Guggenheim Diversified Mutual Fund Forecast - 20 Period Moving Average

GUDAX Fund  USD 25.43  0.00  0.00%   
The 20 Period Moving Average forecasted value of Guggenheim Diversified Income on the next trading day is expected to be 25.43 with a mean absolute deviation of 0 and the sum of the absolute errors of 0. Guggenheim Mutual Fund Forecast is based on your current time horizon.
  
A commonly used 20-period moving average forecast model for Guggenheim Diversified Income is based on a synthetically constructed Guggenheim Diversifieddaily price series in which the value for a trading day is replaced by the mean of that value and the values for 20 of preceding and succeeding time periods. This model is best suited for price series data that changes over time.

Guggenheim Diversified 20 Period Moving Average Price Forecast For the 27th of February

Given 90 days horizon, the 20 Period Moving Average forecasted value of Guggenheim Diversified Income on the next trading day is expected to be 25.43 with a mean absolute deviation of 0, mean absolute percentage error of 0, and the sum of the absolute errors of 0.
Please note that although there have been many attempts to predict Guggenheim 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 Guggenheim Diversified's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).

Guggenheim Diversified Mutual Fund Forecast Pattern

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Model Predictive Factors

The below table displays some essential indicators generated by the model showing the 20 Period Moving Average forecasting method's relative quality and the estimations of the prediction error of Guggenheim Diversified mutual fund data series using in forecasting. Note that when a statistical model is used to represent Guggenheim Diversified 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 Criteria14.8108
BiasArithmetic mean of the errors None
MADMean absolute deviation0.0
MAPEMean absolute percentage error0.0
SAESum of the absolute errors0.0
The eieght-period moving average method has an advantage over other forecasting models in that it does smooth out peaks and valleys in a set of daily observations. Guggenheim Diversified 20-period moving average forecast can only be used reliably to predict one or two periods into the future.

Predictive Modules for Guggenheim Diversified

There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Guggenheim Diversified. 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
25.4325.4325.43
Details
Intrinsic
Valuation
LowRealHigh
25.4325.4325.43
Details
Bollinger
Band Projection (param)
LowMiddleHigh
25.4325.4325.43
Details
Please note, it is not enough to conduct a financial or market analysis of a single entity such as Guggenheim Diversified. Your research has to be compared to or analyzed against Guggenheim Diversified's peers to derive any actionable benefits. When done correctly, Guggenheim Diversified's competitive analysis will give you plenty of quantitative and qualitative data to validate your investment decisions or develop an entirely new strategy toward taking a position in Guggenheim Diversified.

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

Guggenheim Diversified Market Strength Events

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

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 Guggenheim Mutual Fund

Guggenheim Diversified financial ratios help investors to determine whether Guggenheim 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 Guggenheim with respect to the benefits of owning Guggenheim Diversified security.
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