Poor forecasting can
be the reason of terrible consequences. Relatively accurate forecasting, more or less, drives toward financial success. Here are some examples of poor
forecasting that one may encounter.
- Working on a sample that is too small or does not represent the population properly.
- Uses of historical data that is too old.
- Not making a precise use of probabilities when making choices.
- Underestimation or overestimation of the time because forecast methods can drastically vary depending on the timescale.
- Other common estimating error and forecasting biases such as projection bias, impact bias, and overconfidence effect etc.