Applied DB Stock Forward View - Simple Regression

Applied DB Additional Predictive Modules

Most predictive techniques to examine Applied price help traders to determine how to time the market. We provide a combination of tools to recognize potential entry and exit points for Applied using various technical indicators. When you analyze Applied 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. Simple Regression model is a single variable regression model that attempts to put a straight line through Applied DB 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.

Applied DB Simple Regression Price Forecast For the 24th of February

Given 90 days horizon, the Simple Regression forecasted value of Applied DB Public on the next trading day is expected to be 0.57 with a mean absolute deviation of 0.01, mean absolute percentage error of 0.0001, and the sum of the absolute errors of 0.54.

Applied DB Stock Forecast Pattern

Backtest Applied DB

Applied DB Price Prediction

Research Analysis

Applied DB Forecasted Value

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 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. 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 Applied DB Public 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 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 Low Estimated High 0.03 0.58 2.85 Details

Intrinsic Valuation Low Real High 0.02 0.49 2.76 Details

Bollinger Band Projection (param) Low Middle High 0.30 0.58 0.87 Details

Applied DB After-Hype Price Density Analysis

Applied DB Estimiated After-Hype Price Volatility

Applied DB Stock Price Outlook Analysis

Notes

Applied DB Hype Timeline

Applied DB Public is presently traded for 0.58on Thailand Exchange of Thailand. The entity stock is not elastic to its hype. The average elasticity to hype of competition is 0.0. Applied is forecasted not to react to the next headline, with the price staying at about the same level, and average media hype impact volatility is insignificant. The immediate return on the next news is forecasted to be very small, whereas the daily expected return is presently at -0.06%. %. The volatility of related hype on Applied DB is about 0.0%, with the expected price after the next announcement by competition of 0.58. About 45.0% of the company shares are held by company insiders. The company has price-to-book (P/B) ratio of 1.37. Some equities with similar Price to Book (P/B) outperform the market in the long run. Applied DB Public last dividend was issued on the 27th of April 2022. The entity had 11:10 split on the 7th of January 2022. Assuming the 90 days trading horizon the next forecasted press release will be in 5 to 10 days. Check out Historical Fundamental Analysis of Applied DB to cross-verify your projections.

Applied DB Related Hype Analysis

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

Risk & Return

Correlation

Applied DB Market Strength Events

Applied DB Risk Indicators

Story Coverage note for Applied DB

Other Macroaxis Stories

Other Information on Investing in Applied Stock