Jpmorgan Ultra Short Income Etf Market Value
| JPST Etf | 24.88 0.01 0.04% |
| Symbol | JPMorgan |
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.
| 10/26/2025 |
| 01/24/2026 |
If you would invest 0.00 in JPMorgan Ultra on October 26, 2025 and sell it all today you would earn a total of 0.00 from holding JPMorgan Ultra Short Income or generate 0.0% return on investment in JPMorgan Ultra over 90 days. JPMorgan Ultra is related to or competes with JPMorgan Nasdaq, JPMorgan Equity, JPMorgan Growth, and JPMorgan Value. 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 Income upside and downside potential and time the market with a certain degree of confidence.
| Downside Deviation | 0.1348 | |||
| Information Ratio | (0.60) | |||
| Maximum Drawdown | 0.9658 | |||
| Value At Risk | (0.16) | |||
| Potential Upside | 0.1612 |
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 | (0.01) | |||
| Jensen Alpha | (0) | |||
| Total Risk Alpha | (0.01) | |||
| Sortino Ratio | (0.53) | |||
| Treynor Ratio | 0.3338 |
JPMorgan Ultra January 24, 2026 Technical Indicators
| Cycle Indicators | ||
| Math Operators | ||
| Math Transform | ||
| Momentum Indicators | ||
| Overlap Studies | ||
| Pattern Recognition | ||
| Price Transform | ||
| Statistic Functions | ||
| Volatility Indicators | ||
| Volume Indicators |
| Risk Adjusted Performance | (0.01) | |||
| Market Risk Adjusted Performance | 0.3438 | |||
| Mean Deviation | 0.07 | |||
| Semi Deviation | 0.0396 | |||
| Downside Deviation | 0.1348 | |||
| Coefficient Of Variation | 1605.91 | |||
| Standard Deviation | 0.1177 | |||
| Variance | 0.0139 | |||
| Information Ratio | (0.60) | |||
| Jensen Alpha | (0) | |||
| Total Risk Alpha | (0.01) | |||
| Sortino Ratio | (0.53) | |||
| Treynor Ratio | 0.3338 | |||
| Maximum Drawdown | 0.9658 | |||
| Value At Risk | (0.16) | |||
| Potential Upside | 0.1612 | |||
| Downside Variance | 0.0182 | |||
| Semi Variance | 0.0016 | |||
| Expected Short fall | (0.10) | |||
| Skewness | 0.5617 | |||
| Kurtosis | 8.51 |
JPMorgan Ultra Short Backtested Returns
As of now, JPMorgan Etf is very steady. JPMorgan Ultra Short holds Efficiency (Sharpe) Ratio of 0.0561, which attests that the entity had a 0.0561 % return per unit of volatility over the last 3 months. We have found twenty-eight technical indicators for JPMorgan Ultra Short, which you can use to evaluate the volatility of the entity. Please check out JPMorgan Ultra's market risk adjusted performance of 0.3438, and Risk Adjusted Performance of (0.01) to validate if the risk estimate we provide is consistent with the expected return of 0.0066%. The etf retains a Market Volatility (i.e., Beta) of -0.008, 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 | 0.11 |
Insignificant predictability
JPMorgan Ultra Short Income has insignificant predictability. Overlapping area represents the amount of predictability between JPMorgan Ultra time series from 26th of October 2025 to 10th of December 2025 and 10th of December 2025 to 24th of January 2026. 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 0.11 indicates that less than 11.0% of current JPMorgan Ultra price fluctuation can be explain by its past prices.
| Correlation Coefficient | 0.11 | |
| Spearman Rank Test | 0.65 | |
| Residual Average | 0.0 | |
| Price Variance | 0.0 |
Pair Trading with JPMorgan Ultra
One of the main advantages of trading using pair correlations is that every trade hedges away some risk. Because there are two separate transactions required, even if JPMorgan Ultra position performs unexpectedly, the other equity can make up some of the losses. Pair trading also minimizes risk from directional movements in the market. For example, if an entire industry or sector drops because of unexpected headlines, the short position in JPMorgan Ultra will appreciate offsetting losses from the drop in the long position's value.Moving together with JPMorgan Etf
Moving against JPMorgan Etf
| 0.53 | TCLB | TD Canadian Long | PairCorr |
| 0.37 | ZAG | BMO Aggregate Bond | PairCorr |
| 0.37 | HBLK | Blockchain Technologies | PairCorr |
| 0.36 | XBB | iShares Canadian Universe | PairCorr |
| 0.36 | CBCX | CI Galaxy Blockchain | PairCorr |
The ability to find closely correlated positions to JPMorgan Ultra could be a great tool in your tax-loss harvesting strategies, allowing investors a quick way to find a similar-enough asset to replace JPMorgan Ultra when you sell it. If you don't do this, your portfolio allocation will be skewed against your target asset allocation. So, investors can't just sell and buy back JPMorgan Ultra - that would be a violation of the tax code under the "wash sale" rule, and this is why you need to find a similar enough asset and use the proceeds from selling JPMorgan Ultra Short Income to buy it.
The correlation of JPMorgan Ultra is a statistical measure of how it moves in relation to other instruments. This measure is expressed in what is known as the correlation coefficient, which ranges between -1 and +1. A perfect positive correlation (i.e., a correlation coefficient of +1) implies that as JPMorgan Ultra moves, either up or down, the other security will move in the same direction. Alternatively, perfect negative correlation means that if JPMorgan Ultra Short moves in either direction, the perfectly negatively correlated security will move in the opposite direction. If the correlation is 0, the equities are not correlated; they are entirely random. A correlation greater than 0.8 is generally described as strong, whereas a correlation less than 0.5 is generally considered weak.
Correlation analysis and pair trading evaluation for JPMorgan Ultra can also be used as hedging techniques within a particular sector or industry or even over random equities to generate a better risk-adjusted return on your portfolios.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 My Watchlist Analysis module to analyze my current watchlist and to refresh optimization strategy. Macroaxis watchlist is based on self-learning algorithm to remember stocks you like.
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.