Sawit Sumbermas Stock Forecast - Polynomial Regression

SSMS Stock  IDR 1,030  35.00  3.29%   
The Polynomial Regression forecasted value of Sawit Sumbermas Sarana on the next trading day is expected to be 1,012 with a mean absolute deviation of 18.09 and the sum of the absolute errors of 1,122. Sawit Stock Forecast is based on your current time horizon.
  
Sawit Sumbermas polinomial regression implements a single variable polynomial regression model using the daily prices as the independent variable. The coefficients of the regression for Sawit Sumbermas Sarana as well as the accuracy indicators are determined from the period prices.

Sawit Sumbermas Polynomial Regression Price Forecast For the 23rd of November

Given 90 days horizon, the Polynomial Regression forecasted value of Sawit Sumbermas Sarana on the next trading day is expected to be 1,012 with a mean absolute deviation of 18.09, mean absolute percentage error of 500.07, and the sum of the absolute errors of 1,122.
Please note that although there have been many attempts to predict Sawit Stock 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 Sawit Sumbermas' next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).

Sawit Sumbermas Stock Forecast Pattern

Backtest Sawit SumbermasSawit Sumbermas Price PredictionBuy or Sell Advice 

Sawit Sumbermas Forecasted Value

In the context of forecasting Sawit Sumbermas' Stock value on the next trading day, we examine the predictive performance of the model to find good statistically significant boundaries of downside and upside scenarios. Sawit Sumbermas' downside and upside margins for the forecasting period are 1,010 and 1,015, respectively. We have considered Sawit Sumbermas' daily market price to evaluate the above model's predictive performance. Remember, however, there is no scientific proof or empirical evidence that traditional linear or nonlinear forecasting models outperform artificial intelligence and frequency domain models to provide accurate forecasts consistently.
Market Value
1,030
1,012
Expected Value
1,015
Upside

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 Sawit Sumbermas stock data series using in forecasting. Note that when a statistical model is used to represent Sawit Sumbermas 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.
AICAkaike Information Criteria126.1631
BiasArithmetic mean of the errors None
MADMean absolute deviation18.0919
MAPEMean absolute percentage error0.0163
SAESum of the absolute errors1121.6984
A single variable polynomial regression model attempts to put a curve through the Sawit Sumbermas 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 + ... + am*Xm

Predictive Modules for Sawit Sumbermas

There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Sawit Sumbermas Sarana. 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
LowEstimatedHigh
1,0281,0301,032
Details
Intrinsic
Valuation
LowRealHigh
895.51897.751,133
Details
Bollinger
Band Projection (param)
LowMiddleHigh
1,0321,1231,215
Details

Other Forecasting Options for Sawit Sumbermas

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

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

Sawit Sumbermas Sarana 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 Sawit Sumbermas' 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 Sawit Sumbermas' current price.

Sawit Sumbermas Market Strength Events

Market strength indicators help investors to evaluate how Sawit Sumbermas stock reacts to ongoing and evolving market conditions. The investors can use it to make informed decisions about market timing, and determine when trading Sawit Sumbermas shares will generate the highest return on investment. By undertsting and applying Sawit Sumbermas stock market strength indicators, traders can identify Sawit Sumbermas Sarana entry and exit signals to maximize returns.

Sawit Sumbermas Risk Indicators

The analysis of Sawit Sumbermas' basic risk indicators is one of the essential steps in accurately forecasting its future price. The process involves identifying the amount of risk involved in Sawit Sumbermas' investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting sawit stock prices, we also provide a set of basic risk indicators that can assist in the individual investment decision or help in hedging the risk of your existing portfolios.
Please note, the risk measures we provide can be used independently or collectively to perform a risk assessment. When comparing two potential investments, we recommend comparing similar equities with homogenous growth potential and valuation from related markets to determine which investment holds the most risk.

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Other Information on Investing in Sawit Stock

Sawit Sumbermas financial ratios help investors to determine whether Sawit Stock 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 Sawit with respect to the benefits of owning Sawit Sumbermas security.