Forecasting

What Is Forecasting?

Forecasting is a technique that uses historical data as inputs to make informed estimates that are predictive in determining the direction of future trends. Businesses utilize forecasting to determine how to allocate their budgets or plan for anticipated expenses for an upcoming period of time. This is typically based on the projected demand for the goods and services offered.

How Forecasting Works

Investors utilize forecasting to determine if events affecting a company, such as sales expectations, will increase or decrease the price of shares in that company. Forecasting also provides an important benchmark for firms, which need a long-term perspective of operations.

Stock analysts use forecasting to extrapolate how trends, such as GDP or unemployment, will change in the coming quarter or year. The further out the forecast, the higher the chance that the estimate will be inaccurate. Finally, statisticians can utilize forecasting to analyze the potential impact of a change in business operations.. For instance, data may be collected regarding the impact of customer satisfaction by changing business hours or the productivity of employees upon changing certain work conditions.

Forecasting addresses a problem or set of data. Economists make assumptions regarding the situation being analyzed that must be established before the variables of the forecasting are determined. Based on the items determined, an appropriate data set is selected and used in the manipulation of information. The data is analyzed, and the forecast is determined. Finally, a verification period occurs where the forecast is compared to the actual results to establish a more accurate model for forecasting in the future.

Forecasting Methods

Stock analysts use various forecasting methods to determine how a stock's price will move in the future. They might look at revenue and compare it to economic indicators. Changes to financial or statistical data are observed to determine the relationship between multiple variables. These relationships may be based on the passage of time or the occurrence of specific events. For example, a sales forecast may be based upon a specific period (the passage of the next 12 months) or the occurrence of an event (the purchase of a competitor’s business).

Qualitative forecasting models are useful in developing forecasts with a limited scope. These models are highly reliant on expert opinions and are most beneficial in the short term. Examples of qualitative forecasting models include market research, polls, and surveys that apply the Delphi method. Quantitative methods of forecasting exclude expert opinions and utilize statistical data based on quantitative information. Quantitative forecasting models include time series methods, discounting, analysis of leading or lagging indicators, and econometric modeling.