Methods for market volume forecasting

01 Nov 2007 • by Natalie Aster

There are four main methods to assess market volume.

1. Forecast on the basis of average growth rates. This method implies origination of mathematical function which describes market growth rates over a period of time. Then the forecast of the future growth rate is made and market volume is calculated taking into consideration last factual value of this volume. This is the most simple and the least accurate method. The forecast accuracy depends on the correctness of the selection of function and its parameters which describe market volume growth rates. Another factor that affects accuracy is stability on the market. This method is effective when approximate forecasts are required. It is also quite applicable for large time lengths and stable well-shaped markets.

2. Forecast on the basis of correlation between market volume and main macroeconomic parameters. Using this method, a researcher defines the dependence of growth rates from macroeconomic parameters and advertising market. Further, expected market volume is calculated on the basis of this dependence. Forecasts made by relevant economic ministries and departments are also taken into consideration. The main limitation of this method is that it permits to evaluate only general market volume.

3. Forecast on the basis of client intentions. Company’s sales managers poll prospective clients trying to find out which budgets, if any, these clients are going to allocate for the purchase of company’s services. The weaknesses of this method include high resource intensity, involvement of large personnel groups, probable unwillingness of clients to display their intentions. However, this method allows to forecast market structure according to commodity groups.

4. Forecast on the basis of expertly evaluations provided by main players on the market. Strength: expectations of key players are taken into consideration. Weakness: small players are neglected.

Specialists single out the following intervening methods of making forecasts.

1. Polling.
This method reveals opinions of population, experts, specialists, etc. with a view of getting evaluations of forecast character. As a rule, methods, based on polling, are used primarily when, due to some reasons, process regularities could not be reflected by ordinary means and when required data are missing. Expertly analysis based on knowledge and intuition of specialists is widely applicable in market forecasts, especially when market volume or new (modified) commodities are evaluated. One of the most common methods to get expertly evaluation is to use Delphi method. The Delphi method is a systematic interactive forecasting method for obtaining forecasts from a panel of independent experts. The carefully selected experts answer questionnaires in two or more rounds. After each round, a facilitator provides an anonymous summary of the experts’ forecasts from the previous round as well as the reasons they provided for their judgments. Thus, participants are encouraged to revise their earlier answers in light of the replies of other members of the group. It is believed that during this process the range of the answers will decrease and the group will converge towards the "correct" answer. Finally, the process is stopped after a pre-defined stop criterion (e.g. number of rounds, achievement of consensus, stability of results) and the mean or median scores of the final rounds determine the results. Delphi is based on well-researched principles and provides forecasts that are more accurate than those from unstructured groups. The technique can be adapted for use in face-to-face meetings, and is then called mini-Delphi or Estimate-Talk-Estimate (ETE). Delphi has been widely used for business forecasting and has certain advantages over another structured forecasting approach: prediction markets. Unlike the Delphi method, brainstorming is a group creativity technique designed to generate a large number of ideas for the solution to a problem. Although brainstorming has become a popular group technique, researchers have generally failed to find evidence of its effectiveness for enhancing either quantity or quality of ideas generated. Because of such problems as distraction, social loafing, evaluation apprehension, and production blocking, brainstorming groups are little more effective than other types of groups, and they are actually less effective than individuals working independently. For this reason, there have been numerous attempts to improve brainstorming or replace it with more effective variations of the basic technique. Although traditional brainstorming may not increase the productivity of groups, it has other potential benefits, such as enhancing the enjoyment of group work and improving morale. It may also serve as a useful exercise for team building. This method is also applicable in critical situations when there are no real and obvious variants of process development in the future.

2. Extrapolation.
Extrapolation implies the future prolongation of processes reflected in dynamics. When prediction is grounded in current knowledge, it is more precisely termed extrapolation. To extrapolate is "to project, extend, of expand (known data or experiences) into an area not known or experienced so as to arrive at ... knowledge of the unknown area by inferences based on an assumed continuity, correspondence, of other parallelism between it and what is known" (Gove and Merriam Webster 1986). This definition encompasses the process of "scaling up" or deriving inferences and rules that can be applied at broad scales on the basis of data collected at smaller scales. This method is widely applied when information on the past is in abundance and steady trends are revealed. This method is based on the assumption that former trends will survive in future. This method could be also viewed as genetic; it implies the use of econometric models. Most trade market researches stipulate that time factor (or trend) acts as a key factor which governs market development. Extrapolation procedure implies the choice of trend models of forecasting, as well as the building of a curve graph to depict empirical data in the most accurate way (please see the table below).