Applied DB Stock Forecast - 20 Period Moving Average

ADB Stock  THB 0.88  0.02  2.22%   
The 20 Period Moving Average forecasted value of Applied DB Public on the next trading day is expected to be 0.88 with a mean absolute deviation of 0.06 and the sum of the absolute errors of 2.61. Applied Stock Forecast is based on your current time horizon.
  
A commonly used 20-period moving average forecast model for Applied DB Public is based on a synthetically constructed Applied DBdaily price series in which the value for a trading day is replaced by the mean of that value and the values for 20 of preceding and succeeding time periods. This model is best suited for price series data that changes over time.

Applied DB 20 Period Moving Average Price Forecast For the 27th of December

Given 90 days horizon, the 20 Period Moving Average forecasted value of Applied DB Public on the next trading day is expected to be 0.88 with a mean absolute deviation of 0.06, mean absolute percentage error of 0.01, and the sum of the absolute errors of 2.61.
Please note that although there have been many attempts to predict Applied 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 Applied DB's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).

Applied DB Stock Forecast Pattern

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Applied DB Forecasted Value

In the context of forecasting Applied DB'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. Applied DB's downside and upside margins for the forecasting period are 0.01 and 5.33, respectively. We have considered Applied DB'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
0.88
0.88
Expected Value
5.33
Upside

Model Predictive Factors

The below table displays some essential indicators generated by the model showing the 20 Period Moving Average forecasting method's relative quality and the estimations of the prediction error of Applied DB stock data series using in forecasting. Note that when a statistical model is used to represent Applied DB 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 Criteria76.2602
BiasArithmetic mean of the errors 0.0219
MADMean absolute deviation0.0636
MAPEMean absolute percentage error0.0724
SAESum of the absolute errors2.6095
The eieght-period moving average method has an advantage over other forecasting models in that it does smooth out peaks and valleys in a set of daily observations. Applied DB Public 20-period moving average forecast can only be used reliably to predict one or two periods into the future.

Predictive Modules for Applied DB

There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Applied DB 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.
Hype
Prediction
LowEstimatedHigh
0.040.885.33
Details
Intrinsic
Valuation
LowRealHigh
0.040.755.20
Details

Other Forecasting Options for Applied DB

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

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

Applied DB 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 Applied DB'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 Applied DB's current price.

Applied DB Market Strength Events

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

Applied DB Risk Indicators

The analysis of Applied DB'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 Applied DB's investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting applied 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.

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Other Information on Investing in Applied Stock

Applied DB financial ratios help investors to determine whether Applied 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 Applied with respect to the benefits of owning Applied DB security.