Jpmorgan Ultra Short Income Etf Market Value
| JPST Etf | 24.89 0.03 0.12% |
| 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.
| 12/23/2025 |
| 01/22/2026 |
If you would invest 0.00 in JPMorgan Ultra on December 23, 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 30 days. JPMorgan Ultra is related to or competes with JPMorgan Nasdaq, JPMorgan Equity, JPMorgan Growth, and JPMorgan Value. JPMorgan Ultra is entity of Canada. It is traded as Etf on TO exchange. 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 | 0.1306 | |||
| Information Ratio | (0.82) | |||
| Maximum Drawdown | 0.9658 | |||
| Value At Risk | (0.16) | |||
| Potential Upside | 0.2015 |
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 | (0.02) | |||
| Sortino Ratio | (0.73) | |||
| Treynor Ratio | (1.11) |
JPMorgan Ultra Short Backtested Returns
As of now, JPMorgan Etf is very steady. JPMorgan Ultra Short holds Efficiency (Sharpe) Ratio of 0.0623, which attests that the entity had a 0.0623 % return per unit of volatility over the last 3 months. We have found twenty-seven 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 (1.10), and Risk Adjusted Performance of (0.01) to validate if the risk estimate we provide is consistent with the expected return of 0.0073%. The etf retains a Market Volatility (i.e., Beta) of 0.0029, which attests to not very significant fluctuations relative to the market. As returns on the market increase, JPMorgan Ultra's returns are expected to increase less than the market. However, during the bear market, the loss of holding JPMorgan Ultra is expected to be smaller as well.
Auto-correlation | -0.59 |
Good reverse predictability
JPMorgan Ultra Short Income has good reverse predictability. Overlapping area represents the amount of predictability between JPMorgan Ultra time series from 23rd of December 2025 to 7th of January 2026 and 7th of January 2026 to 22nd 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 -0.59 indicates that roughly 59.0% of current JPMorgan Ultra price fluctuation can be explain by its past prices.
| Correlation Coefficient | -0.59 | |
| Spearman Rank Test | 0.05 | |
| Residual Average | 0.0 | |
| Price Variance | 0.0 |
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 Income.
Regressed Prices |
| Timeline |
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
| 0.66 | TCLB | TD Canadian Long | PairCorr |
| 0.61 | HBLK | Blockchain Technologies | PairCorr |
| 0.59 | CBCX | CI Galaxy Blockchain | PairCorr |
| 0.54 | XBB | iShares Canadian Universe | PairCorr |
| 0.53 | ZAG | BMO Aggregate Bond | 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 Premium Stories module to follow Macroaxis premium stories from verified contributors across different equity types, categories and coverage scope.
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.