Trust For Professional Etf Market Value
| JGRW Etf | 27.07 0.09 0.33% |
| Symbol | Trust |
The market value of Trust For Professional is measured differently than its book value, which is the value of Trust that is recorded on the company's balance sheet. Investors also form their own opinion of Trust For's value that differs from its market value or its book value, called intrinsic value, which is Trust For'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 Trust For's market value can be influenced by many factors that don't directly affect Trust For'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 Trust For's value and its price as these two are different measures arrived at by different means. Investors typically determine if Trust For is a good investment by looking at such factors as earnings, sales, fundamental and technical indicators, competition as well as analyst projections. However, Trust For'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.
Trust For '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 Trust For'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 Trust For.
| 11/01/2024 |
| 12/01/2024 |
If you would invest 0.00 in Trust For on November 1, 2024 and sell it all today you would earn a total of 0.00 from holding Trust For Professional or generate 0.0% return on investment in Trust For over 30 days. Trust For is related to or competes with Vanguard Growth, IShares Russell, IShares SP, IShares Core, Vanguard Mega, Vanguard Russell, and IShares MSCI. Trust For is entity of United States. It is traded as Etf on NYSE ARCA exchange. More
Trust For 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 Trust For'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 Trust For Professional upside and downside potential and time the market with a certain degree of confidence.
| Downside Deviation | 0.7222 | |||
| Information Ratio | (0.12) | |||
| Maximum Drawdown | 2.98 | |||
| Value At Risk | (1.25) | |||
| Potential Upside | 1.1 |
Trust For Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for Trust For's investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as Trust For's standard deviation. In reality, there are many statistical measures that can use Trust For historical prices to predict the future Trust For's volatility.| Risk Adjusted Performance | 0.0652 | |||
| Jensen Alpha | (0.04) | |||
| Total Risk Alpha | (0.06) | |||
| Sortino Ratio | (0.11) | |||
| Treynor Ratio | 0.0733 |
Trust For Professional Backtested Returns
At this stage we consider Trust Etf to be very steady. Trust For Professional owns Efficiency Ratio (i.e., Sharpe Ratio) of 0.1, which indicates the etf had a 0.1% return per unit of risk over the last 3 months. We have found thirty technical indicators for Trust For Professional, which you can use to evaluate the volatility of the etf. Please validate Trust For's Semi Deviation of 0.6275, risk adjusted performance of 0.0652, and Coefficient Of Variation of 1148.68 to confirm if the risk estimate we provide is consistent with the expected return of 0.0664%. The entity has a beta of 0.66, which indicates possible diversification benefits within a given portfolio. As returns on the market increase, Trust For's returns are expected to increase less than the market. However, during the bear market, the loss of holding Trust For is expected to be smaller as well.
Auto-correlation | 0.92 |
Excellent predictability
Trust For Professional has excellent predictability. Overlapping area represents the amount of predictability between Trust For time series from 1st of November 2024 to 16th of November 2024 and 16th of November 2024 to 1st of December 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 Trust For Professional price movement. The serial correlation of 0.92 indicates that approximately 92.0% of current Trust For price fluctuation can be explain by its past prices.
| Correlation Coefficient | 0.92 | |
| Spearman Rank Test | 0.84 | |
| Residual Average | 0.0 | |
| Price Variance | 0.09 |
Trust For Professional lagged returns against current returns
Autocorrelation, which is Trust For 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 Trust For's etf expected returns. We can calculate the autocorrelation of Trust For returns to help us make a trade decision. For example, suppose you find that Trust For 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 |
Trust For 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 Trust For etf is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if Trust For etf is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in Trust For etf over time.
Current vs Lagged Prices |
| Timeline |
Trust For Lagged Returns
When evaluating Trust For's market value, investors can use the concept of autocorrelation to see how much of an impact past prices of Trust For etf have on its future price. Trust For 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, Trust For autocorrelation shows the relationship between Trust For etf current value and its past values and can show if there is a momentum factor associated with investing in Trust For Professional.
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 Trust For Professional is a strong investment it is important to analyze Trust For'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 Trust For's future performance. For an informed investment choice regarding Trust Etf, refer to the following important reports:Check out Trust For Correlation, Trust For Volatility and Trust For Alpha and Beta module to complement your research on Trust For. You can also try the Alpha Finder module to use alpha and beta coefficients to find investment opportunities after accounting for the risk.
Trust For 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.