Carnegie Clean Stock Forecast - Double Exponential Smoothing

Double exponential smoothing - also known as Holt exponential smoothing is a refinement of the popular simple exponential smoothing model with an additional trending component. Double exponential smoothing model for Carnegie Clean works best with periods where there are trends or seasonality.

Carnegie Clean Double Exponential Smoothing Price Forecast For the 27th of November

Given 90 days horizon, the Double Exponential Smoothing forecasted value of Carnegie Clean Energy on the next trading day is expected to be 0.04 with a mean absolute deviation of 0.0008, mean absolute percentage error of 0.00000089, and the sum of the absolute errors of 0.04.

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Model Predictive Factors

The below table displays some essential indicators generated by the model showing the Double Exponential Smoothing forecasting method's relative quality and the estimations of the prediction error of Carnegie Clean stock data series using in forecasting. Note that when a statistical model is used to represent Carnegie Clean 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. When Carnegie Clean Energy 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 Carnegie Clean Energy trend in the prices. So in double exponential smoothing past observations are given exponentially smaller weights as the observations get older. In other words, recent Carnegie Clean observations are given relatively more weight in forecasting than the older observations.

Predictive Modules for Carnegie Clean

There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Carnegie Clean Energy. 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 Low Estimated High 0.00 0.04 2.96 Details

Intrinsic Valuation Low Real High 0.00 0.03 2.95 Details

Other Forecasting Options for Carnegie Clean

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

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Carnegie Clean Energy 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 Carnegie Clean'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 Carnegie Clean's current price.

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