FTX Token Market Value
| FTT Crypto | USD 1.26 0.02 1.61% |
| Symbol | FTX |
FTX Token '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 FTX Token'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 FTX Token.
| 10/22/2023 |
| 04/19/2024 |
If you would invest 0.00 in FTX Token on October 22, 2023 and sell it all today you would earn a total of 0.00 from holding FTX Token or generate 0.0% return on investment in FTX Token over 180 days. FTX Token is related to or competes with Solana, XRP, Open Network, Staked Ether, Avalanche, Chainlink, and Ethena. FTX Token is peer-to-peer digital currency powered by the Blockchain technology.
FTX Token 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 FTX Token'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 FTX Token upside and downside potential and time the market with a certain degree of confidence.
| Information Ratio | (0.13) | |||
| Maximum Drawdown | 42.6 | |||
| Value At Risk | (14.87) | |||
| Potential Upside | 10.26 |
FTX Token Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for FTX Token's investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as FTX Token's standard deviation. In reality, there are many statistical measures that can use FTX Token historical prices to predict the future FTX Token's volatility.| Risk Adjusted Performance | (0.07) | |||
| Jensen Alpha | (1.03) | |||
| Total Risk Alpha | (1.62) | |||
| Treynor Ratio | (0.50) |
Sophisticated investors, who have witnessed many market ups and downs, anticipate that the market will even out over time. This tendency of FTX Token'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.
FTX Token Backtested Returns
FTX Token secures Sharpe Ratio (or Efficiency) of -0.12, which denotes digital coin had a -0.12% return per unit of volatility over the last 3 months. FTX Token exposes twenty-three different technical indicators, which can help you to evaluate volatility embedded in its price movement. Please confirm FTX Token's Mean Deviation of 5.06, market risk adjusted performance of (0.49), and Standard Deviation of 7.34 to check the risk estimate we provide. The crypto shows a Beta (market volatility) of 1.83, which means 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, FTX Token will likely underperform.
Auto-correlation | 0.00 |
No correlation between past and present
FTX Token has no correlation between past and present. Overlapping area represents the amount of predictability between FTX Token time series from 22nd of October 2023 to 20th of January 2024 and 20th of January 2024 to 19th 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 FTX Token price movement. The serial correlation of 0.0 indicates that just 0.0% of current FTX Token price fluctuation can be explain by its past prices.
| Correlation Coefficient | 0.0 | |
| Spearman Rank Test | -0.14 | |
| Residual Average | 0.0 | |
| Price Variance | 0.16 |
FTX Token lagged returns against current returns
Autocorrelation, which is FTX Token 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 FTX Token's crypto coin expected returns. We can calculate the autocorrelation of FTX Token returns to help us make a trade decision. For example, suppose you find that FTX Token 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 |
FTX Token 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 FTX Token crypto coin is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if FTX Token crypto coin is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in FTX Token crypto coin over time.
Current vs Lagged Prices |
| Timeline |
FTX Token Lagged Returns
When evaluating FTX Token's market value, investors can use the concept of autocorrelation to see how much of an impact past prices of FTX Token crypto coin have on its future price. FTX Token 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, FTX Token autocorrelation shows the relationship between FTX Token crypto coin current value and its past values and can show if there is a momentum factor associated with investing in FTX Token.
Regressed Prices |
| Timeline |
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FTX Token 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.