Bank Tabungan Stock Forecast - Triple Exponential Smoothing

Triple exponential smoothing for Bank Tabungan - 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 Bank Tabungan 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 Bank Tabungan price movement. However, neither of these exponential smoothing models address any seasonality of Bank Tabungan Negara.

Bank Tabungan Triple Exponential Smoothing Price Forecast For the 13th of December 2024

Given 90 days horizon, the Triple Exponential Smoothing forecasted value of Bank Tabungan Negara on the next trading day is expected to be 1,262 with a mean absolute deviation of 21.03, mean absolute percentage error of 718.42, and the sum of the absolute errors of 1,262.

Bank Tabungan Stock Forecast Pattern

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Bank Tabungan Forecasted Value

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 Bank Tabungan stock data series using in forecasting. Note that when a statistical model is used to represent Bank Tabungan 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 Bank Tabungan 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 Bank Tabungan Negara observations.

Predictive Modules for Bank Tabungan

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 Tabungan Negara. 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 1,253 1,255 1,257 Details

Intrinsic Valuation Low Real High 1,052 1,054 1,380 Details

Bollinger Band Projection (param) Low Middle High 1,184 1,247 1,310 Details

Other Forecasting Options for Bank Tabungan

For every potential investor in Bank, whether a beginner or expert, Bank Tabungan'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 Tabungan's price trends.

Bank Tabungan Related Equities

Risk & Return

Correlation

Bank Tabungan Negara 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 Tabungan'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 Tabungan's current price.

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