Smoothing 2: Moving Average for forecasting

Using a moving average to forecasting a time series
This video supports the textbook Practical Time Series Forecasting.
www.forecastingbook.com
www.galitshmueli.com

[@marlinaismail804]

I really love your explanation. God bless u mam

[@professorviniciusmontgomery]

Thank you very much for the excellent moving average method class. It was very useful for me. I´d appreciate more videos on Forecasts and, if possible, in DOE too.

[@fernandaluciagalvezaranda8850]

Thank you 😩

[@newtonding]

By what metrics do you make the judgement on whether the model capture the trend and seasonality? Based on the visualization of the model itself and forecast error? looking at the two examples in the video, I can understand that seasonality is not captured by looking at the chart of the forecast error since the forecast error clearly shows the seasonality. However, I cannot know how to judge whether the trend is properly captured or not.

[@HardikSondagar]

In validation part (gray one) of visualization, forecast value is constant means information of seasonality and trend is missing as moving average forecasts only single value for whole validation period. It doesn't indicate the same in MAPE, MAD or MSE

[@akrsrivastava]

Wouldnt it be better to do a one step forward forecast?