Tung Ho Stock Forecast - 4 Period Moving Average

1414 Stock  TWD 22.80  0.05  0.22%   
The 4 Period Moving Average forecasted value of Tung Ho Textile on the next trading day is expected to be 22.73 with a mean absolute deviation of 0.38 and the sum of the absolute errors of 21.51. Tung Stock Forecast is based on your current time horizon.
  
A four-period moving average forecast model for Tung Ho Textile 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.

Tung Ho 4 Period Moving Average Price Forecast For the 28th of November

Given 90 days horizon, the 4 Period Moving Average forecasted value of Tung Ho Textile on the next trading day is expected to be 22.73 with a mean absolute deviation of 0.38, mean absolute percentage error of 0.30, and the sum of the absolute errors of 21.51.
Please note that although there have been many attempts to predict Tung 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 Tung Ho's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).

Tung Ho Stock Forecast Pattern

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Tung Ho Forecasted Value

In the context of forecasting Tung Ho'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. Tung Ho's downside and upside margins for the forecasting period are 21.15 and 24.30, respectively. We have considered Tung Ho'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
22.80
22.73
Expected Value
24.30
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 Tung Ho stock data series using in forecasting. Note that when a statistical model is used to represent Tung Ho 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 Criteria109.5451
BiasArithmetic mean of the errors -0.0226
MADMean absolute deviation0.3774
MAPEMean absolute percentage error0.0165
SAESum of the absolute errors21.5125
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 Tung Ho. However, it also has several disadvantages. In particular this model does not produce an actual prediction equation for Tung Ho Textile and therefore, it cannot be a useful forecasting tool for medium or long range price predictions

Predictive Modules for Tung Ho

There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Tung Ho Textile. 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
21.2322.8024.37
Details
Intrinsic
Valuation
LowRealHigh
17.7319.3025.08
Details
Bollinger
Band Projection (param)
LowMiddleHigh
21.8222.6423.46
Details

Other Forecasting Options for Tung Ho

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

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

Tung Ho Textile 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 Tung Ho'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 Tung Ho's current price.

Tung Ho Market Strength Events

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

Tung Ho Risk Indicators

The analysis of Tung Ho'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 Tung Ho's investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting tung 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.

Also Currently Popular

Analyzing currently trending equities could be an opportunity to develop a better portfolio based on different market momentums that they can trigger. Utilizing the top trending stocks is also useful when creating a market-neutral strategy or pair trading technique involving a short or a long position in a currently trending equity.

Additional Tools for Tung Stock Analysis

When running Tung Ho's price analysis, check to measure Tung Ho's market volatility, profitability, liquidity, solvency, efficiency, growth potential, financial leverage, and other vital indicators. We have many different tools that can be utilized to determine how healthy Tung Ho is operating at the current time. Most of Tung Ho's value examination focuses on studying past and present price action to predict the probability of Tung Ho's future price movements. You can analyze the entity against its peers and the financial market as a whole to determine factors that move Tung Ho's price. Additionally, you may evaluate how the addition of Tung Ho to your portfolios can decrease your overall portfolio volatility.