GE Stock Closing Prices: The Minitab dataset (GE.MTW) given for this assignment is structured in the following format. The first column is the months of observations, in total there are 72 months’ recorded. The second column is the monthly closing prices for the public traded stock of GE company, which is what we are interested in analyzing and predicting for its values. The third column contains monthly closing values of the S&P 500 Index (here we use this index to approximate the market conditions, although not appropriate in real modeling), which is commonly used in finance areas to represent the macroeconomic conditions of the market. Besides, since GE’s market performance is influenced by its competitors and business partners (such as its customers), we include two additional variables (columns) into the dataset. The fourth column shows the closing prices of Philip’s stock, who is one of GE’s main competitors. And the fifth column lists the closing stock prices of Boeing Corp., who is an important customer of GE. The last column contains time period index values, which are used as observations for independent variable “Trend.”
BUSA 3050-02 Page 1 of 2 MGNT 4660 Business Forecasting Assignment 5 Due at 10:00pm on July 12 th , 2012. No late submission is allowed. GE Stock Closing Prices: The Minitab dataset (GE.MTW) given for this assignment is structured in the following format. The first column is the months of observations, in total there are 72 months’ recorded. The second column is the monthly closing prices for the public traded stock of GE company, which is what we are interested in analyzing and predicting for its values. The third column contains monthly closing values of the S&P 500 Index (here we use this index to approximate the market conditions, although not appropriate in real modeling), which is commonly used in finance areas to represent the macroeconomic conditions of the market. Besides, since GE’s market performance is influenced by its competitors and business partners (such as its customers), we include two additional variables (columns) into the dataset. The fourth column shows the closing prices of Philip’s stock, who is one of GE’s main competitors. And the fifth column lists the closing stock prices of Boeing Corp., who is an important customer of GE. The last column contains time period index values, which are used as observations for independent variable “Trend.” (For significance test issue, use significance level of =0.05) With this dataset, you are required to do: 1). Plot the GE’s stock closing prices, and discuss whether there is any trend inside the plot. Show your plot. 2). If you detect the existence of a trend, include the trend variable into your dataset, and then run a simple trend regression model as, ttrendt TrendGE *0 And record its R 2 value. Besides, regress GE against each other independent variable, for example, GE against S&P500, in form of ttt PSGE 500&*10 Among all four one-factor (simple linear regression) models, select the one with the highest R 2 value, and write down your estimated model (not equation), discuss the significance of the model. Page 2 of 2 3). Write down the best two-factor (with two independent variables) regression model, and discuss the significance of the model and of partial regression coefficient, besides, what is your interpretation of these coefficients? 4). Write down the best three-factor regression model. 5). Run a four-factor regression model (including all available independent variables), and write down your model, discuss the overall significance of your model. 6). Compare the adjusted R 2 values of all those best models you find, with that of the four-factor model, and discuss which model provides the best fitness for the data. 7). Obtain the forecasted monthly closing prices of GE stock, based on the best model you select in step 6, plot the forecasts with the real GE closing prices.