Acm Dynamic Opportunity Fund Market Value
ADOAX Fund | USD 19.53 0.01 0.05% |
Symbol | Acm |
Acm Dynamic '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 Acm Dynamic'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 Acm Dynamic.
04/08/2022 |
| 03/28/2024 |
If you would invest 0.00 in Acm Dynamic on April 8, 2022 and sell it all today you would earn a total of 0.00 from holding Acm Dynamic Opportunity or generate 0.0% return on investment in Acm Dynamic over 720 days. Acm Dynamic is related to or competes with Acm Dynamic, Acm Tactical, Acm Tactical, Morningstar Unconstrained, Brookfield Real, and New World. Under normal market conditions, the fund seeks to achieve its investment objective by investing in domestic and foreign ... More
Acm Dynamic 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 Acm Dynamic'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 Acm Dynamic Opportunity upside and downside potential and time the market with a certain degree of confidence.
Downside Deviation | 0.6707 | |||
Information Ratio | 0.052 | |||
Maximum Drawdown | 2.83 | |||
Value At Risk | (0.92) | |||
Potential Upside | 1.24 |
Acm Dynamic Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for Acm Dynamic's investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as Acm Dynamic's standard deviation. In reality, there are many statistical measures that can use Acm Dynamic historical prices to predict the future Acm Dynamic's volatility.Risk Adjusted Performance | 0.1436 | |||
Jensen Alpha | 0.0562 | |||
Total Risk Alpha | 0.0111 | |||
Sortino Ratio | 0.0511 | |||
Treynor Ratio | 0.1924 |
Sophisticated investors, who have witnessed many market ups and downs, anticipate that the market will even out over time. This tendency of Acm Dynamic'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.
Acm Dynamic Opportunity Backtested Returns
We consider Acm Dynamic very steady. Acm Dynamic Opportunity secures Sharpe Ratio (or Efficiency) of 0.27, which signifies that the fund had a 0.27% return per unit of risk over the last 3 months. We have found twenty-eight technical indicators for Acm Dynamic Opportunity, which you can use to evaluate the volatility of the entity. Please confirm Acm Dynamic's Downside Deviation of 0.6707, risk adjusted performance of 0.1436, and Mean Deviation of 0.5082 to double-check if the risk estimate we provide is consistent with the expected return of 0.18%. The fund shows a Beta (market volatility) of 0.82, which signifies possible diversification benefits within a given portfolio. As returns on the market increase, Acm Dynamic's returns are expected to increase less than the market. However, during the bear market, the loss of holding Acm Dynamic is expected to be smaller as well.
Auto-correlation | -0.79 |
Almost perfect reverse predictability
Acm Dynamic Opportunity has almost perfect reverse predictability. Overlapping area represents the amount of predictability between Acm Dynamic time series from 8th of April 2022 to 3rd of April 2023 and 3rd of April 2023 to 28th of March 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 Acm Dynamic Opportunity price movement. The serial correlation of -0.79 indicates that around 79.0% of current Acm Dynamic price fluctuation can be explain by its past prices.
Correlation Coefficient | -0.79 | |
Spearman Rank Test | -0.73 | |
Residual Average | 0.0 | |
Price Variance | 0.95 |
Acm Dynamic Opportunity lagged returns against current returns
Autocorrelation, which is Acm Dynamic 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 Acm Dynamic's mutual fund expected returns. We can calculate the autocorrelation of Acm Dynamic returns to help us make a trade decision. For example, suppose you find that Acm Dynamic 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 |
Acm Dynamic 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 Acm Dynamic mutual fund is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if Acm Dynamic mutual fund is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in Acm Dynamic mutual fund over time.
Current vs Lagged Prices |
Timeline |
Acm Dynamic Lagged Returns
When evaluating Acm Dynamic's market value, investors can use the concept of autocorrelation to see how much of an impact past prices of Acm Dynamic mutual fund have on its future price. Acm Dynamic 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, Acm Dynamic autocorrelation shows the relationship between Acm Dynamic mutual fund current value and its past values and can show if there is a momentum factor associated with investing in Acm Dynamic Opportunity.
Regressed Prices |
Timeline |
Pair Trading with Acm Dynamic
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 Acm Dynamic 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 Acm Dynamic will appreciate offsetting losses from the drop in the long position's value.Moving together with Acm Mutual Fund
1.0 | ADOIX | Acm Dynamic Opportunity | PairCorr |
0.89 | TINAX | Acm Tactical Me | PairCorr |
0.9 | TINIX | Acm Tactical Me | PairCorr |
0.81 | NLSCX | Neuberger Berman Long | PairCorr |
The ability to find closely correlated positions to Acm Dynamic could be a great tool in your tax-loss harvesting strategies, allowing investors a quick way to find a similar-enough asset to replace Acm Dynamic 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 Acm Dynamic - 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 Acm Dynamic Opportunity to buy it.
The correlation of Acm Dynamic 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 Acm Dynamic moves, either up or down, the other security will move in the same direction. Alternatively, perfect negative correlation means that if Acm Dynamic Opportunity 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 Acm Dynamic 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 Acm Dynamic Correlation, Acm Dynamic Volatility and Acm Dynamic Alpha and Beta module to complement your research on Acm Dynamic. Note that the Acm Dynamic Opportunity information on this page should be used as a complementary analysis to other Acm Dynamic'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 Portfolio Dashboard module to portfolio dashboard that provides centralized access to all your investments.
Complementary Tools for Acm Mutual Fund analysis
When running Acm Dynamic's price analysis, check to measure Acm Dynamic's market volatility, profitability, liquidity, solvency, efficiency, growth potential, financial leverage, and other vital indicators. We have many different tools that can be utilized to determine how healthy Acm Dynamic is operating at the current time. Most of Acm Dynamic's value examination focuses on studying past and present price action to predict the probability of Acm Dynamic's future price movements. You can analyze the entity against its peers and the financial market as a whole to determine factors that move Acm Dynamic's price. Additionally, you may evaluate how the addition of Acm Dynamic to your portfolios can decrease your overall portfolio volatility.
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Acm Dynamic 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.