Homework assignment number 4 covers Chapters 11 on multiple regression and 13 on time series analysis, and as needed previous regression and inference material. This case study is a continuation of the previous assignment. Use Minitab software for this assignment and add interpretations for every question. You should electronically submit the answers as a single MS Word document with Minitab work pasted into that document to our Blackboard site. All answers require your interpretation, not just the pasted Minitab results, to get any credit. Analysis that you need to provide includes, but is not limited to, discussion of the meaning of the results, analysis of residuals, VIF, analysis of significant observations, and applicability of the model.

In all cases perform full diagnostic analysis including residuals, VIF, influential observations, correlation, graphic descriptive statistics display, etc., and comment on the validity, or lack thereof, of the model and of individual variables and discuss the results including physical meaning. The discussion and interpretation of the results is the critical component of this assignment, not the actual computer analysis which the software performs easily.

Use the ticker that you were assigned for HW04 in this assignment as well as DIA, SPY, and QQQQ ticker data that was provided in the posted Excel file. In all cases unless specifically stated otherwise use the returns and not the original price data.

1. Using returns regress your ticker as the response variable against DIA, SPY and QQQQ as the predictor variables.
2. Using returns and Minitab Use Stat-> Regression- > Stepwise Regression to model your ticker as the response variable and have Minitab determine the best predictor variables.
3. Using the actual prices and not the returns lag your ticker by one to create a new variable using Stat-> Time Series->Lag in Minitab. Regress your ticker as the response variable against the ticker lag 1 variable. Now lag your ticker by two and regress it against the lag 1 and lag 2 values that you created.
4. Using the actual prices and Minitab Stat-> Time Series-> Moving Average try at least 3 periods for the length (say 13, 20 , and 50 ). Perform this both centered and not centered and graph the data and the moving average values for your ticker using the price and not the returns. Now repeat the analysis using Stat-> Time Series-> Single Exponential Smoothing with constants of 0.3 and 0.7. Again graph the results and compare the exponential moving average to the simple moving average.
5. Practice Exam Number 2 (posted) as self-study.

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