Complex Time-Series Forecasting

Part of the lecture series "Free Cash Flow Estimation and Forecasting":
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Notes
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- Forecasts are simple when the data are just trending upwards or downwards without any repeating pattern
- Once there are repeating patterns in the data, more advanced models are needed
- Seasonality is a classic cause of these repeating patterns. A cruise line is going to have much higher sales in the summer than in the winter, and this pattern is going to repeat every year
- In general, these advanced models are outside of the scope of the course. Here we just cover the quarterly seasonal trend model which is specifically designed to deal with this seasonality in quarterly data, which should be sufficient for DCF financial statement forecasting
- Dummy variables are just those which take on a value of 1 for true and 0 for false
- If you need to forecast higher frequency data for other purposes, the quarterly seasonal trend model will not be a good fit. Other frequency seasonality models can be fit, but it would usually be better to go to the full model selection process
- Thankfully, we have software solutions to fit advanced models for us such as prophet, which is integrated into finstmt

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