Fidelity Crypto Industry Etf Market Value
FDIG Etf | USD 39.66 1.98 5.25% |
Symbol | Fidelity |
The market value of Fidelity Crypto Industry is measured differently than its book value, which is the value of Fidelity that is recorded on the company's balance sheet. Investors also form their own opinion of Fidelity Crypto's value that differs from its market value or its book value, called intrinsic value, which is Fidelity Crypto's true underlying value. Investors use various methods to calculate intrinsic value and buy a stock when its market value falls below its intrinsic value. Because Fidelity Crypto's market value can be influenced by many factors that don't directly affect Fidelity Crypto's underlying business (such as a pandemic or basic market pessimism), market value can vary widely from intrinsic value.
Please note, there is a significant difference between Fidelity Crypto's value and its price as these two are different measures arrived at by different means. Investors typically determine if Fidelity Crypto is a good investment by looking at such factors as earnings, sales, fundamental and technical indicators, competition as well as analyst projections. However, Fidelity Crypto's price is the amount at which it trades on the open market and represents the number that a seller and buyer find agreeable to each party.
Fidelity Crypto '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 Fidelity Crypto's etf 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 Fidelity Crypto.
05/26/2025 |
| 08/24/2025 |
If you would invest 0.00 in Fidelity Crypto on May 26, 2025 and sell it all today you would earn a total of 0.00 from holding Fidelity Crypto Industry or generate 0.0% return on investment in Fidelity Crypto over 90 days. Fidelity Crypto is related to or competes with Fidelity Metaverse, IShares Blockchain, Fidelity Covington, Fidelity Covington, and Fidelity Covington. The fund ormally invests at least 80 percent of assets in equity securities included in the index and in depositary rece... More
Fidelity Crypto 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 Fidelity Crypto's etf 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 Fidelity Crypto Industry upside and downside potential and time the market with a certain degree of confidence.
Downside Deviation | 2.32 | |||
Information Ratio | 0.118 | |||
Maximum Drawdown | 12.92 | |||
Value At Risk | (3.26) | |||
Potential Upside | 4.48 |
Fidelity Crypto Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for Fidelity Crypto's investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as Fidelity Crypto's standard deviation. In reality, there are many statistical measures that can use Fidelity Crypto historical prices to predict the future Fidelity Crypto's volatility.Risk Adjusted Performance | 0.1243 | |||
Jensen Alpha | 0.2033 | |||
Total Risk Alpha | 0.0697 | |||
Sortino Ratio | 0.1301 | |||
Treynor Ratio | 0.1935 |
Fidelity Crypto Industry Backtested Returns
Fidelity Crypto appears to be very steady, given 3 months investment horizon. Fidelity Crypto Industry secures Sharpe Ratio (or Efficiency) of 0.16, which denotes the etf had a 0.16 % return per unit of risk over the last 3 months. We have found thirty technical indicators for Fidelity Crypto Industry, which you can use to evaluate the volatility of the entity. Please utilize Fidelity Crypto's Downside Deviation of 2.32, mean deviation of 2.07, and Coefficient Of Variation of 630.04 to check if our risk estimates are consistent with your expectations. The etf shows a Beta (market volatility) of 2.05, 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, Fidelity Crypto will likely underperform.
Auto-correlation | -0.08 |
Very weak reverse predictability
Fidelity Crypto Industry has very weak reverse predictability. Overlapping area represents the amount of predictability between Fidelity Crypto time series from 26th of May 2025 to 10th of July 2025 and 10th of July 2025 to 24th of August 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 Fidelity Crypto Industry price movement. The serial correlation of -0.08 indicates that barely 8.0% of current Fidelity Crypto price fluctuation can be explain by its past prices.
Correlation Coefficient | -0.08 | |
Spearman Rank Test | -0.35 | |
Residual Average | 0.0 | |
Price Variance | 1.74 |
Fidelity Crypto Industry lagged returns against current returns
Autocorrelation, which is Fidelity Crypto etf'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 Fidelity Crypto's etf expected returns. We can calculate the autocorrelation of Fidelity Crypto returns to help us make a trade decision. For example, suppose you find that Fidelity Crypto has exhibited high autocorrelation historically, and you observe that the etf 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 |
Fidelity Crypto 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 Fidelity Crypto etf is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if Fidelity Crypto etf is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in Fidelity Crypto etf over time.
Current vs Lagged Prices |
Timeline |
Fidelity Crypto Lagged Returns
When evaluating Fidelity Crypto's market value, investors can use the concept of autocorrelation to see how much of an impact past prices of Fidelity Crypto etf have on its future price. Fidelity Crypto 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, Fidelity Crypto autocorrelation shows the relationship between Fidelity Crypto etf current value and its past values and can show if there is a momentum factor associated with investing in Fidelity Crypto Industry.
Regressed Prices |
Timeline |
Currently Active Assets on Macroaxis
When determining whether Fidelity Crypto Industry is a strong investment it is important to analyze Fidelity Crypto's competitive position within its industry, examining market share, product or service uniqueness, and competitive advantages. Beyond financials and market position, potential investors should also consider broader economic conditions, industry trends, and any regulatory or geopolitical factors that may impact Fidelity Crypto's future performance. For an informed investment choice regarding Fidelity Etf, refer to the following important reports:Check out Fidelity Crypto Correlation, Fidelity Crypto Volatility and Fidelity Crypto Alpha and Beta module to complement your research on Fidelity Crypto. You can also try the Financial Widgets module to easily integrated Macroaxis content with over 30 different plug-and-play financial widgets.
Fidelity Crypto technical etf 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, etf market cycles, or different charting patterns.