Fidelity Dividend Etf Market Value
| FDRR Etf | USD 53.55 0.10 0.19% |
| Symbol | Fidelity |
The market value of Fidelity Dividend ETF is measured differently than its book value, which is the value of Fidelity that is recorded on the company's balance sheet. Investors also form their own opinion of Fidelity Dividend's value that differs from its market value or its book value, called intrinsic value, which is Fidelity Dividend'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 Fidelity Dividend's market value can be influenced by many factors that don't directly affect Fidelity Dividend'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 Fidelity Dividend's value and its price as these two are different measures arrived at by different means. Investors typically determine if Fidelity Dividend is a good investment by looking at such factors as earnings, sales, fundamental and technical indicators, competition as well as analyst projections. However, Fidelity Dividend'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.
Fidelity Dividend '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 Fidelity Dividend'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 Fidelity Dividend.
| 10/28/2024 |
| 11/27/2024 |
If you would invest 0.00 in Fidelity Dividend on October 28, 2024 and sell it all today you would earn a total of 0.00 from holding Fidelity Dividend ETF or generate 0.0% return on investment in Fidelity Dividend over 30 days. Fidelity Dividend is related to or competes with BlackRock ETF, Rbb Fund, Virtus ETF, and Amplify CWP. The fund normally invests at least 80 percent of assets in securities included in the underlying index and in depository... More
Fidelity Dividend 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 Fidelity Dividend'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 Fidelity Dividend ETF upside and downside potential and time the market with a certain degree of confidence.
| Downside Deviation | 0.6694 | |||
| Information Ratio | (0.07) | |||
| Maximum Drawdown | 3.14 | |||
| Value At Risk | (1.07) | |||
| Potential Upside | 1.03 |
Fidelity Dividend Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for Fidelity Dividend's investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as Fidelity Dividend's standard deviation. In reality, there are many statistical measures that can use Fidelity Dividend historical prices to predict the future Fidelity Dividend's volatility.| Risk Adjusted Performance | 0.0935 | |||
| Jensen Alpha | (0.01) | |||
| Total Risk Alpha | (0.03) | |||
| Sortino Ratio | (0.07) | |||
| Treynor Ratio | 0.1013 |
Fidelity Dividend ETF Backtested Returns
Currently, Fidelity Dividend ETF is very steady. Fidelity Dividend ETF secures Sharpe Ratio (or Efficiency) of 0.15, which denotes the etf had a 0.15% return per unit of risk over the last 3 months. We have found twenty-eight technical indicators for Fidelity Dividend ETF, which you can use to evaluate the volatility of the entity. Please confirm Fidelity Dividend's Mean Deviation of 0.4841, downside deviation of 0.6694, and Coefficient Of Variation of 806.12 to check if the risk estimate we provide is consistent with the expected return of 0.0995%. The etf shows a Beta (market volatility) of 0.73, which means possible diversification benefits within a given portfolio. As returns on the market increase, Fidelity Dividend's returns are expected to increase less than the market. However, during the bear market, the loss of holding Fidelity Dividend is expected to be smaller as well.
Auto-correlation | 0.95 |
Excellent predictability
Fidelity Dividend ETF has excellent predictability. Overlapping area represents the amount of predictability between Fidelity Dividend 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 Fidelity Dividend ETF price movement. The serial correlation of 0.95 indicates that approximately 95.0% of current Fidelity Dividend price fluctuation can be explain by its past prices.
| Correlation Coefficient | 0.95 | |
| Spearman Rank Test | 0.95 | |
| Residual Average | 0.0 | |
| Price Variance | 0.16 |
Fidelity Dividend ETF lagged returns against current returns
Autocorrelation, which is Fidelity Dividend 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 Fidelity Dividend's etf expected returns. We can calculate the autocorrelation of Fidelity Dividend returns to help us make a trade decision. For example, suppose you find that Fidelity Dividend 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 |
Fidelity Dividend 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 Fidelity Dividend etf is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if Fidelity Dividend etf is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in Fidelity Dividend etf over time.
Current vs Lagged Prices |
| Timeline |
Fidelity Dividend Lagged Returns
When evaluating Fidelity Dividend's market value, investors can use the concept of autocorrelation to see how much of an impact past prices of Fidelity Dividend etf have on its future price. Fidelity Dividend 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, Fidelity Dividend autocorrelation shows the relationship between Fidelity Dividend etf current value and its past values and can show if there is a momentum factor associated with investing in Fidelity Dividend ETF.
Regressed Prices |
| Timeline |
Pair Trading with Fidelity Dividend
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 Fidelity Dividend 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 Fidelity Dividend will appreciate offsetting losses from the drop in the long position's value.Moving together with Fidelity Etf
| 0.95 | VTV | Vanguard Value Index | PairCorr |
| 0.97 | VYM | Vanguard High Dividend | PairCorr |
| 0.95 | IWD | iShares Russell 1000 Sell-off Trend | PairCorr |
| 0.96 | DGRO | iShares Core Dividend | PairCorr |
| 0.94 | IVE | iShares SP 500 | PairCorr |
Moving against Fidelity Etf
The ability to find closely correlated positions to Fidelity Dividend could be a great tool in your tax-loss harvesting strategies, allowing investors a quick way to find a similar-enough asset to replace Fidelity Dividend 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 Fidelity Dividend - 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 Fidelity Dividend ETF to buy it.
The correlation of Fidelity Dividend 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 Fidelity Dividend moves, either up or down, the other security will move in the same direction. Alternatively, perfect negative correlation means that if Fidelity Dividend ETF 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 Fidelity Dividend 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 Fidelity Dividend Correlation, Fidelity Dividend Volatility and Fidelity Dividend Alpha and Beta module to complement your research on Fidelity Dividend. You can also try the Fundamentals Comparison module to compare fundamentals across multiple equities to find investing opportunities.
Fidelity Dividend 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.