Trend projection method is a classical method of business forecasting. This method is essentially concerned with the study of movement of variable through time. The use of this method requires a long and reliable time series data. The trend projection method is used under the assumption that the factors responsible for the past trends in variables to be projected (e.g. sales and demand) will continue to play their part in future in the same manner and to the same extend as they did in the past in determining the magnitude and direction of the variable.
There are three (3) techniques of trend projection based on time – series data.

Graphical Method: – under this method, annual sales data is plotted on a graph paper and a line is drawn through the plotted points. Then a free hand line is so drawn that the total distance between the line and the point is minimum.
Sale
Years
Trend Projection
Although this method is very simple and least expensive, the projections made through this method are not very reliable. The reason is that the extension of the trend line involves subjectivity and personal bias of the analysis.

Fitting Trend Equation: Least square method: – Fitting trend equation is a formal technique of projecting the trend in demand. Under this method, a trend line (or curve) is fitted to the time – series data with the aid of statistical techniques. The form of the trend equation that can be fitted to the time series data is determined either by plotting the sales data or by trying different forms of trend equations for the best fit.
When plotted, a time series date may show various trends. The most common types of trend equation are 1) liner and 2) exponential trends
Linear Trend: – When a time series data reveals a rising trend in sales than a straightline trend equation of the following form is fitted
S = A + BT
Where S = annual sales
T = Time (in year)
A & B are constant. The parameter b given the measure of annual increase in sales
Exponential trend: When sales ( or any dependent variable) have increased over the past years at an increasing rate or at a constant percentage rate, than the appropriate trend equation to be used is an exponential trend equation of any of the following type

Y = aebt
Or its semi – logarithmic for
Log y = = log a + bt
This form of trend equation is used when growth rate is constant.

Double log trend equation of equation
Y = aTB
Or it’s double logarithmic form
Log y = log a + b log t
This form of trend equation is used when growth rate is increasing.
Limitation
The first limitations of this method arise out of the assumption that the past rate of change in the dependent variable will persist in the future too. Therefore, the forecast based on this method may be considered to be reliable only for the period during which this assumption holds.
Second, this method cannot be used for shortterm estimates. Also it cannot be used where trend is cyclical with sharp turning points of trough and perks.

Box – Jenkins Method: – This method of forecasting is used only for short – term predictions. Besides, this method is suitable for forecasting demand with only stationary time series sales data. Stationary time series data is one, which does not reveal long term trend. In other words, BoxJenkins technique can be used only on those cases in which timeseries analysis depicts monthly or seasonal variation recurring with some degree of regularity.
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