![Economics 309
Applied Financial and Economic Forecasting
Professor:
Stanley Holmes, Ph.D.
Email:
[email protected]
Office:
BA 132D
Phone:
(903) 468-6029 or (903) 365-7190
Fax:
(903) 886-5601
Semester Project
The objective of the project is to simulate a problem you might
face in your first job or business—developing the best 2 year
forecast for company sales. Forecasting is an important process
in almost all businesses and is an important skill to possess as
an employee. The project is due by midnight Central Time on
12/2/2013. You are strongly encouraged to spread the work](https://image.slidesharecdn.com/economics309appliedfinancialandeconomicforecastingprofe-221031052539-c19c1aa5/85/Economics-309Applied-Financial-and-Economic-ForecastingProfe-docx-1-320.jpg)
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- 1. Economics 309 Applied Financial and Economic Forecasting Professor: Stanley Holmes, Ph.D. Email: [email protected] Office: BA 132D Phone: (903) 468-6029 or (903) 365-7190 Fax: (903) 886-5601 Semester Project The objective of the project is to simulate a problem you might face in your first job or business—developing the best 2 year forecast for company sales. Forecasting is an important process in almost all businesses and is an important skill to possess as an employee. The project is due by midnight Central Time on 12/2/2013. You are strongly encouraged to spread the work
- 2. throughout the semester. 1. Selecting independent (X) variables for your project Hopefully you have all passed this stage. You need to pick X variable quarterly data sets. Make sure the data are NOT seasonally adjusted. The data relationships should be logical and not spurious. For example, do not use the price of hamburger to forecast auto sales. 2. Writing an abstract After you pick your topic, it is a good idea to write a brief abstract to help focus your thoughts. The abstract should not be more than a page. It should include (i) State your forecasting problem- develop the best forecast of each variable. (ii) Information about and description of your data (iii) Description of your proposed models 3. Body of the paper The paper will contain detailed explanations of your thought processes and methodology. At every stage you need to answer the following questions for each variable: (i) What did you do (ex: Winter’s method with these parameter values…) (ii) Why did you do it? (iii) What did you find? (Interpretation of your results) (iv) What is your conclusion? Remember this is a business project report for your company – Do Not Show failed model attempts. Show only the best model for each variable for each forecast method. 4. Methodology
- 3. The body of your paper will include all four major forecasting techniques: (i) Smoothing for each X variable (Chapters 8): You need explain what, why, how etc. (ii) Box-Jenkins for each X variable (Chapters 9, 10, 11, 12): (iii) Decomposition for each X variable (Chapter 7) (iv) Multiple Regression forecast of the sales variable (Y) (Chapter 3, 4, 5 and 6): You will need other variable(s) to help explain the variation in the sales variable of interest. You need to start looking for those explanatory (X) variables!! 5. Appendix Your appendix should contain all the relevant supporting printouts such as the tests, plots, graphs etc. that were not used in the discussion in the body of the presentation. It is better to divide the appendix into parts where each part is representing the output from each methodology (ex: Appendix A: Variable Data and citations, Appendix B: X variable outputs, Appendix C: Sales Revenue outputs). Don’t forget to name or number the appendices, you will need to refer to them when you are talking about a specific methodology. 6. Final Report Your final report should include anexecutive summary of your findings which will include the conclusions (Which of the techniques works best and why for each X variable?). You can add the results to your abstract and make the abstract into an executive summary. You need to have an introductionto talk about your topic in greater length. It will include above sections 3, 4 and 5 and a conclusion. Be detailed and complete in all your sections. This is a case of more is better than less as you explain to me what you have done.
- 4. � Please remember that there is NOT one right way of preparing a paper. Be precise, explain everything in detail and be structured. The outline is ONLY to remind you about the required parts; its arrangement is completely up to you. RevenueJ.C. PennyGAPSearsBest BuyCostcoWalMartTarget DirectTVDISHDisneyNetflixGeicoAetnaAflacUnitedHealth GroupAppleMicrosoftDELL Auto ZoneOReilly Auto PartsWD- 40AT&TVerizonFord MotorGM ChryslerToyotaHersheyHibbett SportsDicks Sporitng GoodsSports AuthorityHome DepotLowesAMD IntelJet BlueU.S. AirwaysAmerican AirlinesSouthwest Airlines United AirlinesUPS FedExDateRevenueDateSalesDateRevenueDateRevenueDateRev enueDateRevenueDateRevenueDateRevenueDateRevenueDate RevenueDateSalesDateRevenueDateRevenue DateRevenueDateRevenueDateRevenueDateRevenueDateSalesD ateSalesDateRevenueDateSalesDateRevenueDateRevenueDateSa lesDateRevenueDateRevenueDateRevenueDateRevenueDateSale sDateRevenueDateRevenueDateSalesDateSalesDateRevenueDat eRevenueDateSalesDateRevenueDateRevenueDateRevenueDate Revenue DateSalesDateRevenue3/31/9543673/31/95848.6883/31/957443 3/31/951947.1113/31/954307.32183/31/895373.25983/31/89282 63/31/953566.83/31/9540.4133/31/80218.13/29/0230.5273/31/9 5951.312/29/006598.43/31/951713.6763/31/951103.8353/31/95 26523/31/9515873/31/951135.9333/31/95364.0613/31/9542.766 3/30/9022.5433/31/9551643/31/953449.73/31/95347839/30/092 67843/31/1097006/29/0133477403/31/95867.4469/30/9620.6181 2/31/043642070003/31/98155.2173/31/953568.9623/31/951634. 693/31/95627.3813/31/9535573/29/02133.3693/31/0516283/31/ 9839603/31/95611.7133/31/951408.3433/29/9653359/29/891647 .4536/30/9544356/30/95868.5146/30/9584406/30/951274.6966/ 30/953896.2386/30/896046.41316/30/8930976/30/953708.56/30
