Guggenheim Diversified Mutual Fund Forecast - Simple Regression

Simple Regression model is a single variable regression model that attempts to put a straight line through Guggenheim Diversified price points. This line is defined by its gradient or slope, and the point at which it intercepts the x-axis. Mathematically, assuming the independent variable is X and the dependent variable is Y, then this line can be represented as: Y = intercept + slope * X.

Guggenheim Diversified Simple Regression Price Forecast For the 22nd of March

Given 90 days horizon, the Simple Regression 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.

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 Simple Regression 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. In general, regression methods applied to historical equity returns or prices series is an area of active research. In recent decades, new methods have been developed for robust regression of price series such as Guggenheim Diversified Income historical returns. These new methods are regression involving correlated responses such as growth curves and different regression methods accommodating various types of missing data.

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 Low Estimated High 25.43 25.43 25.43 Details

Intrinsic Valuation Low Real High 23.52 23.52 27.97 Details

Bollinger Band Projection (param) Low Middle High 25.43 25.43 25.43 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

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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.

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