JMT Network Stock Forecast - Simple Regression

JMT Stock  THB 19.10  0.20  1.04%   
The Simple Regression forecasted value of JMT Network Services on the next trading day is expected to be 19.04 with a mean absolute deviation of 0.80 and the sum of the absolute errors of 49.79. JMT Stock Forecast is based on your current time horizon.
  
Simple Regression model is a single variable regression model that attempts to put a straight line through JMT Network 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.

JMT Network Simple Regression Price Forecast For the 13th of December 2024

Given 90 days horizon, the Simple Regression forecasted value of JMT Network Services on the next trading day is expected to be 19.04 with a mean absolute deviation of 0.80, mean absolute percentage error of 1.03, and the sum of the absolute errors of 49.79.
Please note that although there have been many attempts to predict JMT 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 JMT Network's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).

JMT Network Stock Forecast Pattern

Backtest JMT NetworkJMT Network Price PredictionBuy or Sell Advice 

JMT Network Forecasted Value

In the context of forecasting JMT Network'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. JMT Network's downside and upside margins for the forecasting period are 15.65 and 22.43, respectively. We have considered JMT Network'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
19.10
19.04
Expected Value
22.43
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 JMT Network stock data series using in forecasting. Note that when a statistical model is used to represent JMT Network 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 Criteria119.9748
BiasArithmetic mean of the errors None
MADMean absolute deviation0.8031
MAPEMean absolute percentage error0.0425
SAESum of the absolute errors49.7946
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 JMT Network Services 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 JMT Network

There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as JMT Network Services. 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
15.7119.1022.49
Details
Intrinsic
Valuation
LowRealHigh
12.7216.1119.50
Details
Bollinger
Band Projection (param)
LowMiddleHigh
17.0118.7520.49
Details

Other Forecasting Options for JMT Network

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

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

JMT Network Services 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 JMT Network'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 JMT Network's current price.

JMT Network Market Strength Events

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

JMT Network Risk Indicators

The analysis of JMT Network'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 JMT Network's investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting jmt 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.

Building efficient market-beating portfolios requires time, education, and a lot of computing power!

The Portfolio Architect is an AI-driven system that provides multiple benefits to our users by leveraging cutting-edge machine learning algorithms, statistical analysis, and predictive modeling to automate the process of asset selection and portfolio construction, saving time and reducing human error for individual and institutional investors.

Try AI Portfolio Architect

Other Information on Investing in JMT Stock

JMT Network financial ratios help investors to determine whether JMT 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 JMT with respect to the benefits of owning JMT Network security.