- 22. 1105523/31/111041893/31/11159353/29/0258566/29/1287.0229/ 30/11105216/30/111093666/30/11162406/28/0257959/28/1284.8 5112/30/11105879/30/111102269/30/11164029/30/02666212/31/ 1295.2643/30/121056412/30/1112316912/30/112128812/31/027 1703/29/1386.7126/29/12110083/30/121130183/30/12168673/31 /0365006/28/1393.1039/28/12107926/29/121142966/29/1216779 6/30/03637712/31/12111079/28/121139299/28/12169299/30/037 0143/29/131095312/31/1212791912/31/122272612/31/0385496/ 28/13114353/29/131141873/29/13167063/31/0471896/28/13116 9456/28/13171176/30/0474719/30/04754312/31/0486663/31/057 8296/30/0577159/30/05773412/30/0588543/31/0680276/30/0684 749/29/06865212/29/0695813/30/0779546/29/0790459/28/07893 012/31/07104523/31/0887106/30/0892369/30/08944512/31/0895 993/31/0980876/30/0985969/30/09986712/31/0997393/31/10858 06/30/10100029/30/10974212/31/10107163/31/1190776/30/1110 6759/30/111042512/30/11107793/30/1296296/29/12110889/28/1 21078212/31/12113413/29/13105546/28/1311578 Sheet2 Sheet3 Project Proposal Due by Midnight 9/16/2013 You have been hired by a major corporation to forecast their quarterly sales for two years. As a result, you need to show progress in the initial forecasting steps. Your proposal should begin with a hypothesis statement about the variables that you selected to use in the forecast of company sales. 1. Your proposal should begin with a hypothesis statement about the variables that you selected to use in the forecast of company sales. Include a brief statement of why you chose each variable to forecast sales. 2. Obtain quarterly sales/revenue data for the company you are assigned and load it into Minitab and save it as your Eco 309 Project. See the email that I sent you earlier with the quarterly
- 23. data. You can refer to the project outline for further details. You may also download and save the data as an EXCEL file. The first column should be the dates and second column should be your data. Always label your columns appropriately. 3. Go to one of the approved data sources. This time you will need to obtain minimum 3 related variables. These variables should be values determined outside of the firm. (Not company accounting data) We will call these related variables the X variables. These variables will be quarterly consistent with your Y variable (If your Y variable is quarterly, your X variables will also be quarterly). All variables should be from the same time period. You can refer to the project outline for further details. 4. As an option for one of the three X variables you may Ggo to the company web site, annual reports or 10-K SEC filings and obtain any relevant internal data that you wish to include as another X variable. This could be R&D Expenses, Marketing Expenses, Total Expenses Product Units, Employees, etc. that you believe are important to the output of the company. Make sure that this variable is quarterly as well and covers the same time as the Y variable. 5. As another option for one of the three X variables you may go to the company data in Doc Sharing and see if you can find either competitor companies or companies that produce goods that are complimentary to your assigned company. You may also look for competitors sales data from 10-Ks and annual reports. Remember that this must also cover the entire time period you have for the assigned Y data. You may use the revenue/sales figures for these companies as another X variable. 6. Download and save all your X variables in your Minitab project worksheet labeled appropriately and save Minitab project. You may also save them as an EXCEL file. Recall that the first column is dates and second column is your Y variable. Your third column will be X1, 4th will be X2 and so forth.
- 24. Label your X variables properly so I can understand what those variables are. 7. At this point you should have a copy of dates (C1), Y variable (C2) and X variables (C3 – C5) in a MINITAB project worksheet. Make sure that the variable columns are labeled correctly so I can understand which variables you are analyzing. 8. Run individual “Time Series Plots” and “ACF” on all your variables. Note the Trend, Cycle and Seasonality characteristics that are indicated by these plots. Note which X variable trend, cycle and seasonality characteristics are similar to the Y variable characteristics. 9. Produce descriptive statistics for all your variables. Comment on the mean, range and standard deviation and what they indicate relative to each variable. 10. Run Scatter plots of Y against each X separately. Note the linearity of the relationship. Classify it as positive or negative, weak, moderate or strong. 11. Develop and show the correlation matrix (you can find it under Stat>Basic Statistics>Correlation) of Y and all Xs. Enter the Y values first followed by each X that you have in order of the data columns. You need to tell me which Xs are more related to Y and which Xs are not. You need to prove that the relationships are statistically significant. 12. Your proposal should be a word document and include the pasted relevant Minitab output as well as the, the data used in a table at the end of the word document. The table should be followed by a brief description and source of each variable. You should put the webpage or document page that each variable came from. Do not submit Minitab files. Submit the word proposal document in the proposal dropbox.
- 25. Chapter 1: Chapter 1 - X Variable Data Sources The websites below are the approved sources for your project independent variable (X) data. They include: General Economic and Business data-- www.economagic.comwww.nber.orghttp://research.stlouisfed.or g/fred2/ http://www.economy.com/freelunch Employment Statistics--www.stats.bls.gov Population Characteristics data-- http://www.census.gov/popest/estbygeo.html http://www.census.gov/econ/index.html Regional Economic Data from the Dallas Federal Reserve Bank- - http://dallasfed.org/data/resources.html Texas Employment and Unemployment data http://www.tracer2.com/ Make sure to carefully read the project proposal requirements and the project outline in the Doc Sharing area under the tab at the top of this screen. Look at the data available in these sites and decide which data series you wish to select for the X variables and forecast. Keep in mind that you must find at least three other related quarterly data series of the same length (and dates) to help you forecast your primary sales data series. This means that you will need four data series with the same periods (quarters) for your project.