Jpmorgan Momentum Factor Etf Market Value
JMOM Etf | USD 61.47 0.30 0.49% |
Symbol | JPMorgan |
The market value of JPMorgan Momentum Factor 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 Momentum's value that differs from its market value or its book value, called intrinsic value, which is JPMorgan Momentum'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 Momentum's market value can be influenced by many factors that don't directly affect JPMorgan Momentum'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 Momentum's value and its price as these two are different measures arrived at by different means. Investors typically determine if JPMorgan Momentum is a good investment by looking at such factors as earnings, sales, fundamental and technical indicators, competition as well as analyst projections. However, JPMorgan Momentum'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 Momentum '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 Momentum'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 Momentum.
10/28/2024 |
| 11/27/2024 |
If you would invest 0.00 in JPMorgan Momentum on October 28, 2024 and sell it all today you would earn a total of 0.00 from holding JPMorgan Momentum Factor or generate 0.0% return on investment in JPMorgan Momentum over 30 days. JPMorgan Momentum is related to or competes with JPMorgan Quality, JPMorgan Value, JPMorgan Diversified, JPMorgan Diversified, and Invesco SP. The fund will invest at least 80 percent of its assets in securities included in the underlying index More
JPMorgan Momentum 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 Momentum'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 Momentum Factor upside and downside potential and time the market with a certain degree of confidence.
Downside Deviation | 0.8788 | |||
Information Ratio | 0.0425 | |||
Maximum Drawdown | 4.08 | |||
Value At Risk | (1.27) | |||
Potential Upside | 1.18 |
JPMorgan Momentum Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for JPMorgan Momentum's investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as JPMorgan Momentum's standard deviation. In reality, there are many statistical measures that can use JPMorgan Momentum historical prices to predict the future JPMorgan Momentum's volatility.Risk Adjusted Performance | 0.1483 | |||
Jensen Alpha | 0.0422 | |||
Total Risk Alpha | 0.0204 | |||
Sortino Ratio | 0.0421 | |||
Treynor Ratio | 0.1645 |
JPMorgan Momentum Factor Backtested Returns
As of now, JPMorgan Etf is not too volatile. JPMorgan Momentum Factor holds Efficiency (Sharpe) Ratio of 0.2, which attests that the entity had a 0.2% return per unit of volatility over the last 3 months. We have found thirty technical indicators for JPMorgan Momentum Factor, which you can use to evaluate the volatility of the entity. Please check out JPMorgan Momentum's market risk adjusted performance of 0.1745, and Risk Adjusted Performance of 0.1483 to validate if the risk estimate we provide is consistent with the expected return of 0.17%. The etf retains a Market Volatility (i.e., Beta) of 0.96, which attests to possible diversification benefits within a given portfolio. JPMorgan Momentum returns are very sensitive to returns on the market. As the market goes up or down, JPMorgan Momentum is expected to follow.
Auto-correlation | 0.94 |
Excellent predictability
JPMorgan Momentum Factor has excellent predictability. Overlapping area represents the amount of predictability between JPMorgan Momentum time series from 28th of October 2024 to 12th of November 2024 and 12th of November 2024 to 27th 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 Momentum Factor price movement. The serial correlation of 0.94 indicates that approximately 94.0% of current JPMorgan Momentum price fluctuation can be explain by its past prices.
Correlation Coefficient | 0.94 | |
Spearman Rank Test | 0.54 | |
Residual Average | 0.0 | |
Price Variance | 0.59 |
JPMorgan Momentum Factor lagged returns against current returns
Autocorrelation, which is JPMorgan Momentum 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 Momentum's etf expected returns. We can calculate the autocorrelation of JPMorgan Momentum returns to help us make a trade decision. For example, suppose you find that JPMorgan Momentum 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 Momentum 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 Momentum etf is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if JPMorgan Momentum etf is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in JPMorgan Momentum etf over time.
Current vs Lagged Prices |
Timeline |
JPMorgan Momentum Lagged Returns
When evaluating JPMorgan Momentum's market value, investors can use the concept of autocorrelation to see how much of an impact past prices of JPMorgan Momentum etf have on its future price. JPMorgan Momentum 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 Momentum autocorrelation shows the relationship between JPMorgan Momentum etf current value and its past values and can show if there is a momentum factor associated with investing in JPMorgan Momentum Factor.
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 Momentum Correlation, JPMorgan Momentum Volatility and JPMorgan Momentum Alpha and Beta module to complement your research on JPMorgan Momentum. You can also try the FinTech Suite module to use AI to screen and filter profitable investment opportunities.
JPMorgan Momentum 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.