UCB - Stock Forecast - Triple Exponential Smoothing

UNC Stock  EUR 187.20  0.00  0.00%   
The Triple Exponential Smoothing forecasted value of UCB Dusseldorf on the next trading day is expected to be 195.25 with a mean absolute deviation of 2.66 and the sum of the absolute errors of 159.31. UCB Stock Forecast is based on your current time horizon.
  
Triple exponential smoothing for UCB - - also known as the Winters method - is a refinement of the popular double exponential smoothing model with the addition of periodicity (seasonality) component. Simple exponential smoothing technique works best with data where there are no trend or seasonality components to the data. When UCB - prices exhibit either an increasing or decreasing trend over time, simple exponential smoothing forecasts tend to lag behind observations. Double exponential smoothing is designed to address this type of data series by taking into account any trend in UCB - price movement. However, neither of these exponential smoothing models address any seasonality of UCB Dusseldorf.

UCB - Triple Exponential Smoothing Price Forecast For the 8th of February

Given 90 days horizon, the Triple Exponential Smoothing forecasted value of UCB Dusseldorf on the next trading day is expected to be 195.25 with a mean absolute deviation of 2.66, mean absolute percentage error of 77.79, and the sum of the absolute errors of 159.31.
Please note that although there have been many attempts to predict UCB 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 UCB -'s next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).

UCB - Stock Forecast Pattern

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Model Predictive Factors

The below table displays some essential indicators generated by the model showing the Triple Exponential Smoothing forecasting method's relative quality and the estimations of the prediction error of UCB - stock data series using in forecasting. Note that when a statistical model is used to represent UCB - 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 CriteriaHuge
BiasArithmetic mean of the errors -1.2848
MADMean absolute deviation2.6552
MAPEMean absolute percentage error0.0207
SAESum of the absolute errors159.3124
As with simple exponential smoothing, in triple exponential smoothing models past UCB - observations are given exponentially smaller weights as the observations get older. In other words, recent observations are given relatively more weight in forecasting than the older UCB Dusseldorf observations.

Predictive Modules for UCB -

There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as UCB Dusseldorf. 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
187.20187.20187.20
Details
Intrinsic
Valuation
LowRealHigh
168.48168.48205.92
Details
Bollinger
Band Projection (param)
LowMiddleHigh
86.52113.54140.56
Details

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

UCB - Market Strength Events

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

Thematic Opportunities

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Additional Tools for UCB Stock Analysis

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