Investors can use this prediction interface to forecast Twitter historic prices and determine the direction of Twitter future trends based on various well-known forecasting models. However looking at historical price movement exclusively is usually misleading. Macroaxis recommends to always use this module together with analysis of Twitter historical fundamentals such as revenue growth or operating cash flow patterns. Although naive historical forecasting may sometimes provide an important future outlook for the firm we recommend to always cross-verify it against solid analysis of Twitter systematic risks associated with finding meaningful patterns of Twitter fundamentals over time. Also please take a look at Historical Fundamental Analysis of Twitter to cross-verify your projections.
Triple exponential smoothing for Twitter - 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 Twitter 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 Twitter price movement. However, neither of these exponential smoothing models address any seasonality of Twitter.
As with simple exponential smoothing, in triple exponential smoothing models past Twitter 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 Twitter observations.