OPRE 3333 Lecture Notes - Lecture 8: Business Cycle, Moving Average, Mean Absolute Percentage Error
25 Jun 2018
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CH 8 TIME SERIES + FORECASTING
Forecasting Subjective methods:
Historical analogy –analysis of past experiences◦
Delphi Method –panel of experts◦
Intuition◦
Qualitative methods:
use of expert judgment to develop forecasts
Quantitative forecasting methods can be used when:
(1) past information about the variable being forecast is available,
(2) the information can be quantified, and
(3) it is reasonable to assume that past is prologue
Eight Steps to Forecasting
1.Determine the use of the forecast—what objective are we trying to obtain?
2.Select the items or quantities that are to be forecasted.
3.Determine the time horizon of the forecast.
4.Select the forecasting model or models.
5.Gather the data needed to make the forecast.
6.Validate the forecasting model.
7.Make the forecast.
8.Implement the results.
Time series: sequence of evenly spaced observations of a variable measured at successive periods of
time. based solely on the past values of the variable, and other variables are ignored.
Time series patterns:
Horizontal: data fluctuates randomly around a constant mean over time (stationary time
series).
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Document Summary
Qualitative methods: use of expert judgment to develop forecasts. Quantitative forecasting methods can be used when: (1) past information about the variable being forecast is available, (2) the information can be quantified, and (3) it is reasonable to assume that past is prologue. 2. select the items or quantities that are to be forecasted. 5. gather the data needed to make the forecast. Time series: sequence of evenly spaced observations of a variable measured at successive periods of time. based solely on the past values of the variable, and other variables are ignored. Horizontal: data fluctuates randomly around a constant mean over time (stationary time series). Trend: gradual shifts or movements to higher or lower values over a longer period of time. e. g. changes in consumer preferences. Seasonality: recurring patterns over successive periods of time within a year. e. g. sales umbrellas. Cycles: alternating sequence of points below and above the trendline that last for more than a year. e. g. business cycles.
