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Ridiculously Simple Time Series Forecasting We will review the following techniques: Simple extrapolation (the “naïve” model). Moving average model Weighted.

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Presentation on theme: "Ridiculously Simple Time Series Forecasting We will review the following techniques: Simple extrapolation (the “naïve” model). Moving average model Weighted."— Presentation transcript:

1 Ridiculously Simple Time Series Forecasting We will review the following techniques: Simple extrapolation (the “naïve” model). Moving average model Weighted moving average model

2 The Naïve Model If your time series exhibits little variation from one period to the next, has no discernible trend, and is unaffected by seasonality, the naïve model is just what you need.

3 The Moving Average Model For example, if n = 4, you have a 4-period moving average model.

4 The Weighted Moving Average Model The ω’s are the weights attached to past observations of the time series variable and there are n periods weighted. Notice that: Σω i = 1. The trick is to select the value of n and corresponding values of so as to minimize MSE

5 Example: Forecasting Retail Sales of Women’s Clothing Our data set contains 163 monthly observations on retail sales of women’s clothing in the U.S. (January 1992 to August 2005) measuring in millions of dollars. We will perform in-sample forecasts using the 3 techniques to determine which has the best fit.

6 Techniques 2 and 3 We will do a 6-month moving average for technique 2 We will do a 4-month weighted moving average for technique 3. The weights are as follows:

7 YR MOMO WRC SNaïveNaïve eSq6 mo MA 6 mo MA esq 4 mo. WMA 4 Mo. WMA eSq 20051 2347449846268013070.8523934.73613.6782163.4 20052 24612347129963036.8331584.03211.1746668.8 20053 311524614277163090.2616.72899.0191844.0 20054 3186311550413119.34444.42903.544732.3 20055 317531861213130.31995.12935.862600.0 20056 30593175134562890.528392.33094.96416.0 20057 27503059954812957.743125.43124.84329.6 ESS(1)82925024ESS (2)34161676ESS(3)22718665.1 MSE (1)511882.86MSE(2)217590.3MSE(3)142884.7 root MSE(1)715.46 root MSE(2)466.5 root MSE (3)378.0 Results

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