justified by taking the suggested risk. Use Gigachad Downside Deviation of 10.61, market risk adjusted performance of 4.79, and Risk Adjusted Performance of 0.1473 to evaluate coin specific risk that cannot be diversified away. The crypto retains a Market Volatility (i.e., Beta) of 0.39, which attests to possible diversification benefits within a given portfolio. As returns on the market increase, Gigachad's returns are expected to increase less than the market. However, during the bear market, the loss of holding Gigachad is expected to be smaller as well.
Auto-correlation | 0.88 |
Very good predictability
Gigachad has very good predictability. Overlapping area represents the amount of predictability between Gigachad time series from 7th of December 2024 to 22nd of December 2024 and 22nd of December 2024 to 6th of January 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 Gigachad price movement. The serial correlation of 0.88 indicates that approximately 88.0% of current Gigachad price fluctuation can be explain by its past prices.
Correlation Coefficient | 0.88 | |
Spearman Rank Test | 0.93 | |
Residual Average | 0.0 | |
Price Variance | 0.0 |
Gigachad lagged returns against current returns
Autocorrelation, which is Gigachad 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 Gigachad's crypto coin expected returns. We can calculate the autocorrelation of Gigachad returns to help us make a trade decision. For example, suppose you find that Gigachad 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 |
Gigachad 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 Gigachad crypto coin is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if Gigachad crypto coin is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in Gigachad crypto coin over time.
Current vs Lagged Prices |
Timeline |
Gigachad Lagged Returns
When evaluating Gigachad's market value, investors can use the concept of autocorrelation to see how much of an impact past prices of Gigachad crypto coin have on its future price. Gigachad 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, Gigachad autocorrelation shows the relationship between Gigachad crypto coin current value and its past values and can show if there is a momentum factor associated with investing in Gigachad.
Regressed Prices |
Timeline |
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Check out Gigachad Correlation, Gigachad Volatility and Investing Opportunities module to complement your research on Gigachad. You can also try the Portfolio Suggestion module to get suggestions outside of your existing asset allocation including your own model portfolios.
Gigachad 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.