Fidelity High Dividend Etf Market Value
| FDVV Etf | USD 52.36 0.01 0.02% |
| Symbol | Fidelity |
The market value of Fidelity High Dividend 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 High's value that differs from its market value or its book value, called intrinsic value, which is Fidelity High'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 High's market value can be influenced by many factors that don't directly affect Fidelity High'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 High's value and its price as these two are different measures arrived at by different means. Investors typically determine if Fidelity High is a good investment by looking at such factors as earnings, sales, fundamental and technical indicators, competition as well as analyst projections. However, Fidelity High'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 High '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 High'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 High.
| 10/27/2024 |
| 11/26/2024 |
If you would invest 0.00 in Fidelity High on October 27, 2024 and sell it all today you would earn a total of 0.00 from holding Fidelity High Dividend or generate 0.0% return on investment in Fidelity High over 30 days. Fidelity High is related to or competes with Franklin Templeton, Altrius Global, Invesco Exchange, Franklin International, Madison ETFs, Amplify CWP, and Advisors Inner. The fund normally invests at least 80 percent of assets in securities included in the underlying index and in depository... More
Fidelity High 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 High'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 High Dividend upside and downside potential and time the market with a certain degree of confidence.
| Downside Deviation | 0.5627 | |||
| Information Ratio | (0.08) | |||
| Maximum Drawdown | 2.4 | |||
| Value At Risk | (0.64) | |||
| Potential Upside | 1.13 |
Fidelity High Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for Fidelity High's investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as Fidelity High's standard deviation. In reality, there are many statistical measures that can use Fidelity High historical prices to predict the future Fidelity High's volatility.| Risk Adjusted Performance | 0.109 | |||
| Jensen Alpha | 0.0029 | |||
| Total Risk Alpha | (0.01) | |||
| Sortino Ratio | (0.08) | |||
| Treynor Ratio | 0.1234 |
Sophisticated investors, who have witnessed many market ups and downs, anticipate that the market will even out over time. This tendency of Fidelity High'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.
Fidelity High Dividend Backtested Returns
At this stage we consider Fidelity Etf to be very steady. Fidelity High Dividend secures Sharpe Ratio (or Efficiency) of 0.16, which denotes the etf had a 0.16% return per unit of risk over the last 3 months. We have found twenty-nine technical indicators for Fidelity High Dividend, which you can use to evaluate the volatility of the entity. Please confirm Fidelity High's Downside Deviation of 0.5627, coefficient of variation of 680.11, and Mean Deviation of 0.4413 to check if the risk estimate we provide is consistent with the expected return of 0.0932%. The etf shows a Beta (market volatility) of 0.6, which means possible diversification benefits within a given portfolio. As returns on the market increase, Fidelity High's returns are expected to increase less than the market. However, during the bear market, the loss of holding Fidelity High is expected to be smaller as well.
Auto-correlation | 0.89 |
Very good predictability
Fidelity High Dividend has very good predictability. Overlapping area represents the amount of predictability between Fidelity High time series from 27th of October 2024 to 11th of November 2024 and 11th of November 2024 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 Fidelity High Dividend price movement. The serial correlation of 0.89 indicates that approximately 89.0% of current Fidelity High price fluctuation can be explain by its past prices.
| Correlation Coefficient | 0.89 | |
| Spearman Rank Test | 0.45 | |
| Residual Average | 0.0 | |
| Price Variance | 0.09 |
Fidelity High Dividend lagged returns against current returns
Autocorrelation, which is Fidelity High 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 High's etf expected returns. We can calculate the autocorrelation of Fidelity High returns to help us make a trade decision. For example, suppose you find that Fidelity High 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 High 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 High etf is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if Fidelity High etf is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in Fidelity High etf over time.
Current vs Lagged Prices |
| Timeline |
Fidelity High Lagged Returns
When evaluating Fidelity High's market value, investors can use the concept of autocorrelation to see how much of an impact past prices of Fidelity High etf have on its future price. Fidelity High 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 High autocorrelation shows the relationship between Fidelity High etf current value and its past values and can show if there is a momentum factor associated with investing in Fidelity High Dividend.
Regressed Prices |
| Timeline |
Thematic Opportunities
Explore Investment Opportunities
Check out Fidelity High Correlation, Fidelity High Volatility and Fidelity High Alpha and Beta module to complement your research on Fidelity High. You can also try the Options Analysis module to analyze and evaluate options and option chains as a potential hedge for your portfolios.
Fidelity High 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.