Gabelli Etfs Trust Etf Market Value
| GCAD Etf | 33.66 0.60 1.75% |
| Symbol | Gabelli |
The market value of Gabelli ETFs Trust is measured differently than its book value, which is the value of Gabelli that is recorded on the company's balance sheet. Investors also form their own opinion of Gabelli ETFs' value that differs from its market value or its book value, called intrinsic value, which is Gabelli ETFs' 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 Gabelli ETFs' market value can be influenced by many factors that don't directly affect Gabelli ETFs' 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 Gabelli ETFs' value and its price as these two are different measures arrived at by different means. Investors typically determine if Gabelli ETFs is a good investment by looking at such factors as earnings, sales, fundamental and technical indicators, competition as well as analyst projections. However, Gabelli ETFs' 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.
Gabelli ETFs '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 Gabelli ETFs' 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 Gabelli ETFs.
| 02/03/2025 |
| 03/05/2025 |
If you would invest 0.00 in Gabelli ETFs on February 3, 2025 and sell it all today you would earn a total of 0.00 from holding Gabelli ETFs Trust or generate 0.0% return on investment in Gabelli ETFs over 30 days. Gabelli ETFs is related to or competes with Ultimus Managers, American Beacon, First Trust, Direxion Daily, Direxion Daily, EA Series, and Global X. More
Gabelli ETFs 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 Gabelli ETFs' 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 Gabelli ETFs Trust upside and downside potential and time the market with a certain degree of confidence.
| Information Ratio | 0.0017 | |||
| Maximum Drawdown | 5.2 | |||
| Value At Risk | (1.67) | |||
| Potential Upside | 1.34 |
Gabelli ETFs Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for Gabelli ETFs' investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as Gabelli ETFs' standard deviation. In reality, there are many statistical measures that can use Gabelli ETFs historical prices to predict the future Gabelli ETFs' volatility.| Risk Adjusted Performance | (0.05) | |||
| Jensen Alpha | (0.03) | |||
| Total Risk Alpha | 0.0377 | |||
| Treynor Ratio | (0.13) |
Gabelli ETFs Trust Backtested Returns
Gabelli ETFs Trust holds Efficiency (Sharpe) Ratio of -0.0566, which attests that the entity had a -0.0566 % return per unit of standard deviation over the last 3 months. Gabelli ETFs Trust exposes twenty-three different technical indicators, which can help you to evaluate volatility embedded in its price movement. Please check out Gabelli ETFs' risk adjusted performance of (0.05), and Market Risk Adjusted Performance of (0.12) to validate the risk estimate we provide. The etf retains a Market Volatility (i.e., Beta) of 0.67, which attests to possible diversification benefits within a given portfolio. As returns on the market increase, Gabelli ETFs' returns are expected to increase less than the market. However, during the bear market, the loss of holding Gabelli ETFs is expected to be smaller as well.
Auto-correlation | 0.23 |
Weak predictability
Gabelli ETFs Trust has weak predictability. Overlapping area represents the amount of predictability between Gabelli ETFs time series from 3rd of February 2025 to 18th of February 2025 and 18th of February 2025 to 5th 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 Gabelli ETFs Trust price movement. The serial correlation of 0.23 indicates that over 23.0% of current Gabelli ETFs price fluctuation can be explain by its past prices.
| Correlation Coefficient | 0.23 | |
| Spearman Rank Test | 0.27 | |
| Residual Average | 0.0 | |
| Price Variance | 0.32 |
Gabelli ETFs Trust lagged returns against current returns
Autocorrelation, which is Gabelli ETFs 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 Gabelli ETFs' etf expected returns. We can calculate the autocorrelation of Gabelli ETFs returns to help us make a trade decision. For example, suppose you find that Gabelli ETFs 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 |
Gabelli ETFs 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 Gabelli ETFs etf is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if Gabelli ETFs etf is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in Gabelli ETFs etf over time.
Current vs Lagged Prices |
| Timeline |
Gabelli ETFs Lagged Returns
When evaluating Gabelli ETFs' market value, investors can use the concept of autocorrelation to see how much of an impact past prices of Gabelli ETFs etf have on its future price. Gabelli ETFs 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, Gabelli ETFs autocorrelation shows the relationship between Gabelli ETFs etf current value and its past values and can show if there is a momentum factor associated with investing in Gabelli ETFs Trust.
Regressed Prices |
| Timeline |
Also Currently Popular
Analyzing currently trending equities could be an opportunity to develop a better portfolio based on different market momentums that they can trigger. Utilizing the top trending stocks is also useful when creating a market-neutral strategy or pair trading technique involving a short or a long position in a currently trending equity.When determining whether Gabelli ETFs Trust is a good investment, qualitative aspects like company management, corporate governance, and ethical practices play a significant role. A comparison with peer companies also provides context and helps to understand if Gabelli Etf is undervalued or overvalued. This multi-faceted approach, blending both quantitative and qualitative analysis, forms a solid foundation for making an informed investment decision about Gabelli Etfs Trust Etf. Highlighted below are key reports to facilitate an investment decision about Gabelli Etfs Trust Etf:Check out Gabelli ETFs Correlation, Gabelli ETFs Volatility and Gabelli ETFs Alpha and Beta module to complement your research on Gabelli ETFs. You can also try the Stock Screener module to find equities using a custom stock filter or screen asymmetry in trading patterns, price, volume, or investment outlook..
Gabelli ETFs 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.