Develop an appropriate forecast using exponential smoothing

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Reference no: EM132280925

Assignment: Time Series

Overview - This assignment asks you to use forecasting tools to predict the price of gas based on the historical record of prices in Ottawa.

Note: The forecasting can be done either directly in Excel or by utilizing the built in functionality of the Analytic Solver plugin

Part 1: Collecting the Data

Download the SourceData.csv file from Moodle and save it as an excel file. Manipulate the data to isolate only the data that we are interested in - the price of Regular Unleaded Gasoline in Ottawa, on or after June 6, 2005. Place this data in a separate worksheet, name this worksheet OttawaRegGas. This new sheet is what you will use for your forecast.

Part 2: Creating a Forecast

Complete question 5, parts a through d, using the Ottawa data rather than the table provided in the question. When the text's questions refer to days, substitute in weeks - otherwise the questions remain the same.

Part 3: Adding Trends to the Model

3A: Adding a Trend (Holt's Method)

Develop an appropriate forecast using exponential smoothing with a trend (Holt's method).

3B: Adding Cyclicality (Holt-Winter's Method)

Develop an appropriate forecast using exponential smoothing with a trend and cyclicality (Holt-Winter's method).

Part 4: Choosing the Best Model

Which model, of all the forecasts performed in this assignment, is the best?

Cite one factor that lead the best model to be more appropriate than the other ones.

Suggest two improvements that could be made to make the forecast even better?

Reference no: EM132280925


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Deliverables - The deliverables for this assignment are: A written report providing - Title page with Student’s names and group name, date of submission, Class Section, The answers to each of the questions. Include a screenshot of the summary data and the final 8 weeks of projections for the forecast questions. Your spreadsheet(s).

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