Deutsche Post Pink Sheet Forecast - Polynomial Regression

Deutsche Post polinomial regression implements a single variable polynomial regression model using the daily prices as the independent variable. The coefficients of the regression for Deutsche Post AG as well as the accuracy indicators are determined from the period prices.

Deutsche Post Polynomial Regression Price Forecast For the 27th of November

Given 90 days horizon, the Polynomial Regression forecasted value of Deutsche Post AG on the next trading day is expected to be 52.59 with a mean absolute deviation of 0.58, mean absolute percentage error of 0.54, and the sum of the absolute errors of 35.58.

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Model Predictive Factors

The below table displays some essential indicators generated by the model showing the Polynomial Regression forecasting method's relative quality and the estimations of the prediction error of Deutsche Post pink sheet data series using in forecasting. Note that when a statistical model is used to represent Deutsche Post 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. A single variable polynomial regression model attempts to put a curve through the Deutsche Post historical price points. Mathematically, assuming the independent variable is X and the dependent variable is Y, this line can be indicated as: Y = a₀ + a₁*X + a₂*X² + a₃*X³ + ... + a_m*X^m

Predictive Modules for Deutsche Post

There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Deutsche Post AG. 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 Low Estimated High 51.63 51.63 51.63 Details

Intrinsic Valuation Low Real High 42.34 42.34 56.79 Details

Please note, it is not enough to conduct a financial or market analysis of a single entity such as Deutsche Post. Your research has to be compared to or analyzed against Deutsche Post's peers to derive any actionable benefits. When done correctly, Deutsche Post'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 Deutsche Post AG.

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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.

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