Parametric Dividend Income Fund Market Value
| EAPDX Fund | USD 16.23 0.04 0.25% |
| Symbol | Parametric |
Parametric 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 Parametric Dividend's mutual fund 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 Parametric Dividend.
| 03/20/2024 |
| 04/19/2024 |
If you would invest 0.00 in Parametric Dividend on March 20, 2024 and sell it all today you would earn a total of 0.00 from holding Parametric Dividend Income or generate 0.0% return on investment in Parametric Dividend over 30 days. Parametric Dividend is related to or competes with Parametric Modity, Parametric International, Huber Capital, Oberweis Small, and Dreyfus Strategic. The fund invests at least 80 percent of its net assets in equity securities, which primarily include common stocks of U.... More
Parametric 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 Parametric Dividend's mutual fund 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 Parametric Dividend Income upside and downside potential and time the market with a certain degree of confidence.
| Downside Deviation | 0.896 | |||
| Information Ratio | (0.05) | |||
| Maximum Drawdown | 3.79 | |||
| Value At Risk | (1.21) | |||
| Potential Upside | 1.01 |
Parametric Dividend Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for Parametric Dividend's investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as Parametric Dividend's standard deviation. In reality, there are many statistical measures that can use Parametric Dividend historical prices to predict the future Parametric Dividend's volatility.| Risk Adjusted Performance | 0.029 | |||
| Jensen Alpha | (0.03) | |||
| Total Risk Alpha | (0.05) | |||
| Sortino Ratio | (0.04) | |||
| Treynor Ratio | 0.0224 |
Sophisticated investors, who have witnessed many market ups and downs, anticipate that the market will even out over time. This tendency of Parametric Dividend'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.
Parametric Dividend Backtested Returns
We consider Parametric Dividend very steady. Parametric Dividend maintains Sharpe Ratio (i.e., Efficiency) of 0.0353, which implies the entity had a 0.0353% return per unit of risk over the last 3 months. We have found twenty-seven technical indicators for Parametric Dividend, which you can use to evaluate the volatility of the fund. Please check Parametric Dividend's Semi Deviation of 0.7916, coefficient of variation of 2226.51, and Risk Adjusted Performance of 0.029 to confirm if the risk estimate we provide is consistent with the expected return of 0.0252%. The fund holds a Beta of 0.97, which implies possible diversification benefits within a given portfolio. Parametric Dividend returns are very sensitive to returns on the market. As the market goes up or down, Parametric Dividend is expected to follow.
Auto-correlation | -0.58 |
Good reverse predictability
Parametric Dividend Income has good reverse predictability. Overlapping area represents the amount of predictability between Parametric Dividend time series from 20th of March 2024 to 4th of April 2024 and 4th of April 2024 to 19th of April 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 Parametric Dividend price movement. The serial correlation of -0.58 indicates that roughly 58.0% of current Parametric Dividend price fluctuation can be explain by its past prices.
| Correlation Coefficient | -0.58 | |
| Spearman Rank Test | -0.5 | |
| Residual Average | 0.0 | |
| Price Variance | 0.07 |
Parametric Dividend lagged returns against current returns
Autocorrelation, which is Parametric Dividend mutual fund'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 Parametric Dividend's mutual fund expected returns. We can calculate the autocorrelation of Parametric Dividend returns to help us make a trade decision. For example, suppose you find that Parametric Dividend has exhibited high autocorrelation historically, and you observe that the mutual fund 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 |
Parametric 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 Parametric Dividend mutual fund is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if Parametric Dividend mutual fund is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in Parametric Dividend mutual fund over time.
Current vs Lagged Prices |
| Timeline |
Parametric Dividend Lagged Returns
When evaluating Parametric Dividend's market value, investors can use the concept of autocorrelation to see how much of an impact past prices of Parametric Dividend mutual fund have on its future price. Parametric 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, Parametric Dividend autocorrelation shows the relationship between Parametric Dividend mutual fund current value and its past values and can show if there is a momentum factor associated with investing in Parametric Dividend Income.
Regressed Prices |
| Timeline |
Pair Trading with Parametric 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 Parametric 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 Parametric Dividend will appreciate offsetting losses from the drop in the long position's value.Moving together with Parametric Mutual Fund
| 0.74 | EMAIX | Eaton Vance Msschsts | PairCorr |
The ability to find closely correlated positions to Parametric 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 Parametric 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 Parametric 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 Parametric Dividend Income to buy it.
The correlation of Parametric 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 Parametric Dividend moves, either up or down, the other security will move in the same direction. Alternatively, perfect negative correlation means that if Parametric Dividend 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 Parametric 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 Parametric Dividend Correlation, Parametric Dividend Volatility and Parametric Dividend Alpha and Beta module to complement your research on Parametric Dividend. Note that the Parametric Dividend information on this page should be used as a complementary analysis to other Parametric Dividend's statistical models used to find the right mix of equity instruments to add to your existing portfolios or create a brand new portfolio. You can also try the Instant Ratings module to determine any equity ratings based on digital recommendations. Macroaxis instant equity ratings are based on combination of fundamental analysis and risk-adjusted market performance.
Parametric Dividend technical mutual fund 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, fund market cycles, or different charting patterns.