Applicad Public Stock Forecast - Polynomial Regression
| APP Stock | THB 1.71 0.13 7.07% |
The Polynomial Regression forecasted value of Applicad Public on the next trading day is expected to be 1.75 with a mean absolute deviation of 0.09 and the sum of the absolute errors of 5.80. Applicad Stock Forecast is based on your current time horizon.
Applicad |
Applicad Public Polynomial Regression Price Forecast For the 29th of November
Given 90 days horizon, the Polynomial Regression forecasted value of Applicad Public on the next trading day is expected to be 1.75 with a mean absolute deviation of 0.09, mean absolute percentage error of 0.02, and the sum of the absolute errors of 5.80.Please note that although there have been many attempts to predict Applicad 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 Applicad Public's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).
Applicad Public Stock Forecast Pattern
| Backtest Applicad Public | Applicad Public Price Prediction | Buy or Sell Advice |
Applicad Public Forecasted Value
In the context of forecasting Applicad Public'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. Applicad Public's downside and upside margins for the forecasting period are 0.02 and 6.75, respectively. We have considered Applicad Public'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.
Model Predictive Factors
The below table displays some essential indicators generated by the model showing the Polynomial Regression forecasting method's relative quality and the estimations of the prediction error of Applicad Public stock data series using in forecasting. Note that when a statistical model is used to represent Applicad Public 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.| AIC | Akaike Information Criteria | 115.8523 |
| Bias | Arithmetic mean of the errors | None |
| MAD | Mean absolute deviation | 0.0935 |
| MAPE | Mean absolute percentage error | 0.0563 |
| SAE | Sum of the absolute errors | 5.7953 |
Predictive Modules for Applicad Public
There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Applicad 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.Other Forecasting Options for Applicad Public
For every potential investor in Applicad, whether a beginner or expert, Applicad Public's price movement is the inherent factor that sparks whether it is viable to invest in it or hold it better. Applicad Stock price charts are filled with many 'noises.' These noises can hugely alter the decision one can make regarding investing in Applicad. Basic forecasting techniques help filter out the noise by identifying Applicad Public's price trends.Applicad Public 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 Applicad Public stock to make a market-neutral strategy. Peer analysis of Applicad Public could also be used in its relative valuation, which is a method of valuing Applicad Public by comparing valuation metrics with similar companies.
| Risk & Return | Correlation |
Applicad 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 Applicad Public'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 Applicad Public's current price.| Cycle Indicators | ||
| Math Operators | ||
| Math Transform | ||
| Momentum Indicators | ||
| Overlap Studies | ||
| Pattern Recognition | ||
| Price Transform | ||
| Statistic Functions | ||
| Volatility Indicators | ||
| Volume Indicators |
Applicad Public Market Strength Events
Market strength indicators help investors to evaluate how Applicad Public stock reacts to ongoing and evolving market conditions. The investors can use it to make informed decisions about market timing, and determine when trading Applicad Public shares will generate the highest return on investment. By undertsting and applying Applicad Public stock market strength indicators, traders can identify Applicad Public entry and exit signals to maximize returns.
Applicad Public Risk Indicators
The analysis of Applicad Public'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 Applicad Public's investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting applicad 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.
| Mean Deviation | 2.86 | |||
| Semi Deviation | 3.51 | |||
| Standard Deviation | 5.25 | |||
| Variance | 27.53 | |||
| Downside Variance | 17.73 | |||
| Semi Variance | 12.3 | |||
| Expected Short fall | (4.05) |
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 ArchitectOther Information on Investing in Applicad Stock
Applicad Public financial ratios help investors to determine whether Applicad 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 Applicad with respect to the benefits of owning Applicad Public security.