Uscf Etf Trust Etf Market Value
| UDI Etf | USD 31.04 0.36 1.17% |
| Symbol | USCF |
The market value of USCF ETF Trust is measured differently than its book value, which is the value of USCF that is recorded on the company's balance sheet. Investors also form their own opinion of USCF ETF's value that differs from its market value or its book value, called intrinsic value, which is USCF ETF'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 USCF ETF's market value can be influenced by many factors that don't directly affect USCF ETF'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 USCF ETF's value and its price as these two are different measures arrived at by different means. Investors typically determine if USCF ETF is a good investment by looking at such factors as earnings, sales, fundamental and technical indicators, competition as well as analyst projections. However, USCF ETF'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.
USCF ETF '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 USCF ETF'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 USCF ETF.
| 05/28/2024 |
| 11/24/2024 |
If you would invest 0.00 in USCF ETF on May 28, 2024 and sell it all today you would earn a total of 0.00 from holding USCF ETF Trust or generate 0.0% return on investment in USCF ETF over 180 days. USCF ETF is related to or competes with Franklin Templeton, Altrius Global, Invesco Exchange, Franklin International, Madison ETFs, Amplify CWP, and Advisors Inner. USCF ETF is entity of United States. It is traded as Etf on NYSE ARCA exchange. More
USCF ETF 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 USCF ETF'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 USCF ETF Trust upside and downside potential and time the market with a certain degree of confidence.
| Downside Deviation | 0.6326 | |||
| Information Ratio | (0.01) | |||
| Maximum Drawdown | 4.8 | |||
| Value At Risk | (0.86) | |||
| Potential Upside | 1.17 |
USCF ETF Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for USCF ETF's investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as USCF ETF's standard deviation. In reality, there are many statistical measures that can use USCF ETF historical prices to predict the future USCF ETF's volatility.| Risk Adjusted Performance | 0.1186 | |||
| Jensen Alpha | 0.0018 | |||
| Total Risk Alpha | (0.01) | |||
| Sortino Ratio | (0.01) | |||
| Treynor Ratio | 0.1228 |
Sophisticated investors, who have witnessed many market ups and downs, anticipate that the market will even out over time. This tendency of USCF ETF'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.
USCF ETF Trust Backtested Returns
USCF ETF is very steady at the moment. USCF ETF Trust retains Efficiency (Sharpe Ratio) of 0.12, which indicates the etf had a 0.12% return per unit of volatility over the last 3 months. We have found twenty-eight technical indicators for USCF ETF, which you can use to evaluate the volatility of the etf. Please validate USCF ETF's risk adjusted performance of 0.1186, and Downside Deviation of 0.6326 to confirm if the risk estimate we provide is consistent with the expected return of 0.0965%. The entity owns a Beta (Systematic Risk) of 0.92, which indicates possible diversification benefits within a given portfolio. USCF ETF returns are very sensitive to returns on the market. As the market goes up or down, USCF ETF is expected to follow.
Auto-correlation | 0.77 |
Good predictability
USCF ETF Trust has good predictability. Overlapping area represents the amount of predictability between USCF ETF time series from 28th of May 2024 to 26th of August 2024 and 26th of August 2024 to 24th of November 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 USCF ETF Trust price movement. The serial correlation of 0.77 indicates that around 77.0% of current USCF ETF price fluctuation can be explain by its past prices.
| Correlation Coefficient | 0.77 | |
| Spearman Rank Test | 0.76 | |
| Residual Average | 0.0 | |
| Price Variance | 0.34 |
USCF ETF Trust lagged returns against current returns
Autocorrelation, which is USCF ETF 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 USCF ETF's etf expected returns. We can calculate the autocorrelation of USCF ETF returns to help us make a trade decision. For example, suppose you find that USCF ETF 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 |
USCF ETF 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 USCF ETF etf is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if USCF ETF etf is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in USCF ETF etf over time.
Current vs Lagged Prices |
| Timeline |
USCF ETF Lagged Returns
When evaluating USCF ETF's market value, investors can use the concept of autocorrelation to see how much of an impact past prices of USCF ETF etf have on its future price. USCF ETF 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, USCF ETF autocorrelation shows the relationship between USCF ETF etf current value and its past values and can show if there is a momentum factor associated with investing in USCF ETF Trust.
Regressed Prices |
| Timeline |
Currently Active Assets on Macroaxis
When determining whether USCF ETF Trust offers a strong return on investment in its stock, a comprehensive analysis is essential. The process typically begins with a thorough review of USCF ETF'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 Uscf Etf Trust Etf. Outlined below are crucial reports that will aid in making a well-informed decision on Uscf Etf Trust Etf:Check out USCF ETF Correlation, USCF ETF Volatility and USCF ETF Alpha and Beta module to complement your research on USCF ETF. You can also try the Global Markets Map module to get a quick overview of global market snapshot using zoomable world map. Drill down to check world indexes.
USCF ETF 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.