Goldman Sachs Mutual Fund Forecast - Naive Prediction

GCGUX Fund  USD 18.40  0.00  0.00%   
The Naive Prediction forecasted value of Goldman Sachs Centrated on the next trading day is expected to be 18.40 with a mean absolute deviation of 0 and the sum of the absolute errors of 0. Goldman Mutual Fund Forecast is based on your current time horizon.
  
A naive forecasting model for Goldman Sachs is a special case of the moving average forecasting where the number of periods used for smoothing is one. Therefore, the forecast of Goldman Sachs Centrated 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.

Goldman Sachs Naive Prediction Price Forecast For the 4th of October

Given 90 days horizon, the Naive Prediction forecasted value of Goldman Sachs Centrated on the next trading day is expected to be 18.40 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 Goldman 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 Goldman Sachs' next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).

Goldman Sachs Mutual Fund Forecast Pattern

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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 Goldman Sachs mutual fund data series using in forecasting. Note that when a statistical model is used to represent Goldman Sachs 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 Criteria54.3987
BiasArithmetic mean of the errors None
MADMean absolute deviation0.0
MAPEMean absolute percentage error0.0
SAESum of the absolute errors0.0
This model is not at all useful as a medium-long range forecasting tool of Goldman Sachs Centrated. 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 Goldman Sachs. 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 Goldman Sachs

There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Goldman Sachs Centrated. 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.
Sophisticated investors, who have witnessed many market ups and downs, anticipate that the market will even out over time. This tendency of Goldman Sachs' price to converge to an average value over time is called mean reversion. However, historically, high market prices usually discourage investors that believe in mean reversion to invest, while low prices are viewed as an opportunity to buy.
Hype
Prediction
LowEstimatedHigh
18.4018.4018.40
Details
Intrinsic
Valuation
LowRealHigh
18.4018.4018.40
Details
Bollinger
Band Projection (param)
LowMiddleHigh
18.4018.4018.40
Details

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

Goldman Sachs Market Strength Events

Market strength indicators help investors to evaluate how Goldman Sachs 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 Goldman Sachs shares will generate the highest return on investment. By undertsting and applying Goldman Sachs mutual fund market strength indicators, traders can identify Goldman Sachs Centrated 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 Goldman Mutual Fund

Goldman Sachs financial ratios help investors to determine whether Goldman 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 Goldman with respect to the benefits of owning Goldman Sachs security.
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