Forecasting Approach Using Exponential Smoothing Moving Average And Weighted Moving Average Term Paper

Length: 2 pages Sources: 1 Subject: Weather Type: Term Paper Paper: #57953197 Related Topics: Meteorology
Excerpt from Term Paper :

Forecasting Techniques Using Moving Average, Exponential Smoothing, and Weighted Moving Average

Forecasting is an attempt to predict the future using either quantitative or qualitative technique. Forecasting is an integral part of human activity, however, businesses are increasingly using the forecasting technique to predict sales, demand planning, cost projection, inventory control, corporate planning, advertising planning, production planning and investment cash flow. (Lucey, 2002). While there are different strategies that can be used for the forecasting, however, the time-series analysis is one of the effective strategies that businesses use for the forecasting. The time series analysis is a form of the statistical or mathematical technique using the past data to forecast the future. The benefit of the time series analysis is the simplicity. The examples of the time series analysis are the moving average, weighted moving average and exponential smoothing.

The objective of the study is to use the moving average, weighted moving average and exponential smoothing to forecast the demand for the next three-quarter.

Moving Average Forecast

The study uses the data in Table 1 to calculate the moving average for the demand of the next three-quarter.

Table 1: Actual Demand Data

Quarter

Forecast

Actual Demand

4Q 2008

1Q 2009

2Q 2009

3Q 2009

4Q 2009

1Q 2010

2Q 2010

3Q 2010

4Q 2010

1Q 2011

Table 2: Three --Quarter Moving Average

Quarter

Forecast

Actual Demand

Error

Calculation

3-Quarter Moving Average

4Q 2008

1Q 2009

2Q 2009

3Q 2009

(220+215+210)/3

4Q 2009

(215+210+220)/3

1Q 2010

(210+220+225)/3

...



2Q 2010

(220+225+240)/3

3Q 2010

228,333

(225+240+255)/3

4Q 2010

231,111

(240+255.260)/3

1Q 2011

233,148

(255+260+270)/3

Exponential Smoothing Forecast

Quarter

Forecast

Actual Demand

Calculation

Forecast using Exponential Smoothing with Value 0.6

4Q 2008

(220+215+210+220+225+240)/6

1Q 2009

211.67+0.6 *(220-211.67)

2Q 2009

220.67+0.6 *(215-220.67)

3Q 2009

217.27+0,6*(210-217.27)

4Q 2009

212.91+0,6*(220-212.91)

1Q 2010

217.16+0,6*(225-217.16)

2Q 2010

221.87+0,6*(240-221.87)

3Q 2010

232.75+0,6*(255-232.75)

4Q 2010

246.10+0,6*(260-246.10)

1Q 2011

254.44+0,6*(270-254.44)

Weighted Moving Average

Quarter

Forecast

Actual Demand

Calculation

Forecasting with 3 WMA (0.50, .35, 0.15)

4Q 2008

1Q 2009

2Q 2009

3Q 2009

0.5*210+0.35*215+0.15*220

4Q 2009

0,5*220+0,35*210+0,15*215

1Q 2010

0,5*225+0,35*220+0,15*210

2Q 2010

0,5*240+0,35*225+0,15*220

3Q 2010

0,5*255+0,35*240+0,15*225

4Q 2010

=0,5*260+0,35*255+0,15*240

1Q 2011

Forecasting techniques used for 2008 and 2009 first two-quarters.

The forecasting technique used to solve to the forecast for the period is t= Actual demand for the period (t - 1)

Forecasting error with Weighted Average Technique

The forecasts are not 100% perfect, thus, it is essential to know the extent of…

Sources Used in Documents:

Reference

Lucey, T. (2002). Quantitative Techniques (Sixth Edition).UK. Cengage Learning EMEA.


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