Agfa Gevaert Pink Sheet Forecast - Naive Prediction
| AFGVY Stock | USD 2.29 0.00 0.00% |
The Naive Prediction forecasted value of Agfa Gevaert NV on the next trading day is expected to be 2.17 with a mean absolute deviation of 0.04 and the sum of the absolute errors of 2.62. Agfa Pink Sheet Forecast is based on your current time horizon.
Agfa |
Agfa Gevaert Naive Prediction Price Forecast For the 28th of December
Given 90 days horizon, the Naive Prediction forecasted value of Agfa Gevaert NV on the next trading day is expected to be 2.17 with a mean absolute deviation of 0.04, mean absolute percentage error of 0, and the sum of the absolute errors of 2.62.Please note that although there have been many attempts to predict Agfa Pink Sheet 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 Agfa Gevaert's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).
Agfa Gevaert Pink Sheet Forecast Pattern
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Agfa Gevaert Forecasted Value
In the context of forecasting Agfa Gevaert's Pink Sheet 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. Agfa Gevaert's downside and upside margins for the forecasting period are 0.43 and 3.92, respectively. We have considered Agfa Gevaert'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 Naive Prediction forecasting method's relative quality and the estimations of the prediction error of Agfa Gevaert pink sheet data series using in forecasting. Note that when a statistical model is used to represent Agfa Gevaert pink sheet, 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 | 112.4691 |
| Bias | Arithmetic mean of the errors | None |
| MAD | Mean absolute deviation | 0.043 |
| MAPE | Mean absolute percentage error | 0.0174 |
| SAE | Sum of the absolute errors | 2.6231 |
Predictive Modules for Agfa Gevaert
There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Agfa Gevaert NV. Regardless of method or technology, however, to accurately forecast the pink sheet market is more a matter of luck rather than a particular technique. Nevertheless, trying to predict the pink sheet 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.Sophisticated investors, who have witnessed many market ups and downs, anticipate that the market will even out over time. This tendency of Agfa Gevaert's price to converge to an average value over time is called mean reversion. However, historically, high market prices usually discourage investors that believe in mean reversion to invest, while low prices are viewed as an opportunity to buy.
Other Forecasting Options for Agfa Gevaert
For every potential investor in Agfa, whether a beginner or expert, Agfa Gevaert's price movement is the inherent factor that sparks whether it is viable to invest in it or hold it better. Agfa Pink Sheet price charts are filled with many 'noises.' These noises can hugely alter the decision one can make regarding investing in Agfa. Basic forecasting techniques help filter out the noise by identifying Agfa Gevaert's price trends.Agfa Gevaert 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 Agfa Gevaert pink sheet to make a market-neutral strategy. Peer analysis of Agfa Gevaert could also be used in its relative valuation, which is a method of valuing Agfa Gevaert by comparing valuation metrics with similar companies.
| Risk & Return | Correlation |
Agfa Gevaert NV Technical and Predictive Analytics
The pink sheet market is financially volatile. Despite the volatility, there exist limitless possibilities of gaining profits and building passive income portfolios. With the complexity of Agfa Gevaert'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 Agfa Gevaert's current price.| Cycle Indicators | ||
| Math Operators | ||
| Math Transform | ||
| Momentum Indicators | ||
| Overlap Studies | ||
| Pattern Recognition | ||
| Price Transform | ||
| Statistic Functions | ||
| Volatility Indicators | ||
| Volume Indicators |
Agfa Gevaert Market Strength Events
Market strength indicators help investors to evaluate how Agfa Gevaert pink sheet reacts to ongoing and evolving market conditions. The investors can use it to make informed decisions about market timing, and determine when trading Agfa Gevaert shares will generate the highest return on investment. By undertsting and applying Agfa Gevaert pink sheet market strength indicators, traders can identify Agfa Gevaert NV entry and exit signals to maximize returns.
Agfa Gevaert Risk Indicators
The analysis of Agfa Gevaert'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 Agfa Gevaert's investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting agfa pink sheet 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 | 0.4854 | |||
| Standard Deviation | 1.7 | |||
| Variance | 2.9 |
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 Agfa Pink Sheet Analysis
When running Agfa Gevaert's price analysis, check to measure Agfa Gevaert'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 Agfa Gevaert is operating at the current time. Most of Agfa Gevaert's value examination focuses on studying past and present price action to predict the probability of Agfa Gevaert's future price movements. You can analyze the entity against its peers and the financial market as a whole to determine factors that move Agfa Gevaert's price. Additionally, you may evaluate how the addition of Agfa Gevaert to your portfolios can decrease your overall portfolio volatility.