Bank Artha Stock Forecast - Polynomial Regression

Bank Artha polinomial regression implements a single variable polynomial regression model using the daily prices as the independent variable. The coefficients of the regression for Bank Artha Graha as well as the accuracy indicators are determined from the period prices.

Bank Artha Polynomial Regression Price Forecast For the 30th of November

Given 90 days horizon, the Polynomial Regression forecasted value of Bank Artha Graha on the next trading day is expected to be 317.02 with a mean absolute deviation of 20.09, mean absolute percentage error of 837.00, and the sum of the absolute errors of 1,245.

Bank Artha Stock Forecast Pattern

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Bank Artha Forecasted Value

Model Predictive Factors

The below table displays some essential indicators generated by the model showing the Polynomial Regression 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. A single variable polynomial regression model attempts to put a curve through the Bank Artha historical price points. Mathematically, assuming the independent variable is X and the dependent variable is Y, this line can be indicated as: Y = a₀ + a₁*X + a₂*X² + a₃*X³ + ... + a_m*X^m

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.

Bank Artha Related Equities

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.

Bank Artha Market Strength Events

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