Green Resources Stock Forecast - Simple Regression
| GREEN Stock | THB 0.64 0.01 1.59% |
The Simple Regression forecasted value of Green Resources Public on the next trading day is expected to be 0.62 with a mean absolute deviation of 0.01 and the sum of the absolute errors of 0.74. Green Stock Forecast is based on your current time horizon. Investors can use this forecasting interface to forecast Green Resources stock prices and determine the direction of Green Resources Public's future trends based on various well-known forecasting models. We recommend always using this module together with an analysis of Green Resources' historical fundamentals, such as revenue growth or operating cash flow patterns.
As of now the value of rsi of Green Resources' share price is below 20 . This usually indicates that the stock is significantly oversold. The fundamental principle of the Relative Strength Index (RSI) is to quantify the velocity at which market participants are driving the price of a financial instrument upwards or downwards. Momentum 0
Sell Peaked
Oversold | Overbought |
Using Green Resources hype-based prediction, you can estimate the value of Green Resources Public from the perspective of Green Resources response to recently generated media hype and the effects of current headlines on its competitors.
The Simple Regression forecasted value of Green Resources Public on the next trading day is expected to be 0.62 with a mean absolute deviation of 0.01 and the sum of the absolute errors of 0.74. Green Resources after-hype prediction price | THB 0.64 |
There is no one specific way to measure market sentiment using hype analysis or a similar predictive technique. This prediction method should be used in combination with more fundamental and traditional techniques such as stock price forecasting, technical analysis, analysts consensus, earnings estimates, and various momentum models.
Green |
Green Resources Additional Predictive Modules
Most predictive techniques to examine Green price help traders to determine how to time the market. We provide a combination of tools to recognize potential entry and exit points for Green using various technical indicators. When you analyze Green charts, please remember that the event formation may indicate an entry point for a short seller, and look at other indicators across different periods to confirm that a breakdown or reversion is likely to occur.| Cycle Indicators | ||
| Math Operators | ||
| Math Transform | ||
| Momentum Indicators | ||
| Overlap Studies | ||
| Pattern Recognition | ||
| Price Transform | ||
| Statistic Functions | ||
| Volatility Indicators | ||
| Volume Indicators |
Green Resources Simple Regression Price Forecast For the 17th of January 2026
Given 90 days horizon, the Simple Regression forecasted value of Green Resources Public on the next trading day is expected to be 0.62 with a mean absolute deviation of 0.01, mean absolute percentage error of 0.0002, and the sum of the absolute errors of 0.74.Please note that although there have been many attempts to predict Green 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 Green Resources' next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).
Green Resources Stock Forecast Pattern
| Backtest Green Resources | Green Resources Price Prediction | Buy or Sell Advice |
Green Resources Forecasted Value
In the context of forecasting Green Resources' 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. Green Resources' downside and upside margins for the forecasting period are 0.01 and 2.74, respectively. We have considered Green Resources' 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.
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 Green Resources stock data series using in forecasting. Note that when a statistical model is used to represent Green Resources 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.| AIC | Akaike Information Criteria | 111.4298 |
| Bias | Arithmetic mean of the errors | None |
| MAD | Mean absolute deviation | 0.0119 |
| MAPE | Mean absolute percentage error | 0.0185 |
| SAE | Sum of the absolute errors | 0.7365 |
Predictive Modules for Green Resources
There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Green Resources Public. 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.Other Forecasting Options for Green Resources
For every potential investor in Green, whether a beginner or expert, Green Resources' price movement is the inherent factor that sparks whether it is viable to invest in it or hold it better. Green Stock price charts are filled with many 'noises.' These noises can hugely alter the decision one can make regarding investing in Green. Basic forecasting techniques help filter out the noise by identifying Green Resources' price trends.Green Resources 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 Green Resources stock to make a market-neutral strategy. Peer analysis of Green Resources could also be used in its relative valuation, which is a method of valuing Green Resources by comparing valuation metrics with similar companies.
| Risk & Return | Correlation |
Green Resources Public 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 Green Resources' 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 Green Resources' current price.| Cycle Indicators | ||
| Math Operators | ||
| Math Transform | ||
| Momentum Indicators | ||
| Overlap Studies | ||
| Pattern Recognition | ||
| Price Transform | ||
| Statistic Functions | ||
| Volatility Indicators | ||
| Volume Indicators |
Green Resources Market Strength Events
Market strength indicators help investors to evaluate how Green Resources stock reacts to ongoing and evolving market conditions. The investors can use it to make informed decisions about market timing, and determine when trading Green Resources shares will generate the highest return on investment. By undertsting and applying Green Resources stock market strength indicators, traders can identify Green Resources Public entry and exit signals to maximize returns.
| Accumulation Distribution | 6001.78 | |||
| Daily Balance Of Power | 0.25 | |||
| Rate Of Daily Change | 1.02 | |||
| Day Median Price | 0.63 | |||
| Day Typical Price | 0.63 | |||
| Price Action Indicator | 0.015 | |||
| Period Momentum Indicator | 0.01 |
Green Resources Risk Indicators
The analysis of Green Resources' 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 Green Resources' investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting green 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.
| Mean Deviation | 1.51 | |||
| Standard Deviation | 2.03 | |||
| Variance | 4.14 |
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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Try AI Portfolio ProphetOther Information on Investing in Green Stock
Green Resources financial ratios help investors to determine whether Green 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 Green with respect to the benefits of owning Green Resources security.