Bayer AG Stock Forecast - Simple Regression

BAYN Stock  EUR 19.79  0.19  0.97%   
The Simple Regression forecasted value of Bayer AG NA on the next trading day is expected to be 21.51 with a mean absolute deviation of 1.51 and the sum of the absolute errors of 91.89. Bayer Stock Forecast is based on your current time horizon. We recommend always using this module together with an analysis of Bayer AG's historical fundamentals, such as revenue growth or operating cash flow patterns.
  
Simple Regression model is a single variable regression model that attempts to put a straight line through Bayer AG 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.

Bayer AG Simple Regression Price Forecast For the 28th of November

Given 90 days horizon, the Simple Regression forecasted value of Bayer AG NA on the next trading day is expected to be 21.51 with a mean absolute deviation of 1.51, mean absolute percentage error of 3.02, and the sum of the absolute errors of 91.89.
Please note that although there have been many attempts to predict Bayer 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 Bayer AG's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).

Bayer AG Stock Forecast Pattern

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Bayer AG Forecasted Value

In the context of forecasting Bayer AG'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. Bayer AG's downside and upside margins for the forecasting period are 18.94 and 24.07, respectively. We have considered Bayer AG'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
19.79
21.51
Expected Value
24.07
Upside

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 Bayer AG stock data series using in forecasting. Note that when a statistical model is used to represent Bayer AG 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 Criteria119.2153
BiasArithmetic mean of the errors None
MADMean absolute deviation1.5063
MAPEMean absolute percentage error0.0592
SAESum of the absolute errors91.8863
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 Bayer AG NA 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 Bayer AG

There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Bayer AG NA. 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
17.2219.7922.36
Details
Intrinsic
Valuation
LowRealHigh
16.2518.8221.39
Details
Bollinger
Band Projection (param)
LowMiddleHigh
18.0122.9927.97
Details

Other Forecasting Options for Bayer AG

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

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

Bayer AG NA 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 Bayer AG'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 Bayer AG's current price.

Bayer AG Market Strength Events

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

Bayer AG Risk Indicators

The analysis of Bayer AG'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 Bayer AG's investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting bayer 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.

Currently Active Assets on Macroaxis

Other Information on Investing in Bayer Stock

Bayer AG financial ratios help investors to determine whether Bayer 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 Bayer with respect to the benefits of owning Bayer AG security.