SAP SE Pink Sheet Forecast - Naive Prediction

SAPGF Stock  USD 251.00  1.96  0.79%   
The Naive Prediction forecasted value of SAP SE on the next trading day is expected to be 263.33 with a mean absolute deviation of 3.22 and the sum of the absolute errors of 199.77. SAP Pink Sheet Forecast is based on your current time horizon. We recommend always using this module together with an analysis of SAP SE's historical fundamentals, such as revenue growth or operating cash flow patterns.
  
A naive forecasting model for SAP SE is a special case of the moving average forecasting where the number of periods used for smoothing is one. Therefore, the forecast of SAP SE value for a given trading day is simply the observed value for the previous period. Due to the simplistic nature of the naive forecasting model, it can only be used to forecast up to one period.

SAP SE Naive Prediction Price Forecast For the 12th of December 2024

Given 90 days horizon, the Naive Prediction forecasted value of SAP SE on the next trading day is expected to be 263.33 with a mean absolute deviation of 3.22, mean absolute percentage error of 15.67, and the sum of the absolute errors of 199.77.
Please note that although there have been many attempts to predict SAP 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 SAP SE's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).

SAP SE Pink Sheet Forecast Pattern

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SAP SE Forecasted Value

In the context of forecasting SAP SE'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. SAP SE's downside and upside margins for the forecasting period are 261.73 and 264.94, respectively. We have considered SAP 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
251.00
261.73
Downside
263.33
Expected Value
264.94
Upside

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 SAP SE pink sheet data series using in forecasting. Note that when a statistical model is used to represent SAP SE 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.
AICAkaike Information Criteria122.7003
BiasArithmetic mean of the errors None
MADMean absolute deviation3.2221
MAPEMean absolute percentage error0.0138
SAESum of the absolute errors199.7723
This model is not at all useful as a medium-long range forecasting tool of SAP SE. This model is simplistic and is included partly for completeness and partly because of its simplicity. It is unlikely that you'll want to use this model directly to predict SAP SE. Instead, consider using either the moving average model or the more general weighted moving average model with a higher (i.e., greater than 1) number of periods, and possibly a different set of weights.

Predictive Modules for SAP 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 SAP SE. 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.
Hype
Prediction
LowEstimatedHigh
249.40251.00252.60
Details
Intrinsic
Valuation
LowRealHigh
225.90270.18271.78
Details
Bollinger
Band Projection (param)
LowMiddleHigh
221.63237.56253.49
Details
Please note, it is not enough to conduct a financial or market analysis of a single entity such as SAP SE. Your research has to be compared to or analyzed against SAP SE's peers to derive any actionable benefits. When done correctly, SAP SE'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 SAP SE

For every potential investor in SAP, whether a beginner or expert, SAP SE's price movement is the inherent factor that sparks whether it is viable to invest in it or hold it better. SAP Pink Sheet 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 SAP SE's price trends.

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

SAP SE 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 SAP 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 SAP SE's current price.

SAP SE Market Strength Events

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

SAP SE Risk Indicators

The analysis of SAP 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 SAP SE's investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting sap 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.
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 SAP Pink Sheet

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