Allianzgi Global Mutual Fund Forecast - Triple Exponential Smoothing

Triple exponential smoothing for Allianzgi Global - also known as the Winters method - is a refinement of the popular double exponential smoothing model with the addition of periodicity (seasonality) component. Simple exponential smoothing technique works best with data where there are no trend or seasonality components to the data. When Allianzgi Global prices exhibit either an increasing or decreasing trend over time, simple exponential smoothing forecasts tend to lag behind observations. Double exponential smoothing is designed to address this type of data series by taking into account any trend in Allianzgi Global price movement. However, neither of these exponential smoothing models address any seasonality of Allianzgi Global Sus.

Allianzgi Global Triple Exponential Smoothing Price Forecast For the 16th of January 2025

Given 90 days horizon, the Triple Exponential Smoothing forecasted value of Allianzgi Global Sustainability on the next trading day is expected to be 14.10 with a mean absolute deviation of 0.06, mean absolute percentage error of 0.01, and the sum of the absolute errors of 3.33.

Allianzgi Global Mutual Fund Forecast Pattern

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Model Predictive Factors

The below table displays some essential indicators generated by the model showing the Triple Exponential Smoothing forecasting method's relative quality and the estimations of the prediction error of Allianzgi Global mutual fund data series using in forecasting. Note that when a statistical model is used to represent Allianzgi Global 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. As with simple exponential smoothing, in triple exponential smoothing models past Allianzgi Global observations are given exponentially smaller weights as the observations get older. In other words, recent observations are given relatively more weight in forecasting than the older Allianzgi Global Sustainability observations.

Predictive Modules for Allianzgi Global

There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Allianzgi Global Sus. 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 13.54 14.10 14.66 Details

Intrinsic Valuation Low Real High 13.34 13.90 14.46 Details

Bollinger Band Projection (param) Low Middle High 14.01 14.22 14.42 Details

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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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