Savola Stock Forecast - Polynomial Regression

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

Savola Polynomial Regression Price Forecast For the 10th of June

Given 90 days horizon, the Polynomial Regression forecasted value of Savola Group on the next trading day is expected to be 40.07 with a mean absolute deviation of 0.70, mean absolute percentage error of 0.75, and the sum of the absolute errors of 42.81.

Savola Stock Forecast Pattern

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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 Savola stock data series using in forecasting. Note that when a statistical model is used to represent Savola 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 Savola 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 Savola

There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Savola Group. Regardless of method or technology, however, to accurately forecast the stock or bond 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 36.27 38.75 41.23 Details

Intrinsic Valuation Low Real High 26.58 29.06 42.63 Details

Other Forecasting Options for Savola

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

Savola Related Equities

Risk & Return

Correlation

Savola Group 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 Savola'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 Savola's current price.

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Altman Z Score Details

Intrinsic Valuation Details

Financial Analysis Details

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Technical Analysis Details

Please note, there is a significant difference between Savola's value and its price as these two are different measures arrived at by different means. Investors typically determine if Savola is a good investment by looking at such factors as earnings, sales, fundamental and technical indicators, competition as well as analyst projections. However, Savola's price is the amount at which it trades on the open market and represents the number that a seller and buyer find agreeable to each party. $(function(){ //alert('2050.SR'); displaySymbolSentimentChart('2050.SR','sentimentChart'); });