Jpmorgan Ultra Short Municipal Etf Market Value
| JMST Etf | USD 50.84 0.02 0.04% |
| Symbol | JPMorgan |
The market value of JPMorgan Ultra Short is measured differently than its book value, which is the value of JPMorgan that is recorded on the company's balance sheet. Investors also form their own opinion of JPMorgan Ultra's value that differs from its market value or its book value, called intrinsic value, which is JPMorgan Ultra'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 JPMorgan Ultra's market value can be influenced by many factors that don't directly affect JPMorgan Ultra'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 JPMorgan Ultra's value and its price as these two are different measures arrived at by different means. Investors typically determine if JPMorgan Ultra is a good investment by looking at such factors as earnings, sales, fundamental and technical indicators, competition as well as analyst projections. However, JPMorgan Ultra'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.
JPMorgan Ultra '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 JPMorgan Ultra'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 JPMorgan Ultra.
| 01/04/2023 |
| 11/24/2024 |
If you would invest 0.00 in JPMorgan Ultra on January 4, 2023 and sell it all today you would earn a total of 0.00 from holding JPMorgan Ultra Short Municipal or generate 0.0% return on investment in JPMorgan Ultra over 690 days. JPMorgan Ultra is related to or competes with Dimensional ETF, Dimensional ETF, Dimensional ETF, Dimensional Emerging, and Dimensional World. Under normal circumstances, the fund invests at least 80 percent of its assets in municipal securities, the income from ... More
JPMorgan Ultra 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 JPMorgan Ultra'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 JPMorgan Ultra Short Municipal upside and downside potential and time the market with a certain degree of confidence.
| Downside Deviation | 0.0515 | |||
| Information Ratio | (2.86) | |||
| Maximum Drawdown | 0.2171 | |||
| Value At Risk | (0.04) | |||
| Potential Upside | 0.0594 |
JPMorgan Ultra Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for JPMorgan Ultra's investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as JPMorgan Ultra's standard deviation. In reality, there are many statistical measures that can use JPMorgan Ultra historical prices to predict the future JPMorgan Ultra's volatility.| Risk Adjusted Performance | 0.0132 | |||
| Jensen Alpha | 0.0023 | |||
| Total Risk Alpha | (0.01) | |||
| Sortino Ratio | (2.34) | |||
| Treynor Ratio | (0.01) |
Sophisticated investors, who have witnessed many market ups and downs, anticipate that the market will even out over time. This tendency of JPMorgan Ultra'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.
JPMorgan Ultra Short Backtested Returns
Currently, JPMorgan Ultra Short Municipal is very steady. JPMorgan Ultra Short holds Efficiency (Sharpe) Ratio of 0.24, which attests that the entity had a 0.24% return per unit of volatility over the last 3 months. We have found twenty-nine technical indicators for JPMorgan Ultra Short, which you can use to evaluate the volatility of the entity. Please check out JPMorgan Ultra's risk adjusted performance of 0.0132, and Market Risk Adjusted Performance of (0.0001) to validate if the risk estimate we provide is consistent with the expected return of 0.0103%. The etf retains a Market Volatility (i.e., Beta) of -0.0174, which attests to not very significant fluctuations relative to the market. As returns on the market increase, returns on owning JPMorgan Ultra are expected to decrease at a much lower rate. During the bear market, JPMorgan Ultra is likely to outperform the market.
Auto-correlation | 0.96 |
Excellent predictability
JPMorgan Ultra Short Municipal has excellent predictability. Overlapping area represents the amount of predictability between JPMorgan Ultra time series from 4th of January 2023 to 15th of December 2023 and 15th of December 2023 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 JPMorgan Ultra Short price movement. The serial correlation of 0.96 indicates that 96.0% of current JPMorgan Ultra price fluctuation can be explain by its past prices.
| Correlation Coefficient | 0.96 | |
| Spearman Rank Test | 0.99 | |
| Residual Average | 0.0 | |
| Price Variance | 0.25 |
JPMorgan Ultra Short lagged returns against current returns
Autocorrelation, which is JPMorgan Ultra 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 JPMorgan Ultra's etf expected returns. We can calculate the autocorrelation of JPMorgan Ultra returns to help us make a trade decision. For example, suppose you find that JPMorgan Ultra 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 |
JPMorgan Ultra 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 JPMorgan Ultra etf is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if JPMorgan Ultra etf is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in JPMorgan Ultra etf over time.
Current vs Lagged Prices |
| Timeline |
JPMorgan Ultra Lagged Returns
When evaluating JPMorgan Ultra's market value, investors can use the concept of autocorrelation to see how much of an impact past prices of JPMorgan Ultra etf have on its future price. JPMorgan Ultra 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, JPMorgan Ultra autocorrelation shows the relationship between JPMorgan Ultra etf current value and its past values and can show if there is a momentum factor associated with investing in JPMorgan Ultra Short Municipal.
Regressed Prices |
| Timeline |
Thematic Opportunities
Explore Investment Opportunities
Check out JPMorgan Ultra Correlation, JPMorgan Ultra Volatility and JPMorgan Ultra Alpha and Beta module to complement your research on JPMorgan Ultra. You can also try the Portfolio Dashboard module to portfolio dashboard that provides centralized access to all your investments.
JPMorgan Ultra 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.