PT Astra Stock Forecast - Simple Regression

ASJA Stock  EUR 0.29  0.01  3.57%   
The Simple Regression forecasted value of PT Astra International on the next trading day is expected to be 0.29 with a mean absolute deviation of 0.01 and the sum of the absolute errors of 0.49. ASJA Stock Forecast is based on your current time horizon. We recommend always using this module together with an analysis of PT Astra's historical fundamentals, such as revenue growth or operating cash flow patterns.
  
Simple Regression model is a single variable regression model that attempts to put a straight line through PT Astra price points. This line is defined by its gradient or slope, and the point at which it intercepts the x-axis. Mathematically, assuming the independent variable is X and the dependent variable is Y, then this line can be represented as: Y = intercept + slope * X.

PT Astra Simple Regression Price Forecast For the 24th of November

Given 90 days horizon, the Simple Regression forecasted value of PT Astra International on the next trading day is expected to be 0.29 with a mean absolute deviation of 0.01, mean absolute percentage error of 0.0001, and the sum of the absolute errors of 0.49.
Please note that although there have been many attempts to predict ASJA 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 PT Astra's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).

PT Astra Stock Forecast Pattern

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PT Astra Forecasted Value

In the context of forecasting PT Astra's 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. PT Astra's downside and upside margins for the forecasting period are 0 and 4.16, respectively. We have considered PT Astra's 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
0.29
0.29
Expected Value
4.16
Upside

Model Predictive Factors

The below table displays some essential indicators generated by the model showing the Simple Regression forecasting method's relative quality and the estimations of the prediction error of PT Astra stock data series using in forecasting. Note that when a statistical model is used to represent PT Astra 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 Criteria108.8993
BiasArithmetic mean of the errors None
MADMean absolute deviation0.008
MAPEMean absolute percentage error0.0271
SAESum of the absolute errors0.4891
In general, regression methods applied to historical equity returns or prices series is an area of active research. In recent decades, new methods have been developed for robust regression of price series such as PT Astra International historical returns. These new methods are regression involving correlated responses such as growth curves and different regression methods accommodating various types of missing data.

Predictive Modules for PT Astra

There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as PT Astra International. 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
0.010.294.16
Details
Intrinsic
Valuation
LowRealHigh
0.010.254.12
Details
Please note, it is not enough to conduct a financial or market analysis of a single entity such as PT Astra. Your research has to be compared to or analyzed against PT Astra's peers to derive any actionable benefits. When done correctly, PT Astra's competitive analysis will give you plenty of quantitative and qualitative data to validate your investment decisions or develop an entirely new strategy toward taking a position in PT Astra International.

Other Forecasting Options for PT Astra

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

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

PT Astra International 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 PT Astra'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 PT Astra's current price.

PT Astra Market Strength Events

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

PT Astra Risk Indicators

The analysis of PT Astra's 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 PT Astra's investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting asja 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.

Currently Active Assets on Macroaxis

Other Information on Investing in ASJA Stock

PT Astra financial ratios help investors to determine whether ASJA 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 ASJA with respect to the benefits of owning PT Astra security.