Kang Yong Stock Forecast - 4 Period Moving Average

KYE Stock  THB 287.00  1.00  0.35%   
The 4 Period Moving Average forecasted value of Kang Yong Electric on the next trading day is expected to be 287.25 with a mean absolute deviation of 0.96 and the sum of the absolute errors of 54.75. Kang Stock Forecast is based on your current time horizon.
  
A four-period moving average forecast model for Kang Yong Electric is based on an artificially constructed daily price series in which the value for a given day is replaced by the mean of that value and the values for four preceding and succeeding time periods. This model is best suited to forecast equities with high volatility.

Kang Yong 4 Period Moving Average Price Forecast For the 3rd of December

Given 90 days horizon, the 4 Period Moving Average forecasted value of Kang Yong Electric on the next trading day is expected to be 287.25 with a mean absolute deviation of 0.96, mean absolute percentage error of 1.50, and the sum of the absolute errors of 54.75.
Please note that although there have been many attempts to predict Kang 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 Kang Yong's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).

Kang Yong Stock Forecast Pattern

Backtest Kang YongKang Yong Price PredictionBuy or Sell Advice 

Kang Yong Forecasted Value

In the context of forecasting Kang Yong'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. Kang Yong's downside and upside margins for the forecasting period are 161.26 and 413.24, respectively. We have considered Kang Yong'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
287.00
161.26
Downside
287.25
Expected Value
413.24
Upside

Model Predictive Factors

The below table displays some essential indicators generated by the model showing the 4 Period Moving Average forecasting method's relative quality and the estimations of the prediction error of Kang Yong stock data series using in forecasting. Note that when a statistical model is used to represent Kang Yong 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 Criteria111.1652
BiasArithmetic mean of the errors 0.0307
MADMean absolute deviation0.9605
MAPEMean absolute percentage error0.0033
SAESum of the absolute errors54.75
The four period moving average method has an advantage over other forecasting models in that it does smooth out peaks and troughs in a set of daily price observations of Kang Yong. However, it also has several disadvantages. In particular this model does not produce an actual prediction equation for Kang Yong Electric and therefore, it cannot be a useful forecasting tool for medium or long range price predictions

Predictive Modules for Kang Yong

There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Kang Yong Electric. 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
14.35287.0028,987
Details
Intrinsic
Valuation
LowRealHigh
11.96239.2528,939
Details
Bollinger
Band Projection (param)
LowMiddleHigh
286.79290.21293.62
Details

Other Forecasting Options for Kang Yong

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

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

Kang Yong Electric 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 Kang Yong'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 Kang Yong's current price.

Kang Yong Market Strength Events

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

Kang Yong Risk Indicators

The analysis of Kang Yong'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 Kang Yong's investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting kang 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 Kang Stock

Kang Yong financial ratios help investors to determine whether Kang 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 Kang with respect to the benefits of owning Kang Yong security.