S A P Stock Forecast - Simple Regression

SAP Stock  EUR 166.58  0.06  0.04%   
The Simple Regression forecasted value of SAP SE on the next trading day is expected to be 173.06 with a mean absolute deviation of  3.79  and the sum of the absolute errors of 230.96. SAP Stock Forecast is based on your current time horizon. Investors can use this forecasting interface to forecast S A P stock prices and determine the direction of SAP SE's future trends based on various well-known forecasting models. We recommend always using this module together with an analysis of S A P's historical fundamentals, such as revenue growth or operating cash flow patterns.
Check out Historical Fundamental Analysis of S A P to cross-verify your projections.
  
Most investors in S A P cannot accurately predict what will happen the next trading day because, historically, stock markets tend to be unpredictable and even illogical. Modeling turbulent structures requires applying different statistical methods, techniques, and algorithms to find hidden data structures or patterns within the S A P's time series price data and predict how it will affect future prices. One of these methodologies is forecasting, which interprets S A P's price structures and extracts relationships that further increase the generated results' accuracy.
Simple Regression model is a single variable regression model that attempts to put a straight line through S A P 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.

S A P Simple Regression Price Forecast For the 3rd of June

Given 90 days horizon, the Simple Regression forecasted value of SAP SE on the next trading day is expected to be 173.06 with a mean absolute deviation of 3.79, mean absolute percentage error of 20.15, and the sum of the absolute errors of 230.96.
Please note that although there have been many attempts to predict SAP 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 S A P's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).

S A P Stock Forecast Pattern

Backtest S A PS A P Price PredictionBuy or Sell Advice 

S A P Forecasted Value

In the context of forecasting S A P'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. S A P's downside and upside margins for the forecasting period are 171.62 and 174.50, respectively. We have considered S A P'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
166.58
171.62
Downside
173.06
Expected Value
174.50
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 S A P stock data series using in forecasting. Note that when a statistical model is used to represent S A P 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 Criteria121.1135
BiasArithmetic mean of the errors None
MADMean absolute deviation3.7863
MAPEMean absolute percentage error0.022
SAESum of the absolute errors230.9628
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 SAP SE 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 S A P

There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as SAP SE. 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 S A P'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
165.14166.58168.02
Details
Intrinsic
Valuation
LowRealHigh
149.92168.91170.35
Details
Bollinger
Band Projection (param)
LowMiddleHigh
164.83173.53182.23
Details
Please note, it is not enough to conduct a financial or market analysis of a single entity such as S A P. Your research has to be compared to or analyzed against S A P's peers to derive any actionable benefits. When done correctly, S A P's competitive analysis will give you plenty of quantitative and qualitative data to validate your investment decisions or develop an entirely new strategy toward taking a position in SAP SE.

Other Forecasting Options for S A P

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

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

SAP SE 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 S A P'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 S A P's current price.

S A P Market Strength Events

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

S A P Risk Indicators

The analysis of S A P'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 S A P's investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting sap 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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Check out Historical Fundamental Analysis of S A P to cross-verify your projections.
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When running S A P's price analysis, check to measure S A P'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 S A P is operating at the current time. Most of S A P's value examination focuses on studying past and present price action to predict the probability of S A P's future price movements. You can analyze the entity against its peers and the financial market as a whole to determine factors that move S A P's price. Additionally, you may evaluate how the addition of S A P to your portfolios can decrease your overall portfolio volatility.
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Please note, there is a significant difference between S A P's value and its price as these two are different measures arrived at by different means. Investors typically determine if S A P is a good investment by looking at such factors as earnings, sales, fundamental and technical indicators, competition as well as analyst projections. However, S A P's price is the amount at which it trades on the open market and represents the number that a seller and buyer find agreeable to each party.