Chapter 03 Forecasting (10th)

Chapter 03 Forecasting (10th) - Chapter 3 Forecasting...

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Chapter 3 Forecasting 2010/8/26 Stevenson 10th Edition 1 1 Chapter 3 Forecasting What is forecasting ? How to make a forecast ? Approaches used in forecasting ? How to monitor a forecasting system ? Other applications 2 Features Common to All Forecasts Assume a causal system Forecasts are not perfect Forecast accuracy view point : Forecasts for group of items are better than forecasts for individual items. Forecast accuracy view point : Short-range forecasts are better than long-range forecasts. Time Horizon Two definitions
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Chapter 3 Forecasting 2010/8/26 Stevenson 10th Edition 2 3 Elements of a Good Forecast Timely Accurate Reliable consistent M e a n i g f u l ts Written S m p to d r s ta E y A forecast should be Cost-Effective. 4 Steps in the Forecasting Process Determine the purpose of the forecast Establish a time horizon Select a forecasting technique Obtain, clean, and analyze appropriate data Make the forecast Use the forecast data Monitor the forecast – Acceptable results keep going …. . – Unacceptable results some modifications . ....
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Chapter 3 Forecasting 2010/8/26 Stevenson 10th Edition 3 5 Summary of Forecast Accuracy Forecast accuracy is very easy to define depending on the users needs. (Define: Errors) –A i -F i (Eq.3-1), F i -A i , A i -F i , Σ (A i -F i ), Σ∣ A i -F i , … – Different formula represents different meaning. Measurements of forecast accuracy (text book): – MAD : Mean Absolute Deviation (Eq.3-2/p.76) – MSE : Mean Squared Error (Eq.3-3/p.76) – MAPE : Mean Absolute Percent Error (Eq.3-4/p.76) Example 1/p.76 : Calculation, define n Accuracy is not the only way to evaluate a suitable or perfect or good forecasting system – Smoothing, Responsiveness, Cost, Time, Reliable, …. . 3-6 Forecasting 6 Definition of MAD, MSE, and MAPE MAD = Actual forecast n MSE = Actual forecast ) - 1 2 n ( MAPE = Actual forecast n / Actual*100) ∑(
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Chapter 3 Forecasting 2010/8/26 Stevenson 10th Edition 4 7 Approaches to Forecasting Forecasts based on judgment and opinion – Executive opinions, Salesforce opinions, Consumer survey, …. . – Other Approaches: Delphi method, …. . Forecasts based on time series data Time series : time-ordered sequence of data – Project past “experience” into the future forecast – Identify special patterns Explanatory variable Time Associative forecasting techniques Explanatory variable Time 8 Forecasts Based on Time Series Data
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This note was uploaded on 05/02/2011 for the course FINANCE 9924603 taught by Professor Ssgdbfb during the Spring '11 term at Kyung Hee.

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Chapter 03 Forecasting (10th) - Chapter 3 Forecasting...

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