ALLIANZ SE Stock Forecast - Simple Regression

ALVE Stock  EUR 28.60  0.20  0.70%   
The Simple Regression forecasted value of ALLIANZ SE UNSPADR on the next trading day is expected to be 28.85 with a mean absolute deviation of 0.49 and the sum of the absolute errors of 29.74. ALLIANZ Stock Forecast is based on your current time horizon. We recommend always using this module together with an analysis of ALLIANZ SE'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 ALLIANZ SE 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.

ALLIANZ SE Simple Regression Price Forecast For the 24th of November

Given 90 days horizon, the Simple Regression forecasted value of ALLIANZ SE UNSPADR on the next trading day is expected to be 28.85 with a mean absolute deviation of 0.49, mean absolute percentage error of 0.39, and the sum of the absolute errors of 29.74.
Please note that although there have been many attempts to predict ALLIANZ 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 ALLIANZ SE's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).

ALLIANZ SE Stock Forecast Pattern

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ALLIANZ SE Forecasted Value

In the context of forecasting ALLIANZ SE'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. ALLIANZ SE's downside and upside margins for the forecasting period are 27.36 and 30.34, respectively. We have considered ALLIANZ SE'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
28.60
28.85
Expected Value
30.34
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 ALLIANZ SE stock data series using in forecasting. Note that when a statistical model is used to represent ALLIANZ SE 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 Criteria117.1584
BiasArithmetic mean of the errors None
MADMean absolute deviation0.4876
MAPEMean absolute percentage error0.017
SAESum of the absolute errors29.7417
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 ALLIANZ SE UNSPADR 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 ALLIANZ SE

There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as ALLIANZ SE UNSPADR. 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.
Sophisticated investors, who have witnessed many market ups and downs, anticipate that the market will even out over time. This tendency of ALLIANZ SE'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.
Hype
Prediction
LowEstimatedHigh
27.1128.6030.09
Details
Intrinsic
Valuation
LowRealHigh
25.2926.7831.46
Details
Bollinger
Band Projection (param)
LowMiddleHigh
28.3428.5328.72
Details

Other Forecasting Options for ALLIANZ SE

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

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

ALLIANZ SE UNSPADR 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 ALLIANZ SE'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 ALLIANZ SE's current price.

ALLIANZ SE Market Strength Events

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

ALLIANZ SE Risk Indicators

The analysis of ALLIANZ SE'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 ALLIANZ SE's investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting allianz 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 ALLIANZ Stock

ALLIANZ SE financial ratios help investors to determine whether ALLIANZ 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 ALLIANZ with respect to the benefits of owning ALLIANZ SE security.