Evaluator Moderate Rms Fund Market Value
| EVMLX Fund | USD 10.11 0.04 0.39% |
| Symbol | Evaluator |
Evaluator Moderate '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 Evaluator Moderate'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 Evaluator Moderate.
| 03/18/2024 |
| 04/17/2024 |
If you would invest 0.00 in Evaluator Moderate on March 18, 2024 and sell it all today you would earn a total of 0.00 from holding Evaluator Moderate Rms or generate 0.0% return on investment in Evaluator Moderate over 30 days. Evaluator Moderate is related to or competes with Evaluator Aggressive, Evaluator Aggressive, Evaluator Conservative, Evaluator Growth, Evaluator Growth, and Evaluator Very. The fund seeks to achieve its objective by investing in the securities of other unaffiliated investment companies, inclu... More
Evaluator Moderate 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 Evaluator Moderate'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 Evaluator Moderate Rms upside and downside potential and time the market with a certain degree of confidence.
| Downside Deviation | 0.6035 | |||
| Information Ratio | (0.05) | |||
| Maximum Drawdown | 2.45 | |||
| Value At Risk | (0.70) | |||
| Potential Upside | 0.7042 |
Evaluator Moderate Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for Evaluator Moderate's investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as Evaluator Moderate's standard deviation. In reality, there are many statistical measures that can use Evaluator Moderate historical prices to predict the future Evaluator Moderate's volatility.| Risk Adjusted Performance | 0.0421 | |||
| Jensen Alpha | (0.01) | |||
| Total Risk Alpha | (0.01) | |||
| Sortino Ratio | (0.04) | |||
| Treynor Ratio | 0.0381 |
Sophisticated investors, who have witnessed many market ups and downs, anticipate that the market will even out over time. This tendency of Evaluator Moderate'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.
Evaluator Moderate Rms Backtested Returns
We consider Evaluator Moderate very steady. Evaluator Moderate Rms secures Sharpe Ratio (or Efficiency) of 0.0923, which denotes the fund had a 0.0923% return per unit of standard deviation over the last 3 months. We have found twenty-eight technical indicators for Evaluator Moderate Rms, which you can use to evaluate the volatility of the entity. Please confirm Evaluator Moderate's Downside Deviation of 0.6035, semi deviation of 0.4474, and Mean Deviation of 0.3576 to check if the risk estimate we provide is consistent with the expected return of 0.0441%. The fund shows a Beta (market volatility) of 0.64, which means possible diversification benefits within a given portfolio. As returns on the market increase, Evaluator Moderate's returns are expected to increase less than the market. However, during the bear market, the loss of holding Evaluator Moderate is expected to be smaller as well.
Auto-correlation | -0.24 |
Weak reverse predictability
Evaluator Moderate Rms has weak reverse predictability. Overlapping area represents the amount of predictability between Evaluator Moderate time series from 18th of March 2024 to 2nd of April 2024 and 2nd of April 2024 to 17th 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 Evaluator Moderate Rms price movement. The serial correlation of -0.24 indicates that over 24.0% of current Evaluator Moderate price fluctuation can be explain by its past prices.
| Correlation Coefficient | -0.24 | |
| Spearman Rank Test | -0.59 | |
| Residual Average | 0.0 | |
| Price Variance | 0.01 |
Evaluator Moderate Rms lagged returns against current returns
Autocorrelation, which is Evaluator Moderate 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 Evaluator Moderate's mutual fund expected returns. We can calculate the autocorrelation of Evaluator Moderate returns to help us make a trade decision. For example, suppose you find that Evaluator Moderate 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 |
Evaluator Moderate 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 Evaluator Moderate mutual fund is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if Evaluator Moderate mutual fund is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in Evaluator Moderate mutual fund over time.
Current vs Lagged Prices |
| Timeline |
Evaluator Moderate Lagged Returns
When evaluating Evaluator Moderate's market value, investors can use the concept of autocorrelation to see how much of an impact past prices of Evaluator Moderate mutual fund have on its future price. Evaluator Moderate 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, Evaluator Moderate autocorrelation shows the relationship between Evaluator Moderate mutual fund current value and its past values and can show if there is a momentum factor associated with investing in Evaluator Moderate Rms.
Regressed Prices |
| Timeline |
Some investors attempt to determine whether the market's mood is bullish or bearish by monitoring changes in market sentiment. Unlike more traditional methods such as technical analysis, investor sentiment usually refers to the aggregate attitude towards Evaluator Moderate in the overall investment community. So, suppose investors can accurately measure the market's sentiment. In that case, they can use it for their benefit. For example, some tools to gauge market sentiment could be utilized using contrarian indexes, Evaluator Moderate's short interest history, or implied volatility extrapolated from Evaluator Moderate options trading.
Pair Trading with Evaluator Moderate
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 Evaluator Moderate 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 Evaluator Moderate will appreciate offsetting losses from the drop in the long position's value.Moving together with Evaluator Mutual Fund
| 1.0 | EVAGX | Evaluator Aggressive Rms | PairCorr |
| 0.99 | EVFTX | Evaluator Tactically | PairCorr |
| 1.0 | EVFMX | Evaluator Moderate Rms | PairCorr |
| 1.0 | EVFGX | Evaluator Aggressive Rms | PairCorr |
| 0.98 | EVFCX | Evaluator Conservative | PairCorr |
The ability to find closely correlated positions to Evaluator Moderate could be a great tool in your tax-loss harvesting strategies, allowing investors a quick way to find a similar-enough asset to replace Evaluator Moderate 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 Evaluator Moderate - 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 Evaluator Moderate Rms to buy it.
The correlation of Evaluator Moderate 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 Evaluator Moderate moves, either up or down, the other security will move in the same direction. Alternatively, perfect negative correlation means that if Evaluator Moderate Rms 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 Evaluator Moderate 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 Evaluator Moderate Correlation, Evaluator Moderate Volatility and Evaluator Moderate Alpha and Beta module to complement your research on Evaluator Moderate. You can also try the Fundamentals Comparison module to compare fundamentals across multiple equities to find investing opportunities.
Evaluator Moderate 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.