Jpmorgan Equity Premium Etf Market Value
JEPI Etf | USD 60.50 0.34 0.57% |
Symbol | JPMorgan |
The market value of JPMorgan Equity Premium 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 Equity's value that differs from its market value or its book value, called intrinsic value, which is JPMorgan Equity'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 Equity's market value can be influenced by many factors that don't directly affect JPMorgan Equity'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 Equity's value and its price as these two are different measures arrived at by different means. Investors typically determine if JPMorgan Equity is a good investment by looking at such factors as earnings, sales, fundamental and technical indicators, competition as well as analyst projections. However, JPMorgan Equity'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 Equity '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 Equity'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 Equity.
12/07/2022 |
| 11/26/2024 |
If you would invest 0.00 in JPMorgan Equity on December 7, 2022 and sell it all today you would earn a total of 0.00 from holding JPMorgan Equity Premium or generate 0.0% return on investment in JPMorgan Equity over 720 days. JPMorgan Equity is related to or competes with JPMorgan Nasdaq, Global X, Schwab Dividend, Global X, and Global X. The fund seeks to provide the majority of the returns associated with its primary benchmark, the Standard Poors 500 Tota... More
JPMorgan Equity 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 Equity'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 Equity Premium upside and downside potential and time the market with a certain degree of confidence.
Downside Deviation | 0.3734 | |||
Information Ratio | (0.10) | |||
Maximum Drawdown | 2.06 | |||
Value At Risk | (0.57) | |||
Potential Upside | 0.7229 |
JPMorgan Equity Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for JPMorgan Equity's investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as JPMorgan Equity's standard deviation. In reality, there are many statistical measures that can use JPMorgan Equity historical prices to predict the future JPMorgan Equity's volatility.Risk Adjusted Performance | 0.1633 | |||
Jensen Alpha | 0.0243 | |||
Total Risk Alpha | 0.0169 | |||
Sortino Ratio | (0.11) | |||
Treynor Ratio | 0.1737 |
JPMorgan Equity Premium Backtested Returns
JPMorgan Equity is very steady at the moment. JPMorgan Equity Premium holds Efficiency (Sharpe) Ratio of 0.22, which attests that the entity had a 0.22% return per unit of volatility over the last 3 months. We have found twenty-nine technical indicators for JPMorgan Equity Premium, which you can use to evaluate the volatility of the entity. Please check out JPMorgan Equity's market risk adjusted performance of 0.1837, and Risk Adjusted Performance of 0.1633 to validate if the risk estimate we provide is consistent with the expected return of 0.0913%. The etf retains a Market Volatility (i.e., Beta) of 0.46, which attests to possible diversification benefits within a given portfolio. As returns on the market increase, JPMorgan Equity's returns are expected to increase less than the market. However, during the bear market, the loss of holding JPMorgan Equity is expected to be smaller as well.
Auto-correlation | 0.60 |
Good predictability
JPMorgan Equity Premium has good predictability. Overlapping area represents the amount of predictability between JPMorgan Equity time series from 7th of December 2022 to 2nd of December 2023 and 2nd of December 2023 to 26th 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 Equity Premium price movement. The serial correlation of 0.6 indicates that roughly 60.0% of current JPMorgan Equity price fluctuation can be explain by its past prices.
Correlation Coefficient | 0.6 | |
Spearman Rank Test | 0.76 | |
Residual Average | 0.0 | |
Price Variance | 5.97 |
JPMorgan Equity Premium lagged returns against current returns
Autocorrelation, which is JPMorgan Equity 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 Equity's etf expected returns. We can calculate the autocorrelation of JPMorgan Equity returns to help us make a trade decision. For example, suppose you find that JPMorgan Equity 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 Equity 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 Equity etf is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if JPMorgan Equity etf is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in JPMorgan Equity etf over time.
Current vs Lagged Prices |
Timeline |
JPMorgan Equity Lagged Returns
When evaluating JPMorgan Equity's market value, investors can use the concept of autocorrelation to see how much of an impact past prices of JPMorgan Equity etf have on its future price. JPMorgan Equity 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 Equity autocorrelation shows the relationship between JPMorgan Equity etf current value and its past values and can show if there is a momentum factor associated with investing in JPMorgan Equity Premium.
Regressed Prices |
Timeline |
Currently Active Assets on Macroaxis
When determining whether JPMorgan Equity Premium offers a strong return on investment in its stock, a comprehensive analysis is essential. The process typically begins with a thorough review of JPMorgan Equity's financial statements, including income statements, balance sheets, and cash flow statements, to assess its financial health. Key financial ratios are used to gauge profitability, efficiency, and growth potential of Jpmorgan Equity Premium Etf. Outlined below are crucial reports that will aid in making a well-informed decision on Jpmorgan Equity Premium Etf:Check out JPMorgan Equity Correlation, JPMorgan Equity Volatility and JPMorgan Equity Alpha and Beta module to complement your research on JPMorgan Equity. You can also try the Commodity Channel module to use Commodity Channel Index to analyze current equity momentum.
JPMorgan Equity 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.