Techniques For Forecasting Future Market Trends

Techniques For Forecasting Future Market Trends

Adopting a forecasting techniques, ranges from the subjective forecasting which allows forecasters to predict outcomes based on their subjective thoughts and feelings. Subjective forecasting uses brainstorming sessions to generate ideas and to solve problems casually, free from criticism and peer pressure. They are often used when time constraints prohibit objective forecasts. Subjective forecasts are subject to biases and should be viewed skeptically by decision-makers.

Other sophisticated techniques of forecastings is Time-Series. Time-series forecasting is a quantitative forecastings technique. It measures data gathered over time to identify trends. The data may be taken over any interval: hourly; daily; weekly; monthly; yearly; or longer. Trend, cyclical, seasonal and irregular components make up the time series. The trend component refers to the data’s gradual shifting over time. It is often shown as an upward- or downward-sloping line to represent increasing or decreasing trends, respectively. Cyclical components lie above or below the trend line and repeat for a year or longer. The business cycle illustrates a cyclical component. Seasonal components are similar to cyclicals in their repetitive nature, but they occur in one-year periods. The annual increase in gas prices during the summer driving season and the corresponding decrease during the winter months is an example of a seasonal event. Irregular components happen randomly and cannot be predicted.

Basically, there are three (3) methods of forecasting techniques which includes:

1. Qualitative method
2. Quantitative method
3. Judgemental methods

1. Qualitative forecastings techniques are subjective, based on the opinion and judgment of consumers, experts; they are appropriate when past data are not available. They are usually applied to intermediate- or long-range decisions. Examples of qualitative forecasting methods are informed opinion and judgment, the Delphi method, market research, and historical life-cycle analogy.
2. Quantitative forecastings models are used to forecast future data as a function of past data. They are appropriate to use when past numerical data is available and when it is reasonable to assume that some of the patterns in the data are expected to continue into the future. These methods are usually applied to short- or intermediate-range decisions. Examples of quantitative forecasting methods are last period demand, simple and weighted N-Period moving averages, simple exponential smoothing, and multiplicative seasonal indexes.
3. Judgmental forecasting methods incorporate intuitive judgement, opinions and subjective probability estimates. Judgmental forecastings is used in cases where there is lack of historical data or during completely new and unique market conditions