Bank Artha Stock Forecast - Naive Prediction

A naive forecasting model for Bank Artha is a special case of the moving average forecasting where the number of periods used for smoothing is one. Therefore, the forecast of Bank Artha Graha 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.

Bank Artha Naive Prediction Price Forecast For the 30th of November

Given 90 days horizon, the Naive Prediction forecasted value of Bank Artha Graha on the next trading day is expected to be 439.79 with a mean absolute deviation of 15.41, mean absolute percentage error of 336.23, and the sum of the absolute errors of 955.46.

Bank Artha Stock 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 Bank Artha stock data series using in forecasting. Note that when a statistical model is used to represent Bank Artha 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. This model is not at all useful as a medium-long range forecasting tool of Bank Artha Graha. 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 Bank Artha. 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 Bank Artha

There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Bank Artha Graha. 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 349.98 360.00 370.02 Details

Intrinsic Valuation Low Real High 276.23 286.25 396.00 Details

Bollinger Band Projection (param) Low Middle High 51.62 174.96 298.30 Details

Other Forecasting Options for Bank Artha

For every potential investor in Bank, whether a beginner or expert, Bank Artha's price movement is the inherent factor that sparks whether it is viable to invest in it or hold it better. Bank Stock price charts are filled with many 'noises.' These noises can hugely alter the decision one can make regarding investing in Bank. Basic forecasting techniques help filter out the noise by identifying Bank Artha's price trends.

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Risk & Return

Correlation

Bank Artha Graha Technical and Predictive Analytics

The stock market is financially volatile. Despite the volatility, there exist limitless possibilities of gaining profits and building passive income portfolios. With the complexity of Bank Artha's price movements, a comprehensive understanding of forecasting methods that an investor can rely on to make the right move is invaluable. These methods predict trends that assist an investor in predicting the movement of Bank Artha's current price.

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