Jpmorgan Climate Change Etf Market Value
| TEMP Etf | USD 46.33 0.21 0.45% |
| Symbol | JPMorgan |
The market value of JPMorgan Climate Change 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 Climate's value that differs from its market value or its book value, called intrinsic value, which is JPMorgan Climate'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 Climate's market value can be influenced by many factors that don't directly affect JPMorgan Climate'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 Climate's value and its price as these two are different measures arrived at by different means. Investors typically determine if JPMorgan Climate is a good investment by looking at such factors as earnings, sales, fundamental and technical indicators, competition as well as analyst projections. However, JPMorgan Climate'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 Climate '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 Climate'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 Climate.
| 06/17/2024 |
| 12/14/2024 |
If you would invest 0.00 in JPMorgan Climate on June 17, 2024 and sell it all today you would earn a total of 0.00 from holding JPMorgan Climate Change or generate 0.0% return on investment in JPMorgan Climate over 180 days. JPMorgan Climate is related to or competes with ProShares Big, Direxion Auspice, Eastern, and American Century. The adviser identifies companies that, in the advisers opinion, are developing solutions to address climate change and a... More
JPMorgan Climate 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 Climate'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 Climate Change upside and downside potential and time the market with a certain degree of confidence.
| Information Ratio | (0.14) | |||
| Maximum Drawdown | 4.38 | |||
| Value At Risk | (1.45) | |||
| Potential Upside | 1.35 |
JPMorgan Climate Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for JPMorgan Climate's investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as JPMorgan Climate's standard deviation. In reality, there are many statistical measures that can use JPMorgan Climate historical prices to predict the future JPMorgan Climate's volatility.| Risk Adjusted Performance | (0.01) | |||
| Jensen Alpha | (0.07) | |||
| Total Risk Alpha | (0.13) | |||
| Treynor Ratio | (0.05) |
JPMorgan Climate Change Backtested Returns
JPMorgan Climate Change holds Efficiency (Sharpe) Ratio of -0.0454, which attests that the entity had a -0.0454% return per unit of volatility over the last 3 months. JPMorgan Climate Change exposes twenty-three different technical indicators, which can help you to evaluate volatility embedded in its price movement. Please check out JPMorgan Climate's market risk adjusted performance of (0.04), and Risk Adjusted Performance of (0.01) to validate the risk estimate we provide. The etf retains a Market Volatility (i.e., Beta) of 0.48, which attests to possible diversification benefits within a given portfolio. As returns on the market increase, JPMorgan Climate's returns are expected to increase less than the market. However, during the bear market, the loss of holding JPMorgan Climate is expected to be smaller as well.
Auto-correlation | -0.36 |
Poor reverse predictability
JPMorgan Climate Change has poor reverse predictability. Overlapping area represents the amount of predictability between JPMorgan Climate time series from 17th of June 2024 to 15th of September 2024 and 15th of September 2024 to 14th of December 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 Climate Change price movement. The serial correlation of -0.36 indicates that just about 36.0% of current JPMorgan Climate price fluctuation can be explain by its past prices.
| Correlation Coefficient | -0.36 | |
| Spearman Rank Test | -0.31 | |
| Residual Average | 0.0 | |
| Price Variance | 0.99 |
JPMorgan Climate Change lagged returns against current returns
Autocorrelation, which is JPMorgan Climate 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 Climate's etf expected returns. We can calculate the autocorrelation of JPMorgan Climate returns to help us make a trade decision. For example, suppose you find that JPMorgan Climate 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 Climate 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 Climate etf is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if JPMorgan Climate etf is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in JPMorgan Climate etf over time.
Current vs Lagged Prices |
| Timeline |
JPMorgan Climate Lagged Returns
When evaluating JPMorgan Climate's market value, investors can use the concept of autocorrelation to see how much of an impact past prices of JPMorgan Climate etf have on its future price. JPMorgan Climate 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 Climate autocorrelation shows the relationship between JPMorgan Climate etf current value and its past values and can show if there is a momentum factor associated with investing in JPMorgan Climate Change.
Regressed Prices |
| Timeline |
Pair Trading with JPMorgan Climate
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 Climate 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 Climate will appreciate offsetting losses from the drop in the long position's value.Moving together with JPMorgan Etf
Moving against JPMorgan Etf
| 0.74 | RSPY | Tuttle Capital Management | PairCorr |
| 0.73 | MEME | Roundhill Investments | PairCorr |
| 0.71 | DSJA | DSJA | PairCorr |
| 0.68 | T | ATT Inc Fiscal Year End 22nd of January 2025 | PairCorr |
| 0.64 | PZD | Invesco | PairCorr |
The ability to find closely correlated positions to JPMorgan Climate 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 Climate 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 Climate - 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 Climate Change to buy it.
The correlation of JPMorgan Climate 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 Climate moves, either up or down, the other security will move in the same direction. Alternatively, perfect negative correlation means that if JPMorgan Climate Change 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 Climate 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 Climate Correlation, JPMorgan Climate Volatility and JPMorgan Climate Alpha and Beta module to complement your research on JPMorgan Climate. You can also try the Equity Analysis module to research over 250,000 global equities including funds, stocks and ETFs to find investment opportunities.
JPMorgan Climate 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.