Forecast error is an important concept in the field of economics and financial analysis It is defined as the difference between a predicted or estimated value for a given variable and the actual observed value. This discrepancy occurs because the variables being observed often change in an unexpected manner and thus the forecasted value is inaccurate. Forecast errors can be calculated in both absolute and relative terms. In absolute terms, the forecast error measures the absolute deviation of the forecasted value from its actual value. In relative terms, the forecast error is expressed as a percentage of the actual value.
An example of an absolute forecast error is when a company predicts that a product will sell 10,000 units but only 5,000 units are actually sold. In this case, the absolute forecast error would be 5,000 units. In relative terms, the forecast error would be equal to 50%, since the forecast value was 50% higher than the actual value.
Another example of forecast error is when a company forecasts next month’s sales to be $1,000,000 but the actual sales are only $950,000. In this case, the absolute forecast error is $50,000 and the relative forecast error is 5%.
The following are the five best examples of forecast errors.
1. Inflation forecast error: this is an absolute forecast error that measures the difference between the predicted rate of inflation and the actual rate of inflation. For example, if a company predicts that inflation will be 10% but the actual rate of inflation is 12%, then the forecast error is 2%.
2. Interest rate forecast error: this is a relative forecast error that measures the difference between a predicted interest rate and the actual rate. For instance, if a company predicts that interest rates will be 8%, but the actual rate is 10%, then the forecast error is -2%.
3. Exchange rate forecast error: this is an absolute forecast error that measures the difference between a predicted exchange rate and the actual rate. For example, if a company predicts that the exchange rate between Dollar and Euro will be 1.20, but the actual rate is 1.30, then the forecast error is 0.10.
4. Stock price forecast error: this is an absolute forecast error that measures the difference between a predicted stock price and the actual price. For example, if a company predicts that a certain stock will be worth $50 but the actual price is $40, then the forecast error is $10.
5. GDP forecast error: this is an absolute forecast error that measures the difference between a predicted GDP growth rate and the actual growth rate. For example, if the predicted GDP growth rate is 5%, but the actual growth rate is only 3%, then the forecast error is -2%.