Power Momentum Mutual Fund Forecast - 4 Period Moving Average

MOJOX Fund  USD 14.66  0.04  0.27%   
The 4 Period Moving Average forecasted value of Power Momentum Index on the next trading day is expected to be 14.78 with a mean absolute deviation of 0.16 and the sum of the absolute errors of 9.09. Power Mutual Fund Forecast is based on your current time horizon.
  
A four-period moving average forecast model for Power Momentum Index is based on an artificially constructed daily price series in which the value for a given day is replaced by the mean of that value and the values for four preceding and succeeding time periods. This model is best suited to forecast equities with high volatility.

Power Momentum 4 Period Moving Average Price Forecast For the 22nd of December

Given 90 days horizon, the 4 Period Moving Average forecasted value of Power Momentum Index on the next trading day is expected to be 14.78 with a mean absolute deviation of 0.16, mean absolute percentage error of 0.05, and the sum of the absolute errors of 9.09.
Please note that although there have been many attempts to predict Power 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 Power Momentum's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).

Power Momentum Mutual Fund Forecast Pattern

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Power Momentum Forecasted Value

In the context of forecasting Power Momentum'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. Power Momentum's downside and upside margins for the forecasting period are 13.85 and 15.72, respectively. We have considered Power Momentum'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.
Market Value
14.66
14.78
Expected Value
15.72
Upside

Model Predictive Factors

The below table displays some essential indicators generated by the model showing the 4 Period Moving Average forecasting method's relative quality and the estimations of the prediction error of Power Momentum mutual fund data series using in forecasting. Note that when a statistical model is used to represent Power Momentum 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.
AICAkaike Information Criteria107.743
BiasArithmetic mean of the errors -0.0145
MADMean absolute deviation0.1595
MAPEMean absolute percentage error0.0107
SAESum of the absolute errors9.09
The four period moving average method has an advantage over other forecasting models in that it does smooth out peaks and troughs in a set of daily price observations of Power Momentum. However, it also has several disadvantages. In particular this model does not produce an actual prediction equation for Power Momentum Index and therefore, it cannot be a useful forecasting tool for medium or long range price predictions

Predictive Modules for Power Momentum

There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Power Momentum Index. 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.
Hype
Prediction
LowEstimatedHigh
13.7214.6615.60
Details
Intrinsic
Valuation
LowRealHigh
13.7814.7215.66
Details
Bollinger
Band Projection (param)
LowMiddleHigh
14.7115.2115.72
Details

Other Forecasting Options for Power Momentum

For every potential investor in Power, whether a beginner or expert, Power Momentum's price movement is the inherent factor that sparks whether it is viable to invest in it or hold it better. Power Mutual Fund price charts are filled with many 'noises.' These noises can hugely alter the decision one can make regarding investing in Power. Basic forecasting techniques help filter out the noise by identifying Power Momentum's price trends.

Power Momentum 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 Power Momentum mutual fund to make a market-neutral strategy. Peer analysis of Power Momentum could also be used in its relative valuation, which is a method of valuing Power Momentum by comparing valuation metrics with similar companies.
 Risk & Return  Correlation

Power Momentum Index 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 Power Momentum'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 Power Momentum's current price.

Power Momentum Market Strength Events

Market strength indicators help investors to evaluate how Power Momentum 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 Power Momentum shares will generate the highest return on investment. By undertsting and applying Power Momentum mutual fund market strength indicators, traders can identify Power Momentum Index entry and exit signals to maximize returns.

Power Momentum Risk Indicators

The analysis of Power Momentum'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 Power Momentum's investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting power 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.
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.

Also Currently Popular

Analyzing currently trending equities could be an opportunity to develop a better portfolio based on different market momentums that they can trigger. Utilizing the top trending stocks is also useful when creating a market-neutral strategy or pair trading technique involving a short or a long position in a currently trending equity.

Other Information on Investing in Power Mutual Fund

Power Momentum financial ratios help investors to determine whether Power Mutual Fund is cheap or expensive when compared to a particular measure, such as profits or enterprise value. In other words, they help investors to determine the cost of investment in Power with respect to the benefits of owning Power Momentum security.
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