Valkyrie Bitcoin Miners Etf Market Value
| WGMI Etf | USD 15.30 0.73 5.01% |
| Symbol | Valkyrie |
The market value of Valkyrie Bitcoin Miners is measured differently than its book value, which is the value of Valkyrie that is recorded on the company's balance sheet. Investors also form their own opinion of Valkyrie Bitcoin's value that differs from its market value or its book value, called intrinsic value, which is Valkyrie Bitcoin'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 Valkyrie Bitcoin's market value can be influenced by many factors that don't directly affect Valkyrie Bitcoin'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 Valkyrie Bitcoin's value and its price as these two are different measures arrived at by different means. Investors typically determine if Valkyrie Bitcoin is a good investment by looking at such factors as earnings, sales, fundamental and technical indicators, competition as well as analyst projections. However, Valkyrie Bitcoin'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.
Valkyrie Bitcoin '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 Valkyrie Bitcoin'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 Valkyrie Bitcoin.
| 12/15/2024 |
| 03/15/2025 |
If you would invest 0.00 in Valkyrie Bitcoin on December 15, 2024 and sell it all today you would earn a total of 0.00 from holding Valkyrie Bitcoin Miners or generate 0.0% return on investment in Valkyrie Bitcoin over 90 days. Valkyrie Bitcoin is related to or competes with VanEck Digital, Bitwise Crypto, Valkyrie Bitcoin, and Stronghold Digital. The fund is an actively-managed exchange-traded fund that will invest at least 80 percent of its net assets in securitie... More
Valkyrie Bitcoin 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 Valkyrie Bitcoin'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 Valkyrie Bitcoin Miners upside and downside potential and time the market with a certain degree of confidence.
| Information Ratio | (0.14) | |||
| Maximum Drawdown | 31.65 | |||
| Value At Risk | (10.84) | |||
| Potential Upside | 7.04 |
Valkyrie Bitcoin Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for Valkyrie Bitcoin's investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as Valkyrie Bitcoin's standard deviation. In reality, there are many statistical measures that can use Valkyrie Bitcoin historical prices to predict the future Valkyrie Bitcoin's volatility.| Risk Adjusted Performance | (0.13) | |||
| Jensen Alpha | (0.69) | |||
| Total Risk Alpha | 0.0188 | |||
| Treynor Ratio | (0.62) |
Valkyrie Bitcoin Miners Backtested Returns
Valkyrie Bitcoin Miners owns Efficiency Ratio (i.e., Sharpe Ratio) of -0.18, which indicates the etf had a -0.18 % return per unit of risk over the last 3 months. Valkyrie Bitcoin Miners exposes twenty-two different technical indicators, which can help you to evaluate volatility embedded in its price movement. Please validate Valkyrie Bitcoin's Risk Adjusted Performance of (0.13), coefficient of variation of (612.83), and Variance of 29.09 to confirm the risk estimate we provide. The entity has a beta of 1.44, which indicates 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, Valkyrie Bitcoin will likely underperform.
Auto-correlation | 0.26 |
Poor predictability
Valkyrie Bitcoin Miners has poor predictability. Overlapping area represents the amount of predictability between Valkyrie Bitcoin time series from 15th of December 2024 to 29th of January 2025 and 29th of January 2025 to 15th of March 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 Valkyrie Bitcoin Miners price movement. The serial correlation of 0.26 indicates that nearly 26.0% of current Valkyrie Bitcoin price fluctuation can be explain by its past prices.
| Correlation Coefficient | 0.26 | |
| Spearman Rank Test | 0.22 | |
| Residual Average | 0.0 | |
| Price Variance | 9.39 |
Valkyrie Bitcoin Miners lagged returns against current returns
Autocorrelation, which is Valkyrie Bitcoin 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 Valkyrie Bitcoin's etf expected returns. We can calculate the autocorrelation of Valkyrie Bitcoin returns to help us make a trade decision. For example, suppose you find that Valkyrie Bitcoin 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 |
Valkyrie Bitcoin 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 Valkyrie Bitcoin etf is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if Valkyrie Bitcoin etf is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in Valkyrie Bitcoin etf over time.
Current vs Lagged Prices |
| Timeline |
Valkyrie Bitcoin Lagged Returns
When evaluating Valkyrie Bitcoin's market value, investors can use the concept of autocorrelation to see how much of an impact past prices of Valkyrie Bitcoin etf have on its future price. Valkyrie Bitcoin 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, Valkyrie Bitcoin autocorrelation shows the relationship between Valkyrie Bitcoin etf current value and its past values and can show if there is a momentum factor associated with investing in Valkyrie Bitcoin Miners.
Regressed Prices |
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Currently Active Assets on Macroaxis
When determining whether Valkyrie Bitcoin Miners offers a strong return on investment in its stock, a comprehensive analysis is essential. The process typically begins with a thorough review of Valkyrie Bitcoin's financial statements, including income statements, balance sheets, and cash flow statements, to assess its financial health. Key financial ratios are used to gauge profitability, efficiency, and growth potential of Valkyrie Bitcoin Miners Etf. Outlined below are crucial reports that will aid in making a well-informed decision on Valkyrie Bitcoin Miners Etf:Check out Valkyrie Bitcoin Correlation, Valkyrie Bitcoin Volatility and Valkyrie Bitcoin Alpha and Beta module to complement your research on Valkyrie Bitcoin. You can also try the Theme Ratings module to determine theme ratings based on digital equity recommendations. Macroaxis theme ratings are based on combination of fundamental analysis and risk-adjusted market performance.
Valkyrie Bitcoin 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.