Stryve Foods Stock Forecast - Triple Exponential Smoothing

Triple exponential smoothing for Stryve Foods - 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 Stryve Foods 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 Stryve Foods price movement. However, neither of these exponential smoothing models address any seasonality of Stryve Foods.

Stryve Foods Triple Exponential Smoothing Price Forecast For the 28th of February

Given 90 days horizon, the Triple Exponential Smoothing forecasted value of Stryve Foods on the next trading day is expected to be 0.01 with a mean absolute deviation of 0, mean absolute percentage error of 0.00000774, and the sum of the absolute errors of 0.12.

Stryve Foods Stock 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 Stryve Foods stock data series using in forecasting. Note that when a statistical model is used to represent Stryve Foods stock, 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 Stryve Foods 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 Stryve Foods observations.

Predictive Modules for Stryve Foods

There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Stryve Foods. Regardless of method or technology, however, to accurately forecast the stock market is more a matter of luck rather than a particular technique. Nevertheless, trying to predict the stock 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 0.00 0 45.93 Details

Intrinsic Valuation Low Real High 0.00 0 45.93 Details

Bollinger Band Projection (param) Low Middle High 0.0007 0.01 0.01 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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