Sika AG Stock Forecast - Simple Regression

SIKA Stock   231.40  2.40  1.05%   
The Simple Regression forecasted value of Sika AG on the next trading day is expected to be 232.84 with a mean absolute deviation of 5.16 and the sum of the absolute errors of 314.73. Sika Stock Forecast is based on your current time horizon.
  
Simple Regression model is a single variable regression model that attempts to put a straight line through Sika 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.

Sika AG Simple Regression Price Forecast For the 24th of November

Given 90 days horizon, the Simple Regression forecasted value of Sika AG on the next trading day is expected to be 232.84 with a mean absolute deviation of 5.16, mean absolute percentage error of 48.93, and the sum of the absolute errors of 314.73.
Please note that although there have been many attempts to predict Sika 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 Sika AG's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).

Sika AG Stock Forecast Pattern

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Sika AG Forecasted Value

In the context of forecasting Sika 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. Sika AG's downside and upside margins for the forecasting period are 231.57 and 234.11, respectively. We have considered Sika 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
231.40
231.57
Downside
232.84
Expected Value
234.11
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 Sika AG stock data series using in forecasting. Note that when a statistical model is used to represent Sika 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 Criteria122.0009
BiasArithmetic mean of the errors None
MADMean absolute deviation5.1596
MAPEMean absolute percentage error0.0197
SAESum of the absolute errors314.735
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 Sika AG 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 Sika 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 Sika AG. 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
230.12231.40232.68
Details
Intrinsic
Valuation
LowRealHigh
208.26243.35244.63
Details
Bollinger
Band Projection (param)
LowMiddleHigh
226.77246.49266.20
Details

Other Forecasting Options for Sika AG

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

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

Sika AG 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 Sika 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 Sika AG's current price.

Sika AG Market Strength Events

Market strength indicators help investors to evaluate how Sika 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 Sika AG shares will generate the highest return on investment. By undertsting and applying Sika AG stock market strength indicators, traders can identify Sika AG entry and exit signals to maximize returns.

Sika AG Risk Indicators

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

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 Sika Stock Analysis

When running Sika AG's price analysis, check to measure Sika AG'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 Sika AG is operating at the current time. Most of Sika AG's value examination focuses on studying past and present price action to predict the probability of Sika AG's future price movements. You can analyze the entity against its peers and the financial market as a whole to determine factors that move Sika AG's price. Additionally, you may evaluate how the addition of Sika AG to your portfolios can decrease your overall portfolio volatility.