Acm Dynamic Mutual Fund Forecast - Polynomial Regression
| ADOAX Fund | USD 18.95 0.08 0.42% |
The Polynomial Regression forecasted value of Acm Dynamic Opportunity on the next trading day is expected to be 18.62 with a mean absolute deviation of 0.12 and the sum of the absolute errors of 7.30. Acm Mutual Fund Forecast is based on your current time horizon. Investors can use this forecasting interface to forecast Acm Dynamic stock prices and determine the direction of Acm Dynamic Opportunity's future trends based on various well-known forecasting models. We recommend always using this module together with an analysis of Acm Dynamic's historical fundamentals, such as revenue growth or operating cash flow patterns.
Check out Historical Fundamental Analysis of Acm Dynamic to cross-verify your projections. Acm |
Most investors in Acm Dynamic cannot accurately predict what will happen the next trading day because, historically, fund markets tend to be unpredictable and even illogical. Modeling turbulent structures requires applying different statistical methods, techniques, and algorithms to find hidden data structures or patterns within the Acm Dynamic's time series price data and predict how it will affect future prices. One of these methodologies is forecasting, which interprets Acm Dynamic's price structures and extracts relationships that further increase the generated results' accuracy.
Acm Dynamic polinomial regression implements a single variable polynomial regression model using the daily prices as the independent variable. The coefficients of the regression for Acm Dynamic Opportunity as well as the accuracy indicators are determined from the period prices. Acm Dynamic Polynomial Regression Price Forecast For the 26th of April
Given 90 days horizon, the Polynomial Regression forecasted value of Acm Dynamic Opportunity on the next trading day is expected to be 18.62 with a mean absolute deviation of 0.12, mean absolute percentage error of 0.02, and the sum of the absolute errors of 7.30.Please note that although there have been many attempts to predict Acm Mutual Fund prices using its time series forecasting, we generally do not recommend using it to place bets in the real market. The most commonly used models for forecasting predictions are the autoregressive models, which specify that Acm Dynamic's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).
Acm Dynamic Mutual Fund Forecast Pattern
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Acm Dynamic Forecasted Value
In the context of forecasting Acm Dynamic's Mutual Fund value on the next trading day, we examine the predictive performance of the model to find good statistically significant boundaries of downside and upside scenarios. Acm Dynamic's downside and upside margins for the forecasting period are 17.88 and 19.37, respectively. We have considered Acm Dynamic's daily market price to evaluate the above model's predictive performance. Remember, however, there is no scientific proof or empirical evidence that traditional linear or nonlinear forecasting models outperform artificial intelligence and frequency domain models to provide accurate forecasts consistently.
Model Predictive Factors
The below table displays some essential indicators generated by the model showing the Polynomial Regression forecasting method's relative quality and the estimations of the prediction error of Acm Dynamic mutual fund data series using in forecasting. Note that when a statistical model is used to represent Acm Dynamic mutual fund, the representation will rarely be exact; so some information will be lost using the model to explain the process. AIC estimates the relative amount of information lost by a given model: the less information a model loses, the higher its quality.| AIC | Akaike Information Criteria | 114.2682 |
| Bias | Arithmetic mean of the errors | None |
| MAD | Mean absolute deviation | 0.1197 |
| MAPE | Mean absolute percentage error | 0.0063 |
| SAE | Sum of the absolute errors | 7.3019 |
Predictive Modules for Acm Dynamic
There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Acm Dynamic Opportunity. Regardless of method or technology, however, to accurately forecast the mutual fund market is more a matter of luck rather than a particular technique. Nevertheless, trying to predict the mutual fund market accurately is still an essential part of the overall investment decision process. Using different forecasting techniques and comparing the results might improve your chances of accuracy even though unexpected events may often change the market sentiment and impact your forecasting results.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.
Other Forecasting Options for Acm Dynamic
For every potential investor in Acm, whether a beginner or expert, Acm Dynamic's price movement is the inherent factor that sparks whether it is viable to invest in it or hold it better. Acm Mutual Fund price charts are filled with many 'noises.' These noises can hugely alter the decision one can make regarding investing in Acm. Basic forecasting techniques help filter out the noise by identifying Acm Dynamic's price trends.Acm Dynamic Related Equities
One of the popular trading techniques among algorithmic traders is to use market-neutral strategies where every trade hedges away some risk. Because there are two separate transactions required, even if one position performs unexpectedly, the other equity can make up some of the losses. Below are some of the equities that can be combined with Acm Dynamic mutual fund to make a market-neutral strategy. Peer analysis of Acm Dynamic could also be used in its relative valuation, which is a method of valuing Acm Dynamic by comparing valuation metrics with similar companies.
| Risk & Return | Correlation |
Acm Dynamic Opportunity Technical and Predictive Analytics
The mutual fund market is financially volatile. Despite the volatility, there exist limitless possibilities of gaining profits and building passive income portfolios. With the complexity of Acm Dynamic's price movements, a comprehensive understanding of forecasting methods that an investor can rely on to make the right move is invaluable. These methods predict trends that assist an investor in predicting the movement of Acm Dynamic's current price.| Cycle Indicators | ||
| Math Operators | ||
| Math Transform | ||
| Momentum Indicators | ||
| Overlap Studies | ||
| Pattern Recognition | ||
| Price Transform | ||
| Statistic Functions | ||
| Volatility Indicators | ||
| Volume Indicators |
Acm Dynamic Market Strength Events
Market strength indicators help investors to evaluate how Acm Dynamic mutual fund reacts to ongoing and evolving market conditions. The investors can use it to make informed decisions about market timing, and determine when trading Acm Dynamic shares will generate the highest return on investment. By undertsting and applying Acm Dynamic mutual fund market strength indicators, traders can identify Acm Dynamic Opportunity entry and exit signals to maximize returns.
| Daily Balance Of Power | (9,223,372,036,855) | |||
| Rate Of Daily Change | 1.0 | |||
| Day Median Price | 18.95 | |||
| Day Typical Price | 18.95 | |||
| Price Action Indicator | (0.04) | |||
| Period Momentum Indicator | (0.08) |
Acm Dynamic Risk Indicators
The analysis of Acm Dynamic's basic risk indicators is one of the essential steps in accurately forecasting its future price. The process involves identifying the amount of risk involved in Acm Dynamic's investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting acm mutual fund prices, we also provide a set of basic risk indicators that can assist in the individual investment decision or help in hedging the risk of your existing portfolios.
| Mean Deviation | 0.5837 | |||
| Semi Deviation | 0.5998 | |||
| Standard Deviation | 0.7348 | |||
| Variance | 0.54 | |||
| Downside Variance | 0.5922 | |||
| Semi Variance | 0.3598 | |||
| Expected Short fall | (0.63) |
Please note, the risk measures we provide can be used independently or collectively to perform a risk assessment. When comparing two potential investments, we recommend comparing similar equities with homogenous growth potential and valuation from related markets to determine which investment holds the most risk.
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
| 0.76 | TINAX | Acm Tactical Me | PairCorr |
| 0.78 | TINIX | Acm Tactical Me | PairCorr |
Moving against Acm Mutual Fund
| 0.95 | UIPIX | Ultrashort Mid Cap | PairCorr |
| 0.79 | USPSX | Profunds Ultrashort | PairCorr |
| 0.78 | USPIX | Profunds Ultrashort | 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 Historical Fundamental Analysis of Acm Dynamic to cross-verify your projections. 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 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.