Morgan Stanley Mutual Fund Forecast - Naive Prediction

A naive forecasting model for Morgan Stanley is a special case of the moving average forecasting where the number of periods used for smoothing is one. Therefore, the forecast of Morgan Stanley Institutional value for a given trading day is simply the observed value for the previous period. Due to the simplistic nature of the naive forecasting model, it can only be used to forecast up to one period.

Morgan Stanley Naive Prediction Price Forecast For the 30th of December

Given 90 days horizon, the Naive Prediction forecasted value of Morgan Stanley Institutional on the next trading day is expected to be 10.06 with a mean absolute deviation of 0.05, mean absolute percentage error of 0.01, and the sum of the absolute errors of 3.34.

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Model Predictive Factors

The below table displays some essential indicators generated by the model showing the Naive Prediction forecasting method's relative quality and the estimations of the prediction error of Morgan Stanley mutual fund data series using in forecasting. Note that when a statistical model is used to represent Morgan Stanley 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. This model is not at all useful as a medium-long range forecasting tool of Morgan Stanley Institutional. This model is simplistic and is included partly for completeness and partly because of its simplicity. It is unlikely that you'll want to use this model directly to predict Morgan Stanley. Instead, consider using either the moving average model or the more general weighted moving average model with a higher (i.e., greater than 1) number of periods, and possibly a different set of weights.

Predictive Modules for Morgan Stanley

There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Morgan Stanley Insti. 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 9.52 10.09 10.66 Details

Intrinsic Valuation Low Real High 9.28 9.85 10.42 Details

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