Jpmorgan Fundamental Data Etf Market Value
| SCDS Etf | 50.96 1.12 2.25% |
| Symbol | JPMorgan |
The market value of JPMorgan Fundamental Data 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 Fundamental's value that differs from its market value or its book value, called intrinsic value, which is JPMorgan Fundamental'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 Fundamental's market value can be influenced by many factors that don't directly affect JPMorgan Fundamental'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 Fundamental's value and its price as these two are different measures arrived at by different means. Investors typically determine if JPMorgan Fundamental is a good investment by looking at such factors as earnings, sales, fundamental and technical indicators, competition as well as analyst projections. However, JPMorgan Fundamental'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 Fundamental '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 Fundamental'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 Fundamental.
| 12/17/2024 |
| 03/17/2025 |
If you would invest 0.00 in JPMorgan Fundamental on December 17, 2024 and sell it all today you would earn a total of 0.00 from holding JPMorgan Fundamental Data or generate 0.0% return on investment in JPMorgan Fundamental over 90 days. JPMorgan Fundamental is related to or competes with IShares ESG, IShares ESG, IShares ESG, IShares ESG, and IShares ESG. More
JPMorgan Fundamental 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 Fundamental'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 Fundamental Data upside and downside potential and time the market with a certain degree of confidence.
| Information Ratio | (0.11) | |||
| Maximum Drawdown | 4.91 | |||
| Value At Risk | (2.45) | |||
| Potential Upside | 1.35 |
JPMorgan Fundamental Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for JPMorgan Fundamental's investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as JPMorgan Fundamental's standard deviation. In reality, there are many statistical measures that can use JPMorgan Fundamental historical prices to predict the future JPMorgan Fundamental's volatility.| Risk Adjusted Performance | (0.17) | |||
| Jensen Alpha | (0.14) | |||
| Total Risk Alpha | (0.09) | |||
| Treynor Ratio | (0.25) |
Sophisticated investors, who have witnessed many market ups and downs, anticipate that the market will even out over time. This tendency of JPMorgan Fundamental'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 Fundamental Data Backtested Returns
JPMorgan Fundamental Data holds Efficiency (Sharpe) Ratio of -0.16, which attests that the entity had a -0.16 % return per unit of volatility over the last 3 months. JPMorgan Fundamental Data exposes twenty-four different technical indicators, which can help you to evaluate volatility embedded in its price movement. Please check out JPMorgan Fundamental's market risk adjusted performance of (0.24), and Risk Adjusted Performance of (0.17) to validate the risk estimate we provide. The etf retains a Market Volatility (i.e., Beta) of 0.97, which attests to possible diversification benefits within a given portfolio. JPMorgan Fundamental returns are very sensitive to returns on the market. As the market goes up or down, JPMorgan Fundamental is expected to follow.
Auto-correlation | -0.76 |
Almost perfect reverse predictability
JPMorgan Fundamental Data has almost perfect reverse predictability. Overlapping area represents the amount of predictability between JPMorgan Fundamental time series from 17th of December 2024 to 31st of January 2025 and 31st of January 2025 to 17th of March 2025. 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 Fundamental Data price movement. The serial correlation of -0.76 indicates that around 76.0% of current JPMorgan Fundamental price fluctuation can be explain by its past prices.
| Correlation Coefficient | -0.76 | |
| Spearman Rank Test | -0.57 | |
| Residual Average | 0.0 | |
| Price Variance | 6.5 |
JPMorgan Fundamental Data lagged returns against current returns
Autocorrelation, which is JPMorgan Fundamental 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 Fundamental's etf expected returns. We can calculate the autocorrelation of JPMorgan Fundamental returns to help us make a trade decision. For example, suppose you find that JPMorgan Fundamental 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 Fundamental 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 Fundamental etf is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if JPMorgan Fundamental etf is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in JPMorgan Fundamental etf over time.
Current vs Lagged Prices |
| Timeline |
JPMorgan Fundamental Lagged Returns
When evaluating JPMorgan Fundamental's market value, investors can use the concept of autocorrelation to see how much of an impact past prices of JPMorgan Fundamental etf have on its future price. JPMorgan Fundamental 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 Fundamental autocorrelation shows the relationship between JPMorgan Fundamental etf current value and its past values and can show if there is a momentum factor associated with investing in JPMorgan Fundamental Data.
Regressed Prices |
| Timeline |
Thematic Opportunities
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Check out JPMorgan Fundamental Correlation, JPMorgan Fundamental Volatility and JPMorgan Fundamental Alpha and Beta module to complement your research on JPMorgan Fundamental. You can also try the Stock Screener module to find equities using a custom stock filter or screen asymmetry in trading patterns, price, volume, or investment outlook..
JPMorgan Fundamental 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.