Types of forecasts
Forecasts are used to predict future events and are used in business, finance, and economics. Forecasts can be qualitative or quantitative.
Quantitative forecasts are based on mathematical relationships and use historical data to generate future projections. Examples of quantitative forecasts include linear regression, time series analysis, and exponential smoothing.
- Linear regression: This type of forecasting uses a linear equation to describe the relationship between two or more variables. The equation is used to generate a prediction of the value of one variable based on the value of another variable.
- Time series analysis: This methodology uses historical data to identify patterns and trends in the data which can then be used to generate a forecast of future values.
- Exponential smoothing: This forecasting technique uses weighted averages of past data to generate a forecast of future values.
Qualitative forecasts are based on subjective judgments and opinions. Examples of qualitative forecasts include Delphi technique, scenario planning, and analogies.
- Delphi technique: This technique involves a panel of experts who provide their estimates and judgement of future events.
- Scenario planning: This forecasting technique involves creating different ‘what if’ scenarios to explore the potential outcomes of different decisions.
- Analogies: This method uses similarities between past events and the current situation to generate a forecast.
Examples of types of forecasts
Forecasts are used to predict future events and are used in business, finance, and economics. Forecasts can be qualitative or quantitative.
Quantitative forecasts are based on mathematical relationships and use historical data to generate future projections. Examples of quantitative forecasts include linear regression, time series analysis, and exponential smoothing.
- Linear regression: This type of forecasting uses a linear equation to describe the relationship between two or more variables. The equation is used to generate a prediction of the value of one variable based on the value of another variable.
- Time series analysis: This methodology uses historical data to identify patterns and trends in the data which can then be used to generate a forecast of future values.
- Exponential smoothing: This forecasting technique uses weighted averages of past data to generate a forecast of future values.
Qualitative forecasts are based on subjective judgments and opinions. Examples of qualitative forecasts include Delphi technique, scenario planning, and analogies.
- Delphi technique: This technique involves a panel of experts who provide their estimates and judgement of future events.
- Scenario planning: This forecasting technique involves creating different ‘what if’ scenarios to explore the potential outcomes of different decisions.
- Analogies: This method uses similarities between past events and the current situation to generate a forecast.
When to use Types of forecasts
Forecasts are used to predict future events and are often used in business, finance, and economics. Depending on the situation and the type of information needed, different forecast types may be used.
- Linear regression: Linear regression is well suited for making predictions about the future values of a single variable based on the current value of another variable.
- Time series analysis: Time series analysis is useful for making predictions about future values of a single variable based on past values of that variable.
- Exponential smoothing: Exponential smoothing is useful for making predictions about future values of a single variable based on past values of that variable, but is more effective when the data is subject to random fluctuations.
- Delphi technique: The Delphi technique is useful for making predictions about future events where the opinions of multiple experts are needed.
- Scenario planning: Scenario planning is useful for making predictions about future events where there is uncertainty about the potential outcomes of different decisions.
- Analogies: Analogies can be used to make predictions about future events based on similarities with past events.
Methods of creating forecasts
Forecasts are used to predict future events and are used in business, finance, and economics. Forecasts can be classified into two main types: qualitative and quantitative.
Qualitative forecasts are based on subjective judgments and opinions. Examples of qualitative forecasts include Delphi technique, scenario planning, and analogies.
- Delphi technique: This technique involves a panel of experts who provide their estimates and judgement of future events.
- Scenario planning: This forecasting technique involves creating different ‘what if’ scenarios to explore the potential outcomes of different decisions.
- Analogies: This method uses similarities between past events and the current situation to generate a forecast.
Quantitative forecasts are based on mathematical relationships and use historical data to generate future projections. Examples of quantitative forecasts include linear regression, time series analysis, and exponential smoothing.
- Linear regression: This type of forecasting uses a linear equation to describe the relationship between two or more variables. The equation is used to generate a prediction of the value of one variable based on the value of another variable.
- Time series analysis: This methodology uses historical data to identify patterns and trends in the data which can then be used to generate a forecast of future values.
- Exponential smoothing: This forecasting technique uses weighted averages of past data to generate a forecast of future values.
Advantages of forecasts
Forecasts can be used to predict future events and can be either quantitative or qualitative. Quantitative forecasts are based on mathematical relationships and use historical data to generate future projections, while qualitative forecasts are based on subjective judgments and opinions.
The advantages of quantitative forecasts are that they are relatively reliable and can be used to generate accurate predictions. Additionally, they can be used to identify relationships between different variables.
The advantages of qualitative forecasts are that they can be used to generate insights which would not be possible using quantitative methods. Additionally, they are more adaptable to changing conditions and can incorporate expert opinion.
Limitations of forecasts
Quantitative forecasts have the limitation of being unable to accurately predict events that may not have happened in the past. Qualitative forecasts are also limited by the subjective judgement of the experts involved in the process and can be influenced by bias. Additionally, both quantitative and qualitative forecasts can be affected by unexpected external events or changes in the market.
Forecasting can also be classified as either deterministic or probabilistic.
- Deterministic forecasting: This approach assumes that the future will be the same as the present, and uses historical data to generate a forecast.
- Probabilistic forecasting: This approach assumes that the future is uncertain, and uses probabilities to generate a forecast. This type of forecasting is useful for making decisions in uncertain environments.
| Types of forecasts — recommended articles |
| Scenario analysis — Strategic scenarios method — Linear regression analysis — Logistic regression model — Risk estimation — Stochastic volatility — Hierarchical regression analysis — Probability theory — Statistical methods |
References
- Murphy, A. H. (1977). The value of climatological, categorical and probabilistic forecasts in the cost-loss ratio situation. Monthly Weather Review, 105(7), 803-816.
- Vannitsem, S., Bremnes, J. B., Demaeyer, J., Evans, G. R., Flowerdew, J., Hemri, S., ... & Ylhaisi, J. (2021). Statistical postprocessing for weather forecasts: Review, challenges, and avenues in a big data world. Bulletin of the American Meteorological Society, 102(3), E681-E699.
