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# Forecasting time series based on Moving average

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Please provide tutorial help involving moving averages.

Moving averages often are used to identify movement in stock prices. Daily closing prices (in dollars per share) for a large company (Tab STOCK PRICES data set)

a) Use a 3-time period moving average to smooth the time series. Forecast the closing price for the next trading day.

b) Use the exponential smoothing with a smoothing constant of .6 to smooth the time series. Forecast the closing price for the next trading day.

c) Can you improve upon your exponential smoothing?

d) Which method do you prefer?

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#### Solution Preview

** Please see the attached file for the complete solution **

Moving Average

number of periods: 3

t Price 3MA
1 81.32
2 81.10
3 80.38 80.933
4 81.34 80.940
5 80.54 80.753
6 80.62 80.833
7 79.54 80.233
8 79.46 79.873
9 81.02 80.007
10 80.98 80.487
11 80.80 80.933
12 81.44 81.073
13 81.48 81.240
14 80.75 81.223
15 80.48 80.903
16 80.01 80.413
17 80.33 80.273

Simple Exponential ...

#### Solution Summary

This solution provides a step by step method for computing the Time Series Forecasting.

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## Time Series Forecasting Methods

The scenario we will be using is attached; Your Director of Supply Chain needs help in developing forecasts. Choose one of the following three options.

1.Develop forecasts for periods 6 through 24 using moving average with 3 periods, 4 periods, and 5 periods, or...

2.Develop forecasts for periods 3 through 24 using a smoothing factor of 0.2 and 0.3, or...

3.Develop forecasts for periods 5 through 24 using weighted moving average with weights of 0.4, 0.3, 0.2, and 0.1.

Guidelines:
Calculate the MAD and MSE for all of your forecasts.
Start MAD and MSE calculations for moving averages in period 6.
Start MAD and MSE calculations for exponential smoothing in period 5.
Start MAD and MSE calculations for Weighted Averages in period 5.
Write a 1 page article describing the different forecasting tools.

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