Homework 1
Homework #1
Group homework
Professor: Stathis Tompaidis
Team:
Jessica Janeth Padilla Torres A00952287
Arturo Sánchez Gómez A00952008
Diego Ramos León de la Barra A01530381
Oscar Chávez Chávez A01530382
Oscar Daniel Lechuga Pérez A01530442
José Ricardo Reyes A00454161
Problem 1
Explore the relationship between the selling prices (Y) and the appraised values (X) of the 150 homes in the file hw1_1.xlsx by estimating simple linear regression model. Also, compute the standard error of estimate se and the coefficient of determination R2 for the estimated least squares line. Interpret these measures and the least squares line for these data. a Is there evidence of a linear relationship between the selling price and appraised value? If so, characterize the relationship (i.e., indicate whether the relationship is a positive or negative one, a strong or weak one, etc.) b For which of the two remaining variables, the size of the home and the number of bedrooms in the home, is the relationship with the home’s selling price stronger? Justify your choice with additional simple linear regression models.
Problem 2
The beta of a stock is found by running a regression with the explanatory variable being the monthly return on a market index and the dependent variable being the monthly return on the stock. The beta of the stock is then the slope of this regression. a Explain why most stocks have a positive beta. b Explain why a stock whit a beta with absolute value greater than 1 is more volatile than the market and a stock with a beta less than 1 (in absolute value) is less volatile than the market. c Use the data in the file hw1_2.xlsx to estimate the beta for Ford Motor Company. d What percentage of the variation in Ford’s return is explained by market variation? What percentage is unexplained by market variation? e Verify (using Excel’s COVAR and VARP functions) that the beta for Ford is given by the ratio of the Covariance between Ford and Market and the Variance of Market.
Group homework
Professor: Stathis Tompaidis
Team:
Jessica Janeth Padilla Torres A00952287
Arturo Sánchez Gómez A00952008
Diego Ramos León de la Barra A01530381
Oscar Chávez Chávez A01530382
Oscar Daniel Lechuga Pérez A01530442
José Ricardo Reyes A00454161
Problem 1
Explore the relationship between the selling prices (Y) and the appraised values (X) of the 150 homes in the file hw1_1.xlsx by estimating simple linear regression model. Also, compute the standard error of estimate se and the coefficient of determination R2 for the estimated least squares line. Interpret these measures and the least squares line for these data. a Is there evidence of a linear relationship between the selling price and appraised value? If so, characterize the relationship (i.e., indicate whether the relationship is a positive or negative one, a strong or weak one, etc.) b For which of the two remaining variables, the size of the home and the number of bedrooms in the home, is the relationship with the home’s selling price stronger? Justify your choice with additional simple linear regression models.
Problem 2
The beta of a stock is found by running a regression with the explanatory variable being the monthly return on a market index and the dependent variable being the monthly return on the stock. The beta of the stock is then the slope of this regression. a Explain why most stocks have a positive beta. b Explain why a stock whit a beta with absolute value greater than 1 is more volatile than the market and a stock with a beta less than 1 (in absolute value) is less volatile than the market. c Use the data in the file hw1_2.xlsx to estimate the beta for Ford Motor Company. d What percentage of the variation in Ford’s return is explained by market variation? What percentage is unexplained by market variation? e Verify (using Excel’s COVAR and VARP functions) that the beta for Ford is given by the ratio of the Covariance between Ford and Market and the Variance of Market.