Zalando SE OTC Stock Forecast - 4 Period Moving Average

ZLDSF Stock  USD 36.68  4.08  12.52%   
The 4 Period Moving Average forecasted value of Zalando SE on the next trading day is expected to be 35.66 with a mean absolute deviation of 0.69 and the sum of the absolute errors of 39.91. Zalando OTC Stock Forecast is based on your current time horizon. We recommend always using this module together with an analysis of Zalando SE's historical fundamentals, such as revenue growth or operating cash flow patterns.
  
A four-period moving average forecast model for Zalando SE is based on an artificially constructed daily price series in which the value for a given day is replaced by the mean of that value and the values for four preceding and succeeding time periods. This model is best suited to forecast equities with high volatility.

Zalando SE 4 Period Moving Average Price Forecast For the 12th of December 2024

Given 90 days horizon, the 4 Period Moving Average forecasted value of Zalando SE on the next trading day is expected to be 35.66 with a mean absolute deviation of 0.69, mean absolute percentage error of 1.98, and the sum of the absolute errors of 39.91.
Please note that although there have been many attempts to predict Zalando OTC 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 Zalando SE's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).

Zalando SE OTC Stock Forecast Pattern

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Zalando SE Forecasted Value

In the context of forecasting Zalando SE's OTC 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. Zalando SE's downside and upside margins for the forecasting period are 31.44 and 39.88, respectively. We have considered Zalando 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
36.68
35.66
Expected Value
39.88
Upside

Model Predictive Factors

The below table displays some essential indicators generated by the model showing the 4 Period Moving Average forecasting method's relative quality and the estimations of the prediction error of Zalando SE otc stock data series using in forecasting. Note that when a statistical model is used to represent Zalando SE otc 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 Criteria113.2819
BiasArithmetic mean of the errors -0.3155
MADMean absolute deviation0.6881
MAPEMean absolute percentage error0.0216
SAESum of the absolute errors39.91
The four period moving average method has an advantage over other forecasting models in that it does smooth out peaks and troughs in a set of daily price observations of Zalando SE. However, it also has several disadvantages. In particular this model does not produce an actual prediction equation for Zalando SE and therefore, it cannot be a useful forecasting tool for medium or long range price predictions

Predictive Modules for Zalando 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 Zalando SE. Regardless of method or technology, however, to accurately forecast the otc stock market is more a matter of luck rather than a particular technique. Nevertheless, trying to predict the otc 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 Zalando 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
31.5435.7639.98
Details
Intrinsic
Valuation
LowRealHigh
35.0939.3143.53
Details
Bollinger
Band Projection (param)
LowMiddleHigh
25.3530.8936.43
Details

Other Forecasting Options for Zalando SE

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

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

Zalando SE Technical and Predictive Analytics

The otc stock market is financially volatile. Despite the volatility, there exist limitless possibilities of gaining profits and building passive income portfolios. With the complexity of Zalando 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 Zalando SE's current price.

Zalando SE Market Strength Events

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

Zalando SE Risk Indicators

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

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