Forecasting with Holt's Linear Trend Exponential Smoothing

In my previous post, we introduced the idea of exponential smoothing for building forecasting models. The gist of exponential smoothing is to put more weight on recent observations and less weight, exponentially, on more historical ones. The first model we introduced was simple exponential smoothing. The'simple' part refers to the model not taking into account trend or seasonality, and only forecasting the level. This leads to this particular model to often deliver inadequate forecasts for most time series. Therefore, we need to further iterate from this simple approach.