Jpmorgan Research Market Fund Market Value
| JMNAX Fund | USD 13.98 0.02 0.14% |
| Symbol | Jpmorgan |
Jpmorgan Research '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 Research's mutual fund 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 Research.
| 07/22/2023 |
| 04/17/2024 |
If you would invest 0.00 in Jpmorgan Research on July 22, 2023 and sell it all today you would earn a total of 0.00 from holding Jpmorgan Research Market or generate 0.0% return on investment in Jpmorgan Research over 270 days. Jpmorgan Research is related to or competes with Jpmorgan Smartretirement, Jpmorgan Smartretirement, Jpmorgan Smartretirement, Jpmorgan Smartretirement, Jpmorgan Smartretirement, Jpmorgan Smartretirement, and Jpmorgan Smartretirement. The fund takes long and short positions in different securities, selecting from a universe of mid- to large-capitalizati... More
Jpmorgan Research 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 Research's mutual fund 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 Research Market upside and downside potential and time the market with a certain degree of confidence.
| Downside Deviation | 0.3176 | |||
| Information Ratio | 0.055 | |||
| Maximum Drawdown | 1.69 | |||
| Value At Risk | (0.36) | |||
| Potential Upside | 0.5224 |
Jpmorgan Research Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for Jpmorgan Research's investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as Jpmorgan Research's standard deviation. In reality, there are many statistical measures that can use Jpmorgan Research historical prices to predict the future Jpmorgan Research's volatility.| Risk Adjusted Performance | 0.1505 | |||
| Jensen Alpha | 0.0627 | |||
| Total Risk Alpha | 0.042 | |||
| Sortino Ratio | 0.0496 | |||
| Treynor Ratio | 2.7 |
Sophisticated investors, who have witnessed many market ups and downs, anticipate that the market will even out over time. This tendency of Jpmorgan Research'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 Research Market Backtested Returns
We consider Jpmorgan Research very steady. Jpmorgan Research Market holds Efficiency (Sharpe) Ratio of 0.24, which attests that the entity had a 0.24% return per unit of risk over the last 3 months. We have found twenty-seven technical indicators for Jpmorgan Research Market, which you can use to evaluate the volatility of the entity. Please check out Jpmorgan Research's Risk Adjusted Performance of 0.1505, market risk adjusted performance of 2.71, and Coefficient Of Variation of 387.91 to validate if the risk estimate we provide is consistent with the expected return of 0.0714%. The fund retains a Market Volatility (i.e., Beta) of 0.0236, which attests to not very significant fluctuations relative to the market. As returns on the market increase, Jpmorgan Research's returns are expected to increase less than the market. However, during the bear market, the loss of holding Jpmorgan Research is expected to be smaller as well.
Auto-correlation | 0.89 |
Very good predictability
Jpmorgan Research Market has very good predictability. Overlapping area represents the amount of predictability between Jpmorgan Research time series from 22nd of July 2023 to 4th of December 2023 and 4th of December 2023 to 17th of April 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 Research Market price movement. The serial correlation of 0.89 indicates that approximately 89.0% of current Jpmorgan Research price fluctuation can be explain by its past prices.
| Correlation Coefficient | 0.89 | |
| Spearman Rank Test | 0.93 | |
| Residual Average | 0.0 | |
| Price Variance | 0.07 |
Jpmorgan Research Market lagged returns against current returns
Autocorrelation, which is Jpmorgan Research mutual fund'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 Research's mutual fund expected returns. We can calculate the autocorrelation of Jpmorgan Research returns to help us make a trade decision. For example, suppose you find that Jpmorgan Research has exhibited high autocorrelation historically, and you observe that the mutual fund 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 Research 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 Research mutual fund is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if Jpmorgan Research mutual fund is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in Jpmorgan Research mutual fund over time.
Current vs Lagged Prices |
| Timeline |
Jpmorgan Research Lagged Returns
When evaluating Jpmorgan Research's market value, investors can use the concept of autocorrelation to see how much of an impact past prices of Jpmorgan Research mutual fund have on its future price. Jpmorgan Research 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 Research autocorrelation shows the relationship between Jpmorgan Research mutual fund current value and its past values and can show if there is a momentum factor associated with investing in Jpmorgan Research Market.
Regressed Prices |
| Timeline |
Building efficient market-beating portfolios requires time, education, and a lot of computing power!
The Portfolio Architect is an AI-driven system that provides multiple benefits to our users by leveraging cutting-edge machine learning algorithms, statistical analysis, and predictive modeling to automate the process of asset selection and portfolio construction, saving time and reducing human error for individual and institutional investors.
Try AI Portfolio ArchitectCheck out Jpmorgan Research Correlation, Jpmorgan Research Volatility and Jpmorgan Research Alpha and Beta module to complement your research on Jpmorgan Research. Note that the Jpmorgan Research Market information on this page should be used as a complementary analysis to other Jpmorgan Research's statistical models used to find the right mix of equity instruments to add to your existing portfolios or create a brand new portfolio. You can also try the Portfolio Dashboard module to portfolio dashboard that provides centralized access to all your investments.
Jpmorgan Research technical mutual fund 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, fund market cycles, or different charting patterns.