Question

An analyst for an investment company wants to develop a regression model to predict the annual...

An analyst for an investment company wants to develop a regression model to predict the annual rate of return (Y) for a stock based on its PE (price/earnings) ratio (X1) and a risk measure (X2). A regression analysis resulted in the following:

If the PE ratio is 11 and the risk measure is 5, then the rate of return is predicted to be

18.10

18.95

17.80

17.45

Math   Statistics-And-Probability   
0 0
Add a commentTranscribed image text
Next >

Homework Answers

Answer #1

ANSWER::

The estimated regression equation is,

Rate of return = - 3.0093+1.1537PE+1.6212 Risk measure

Calculate the rate of return when PE ration is 11 nand the risk measure is 5.

Rate of return = - 3.0093+1.1537(11)+1.6212(5)

= -3.0093+12.6907+8.106

= 17.7874

Rate of return = 17.79 (near by value 17.80)

Option:: (C) is correct...........

  

**Please give me "like"....its very important for me now please....dont skip

NOTE:: I HOPE YOUR HAPPY WITH MY ANSWER....***PLEASE SUPPORT ME WITH YOUR RATING

0 0
Know the answer?
Your Answer:

Post as a guest

Your Name:

What's your source?

Earn Coins

Coins can be redeemed for fabulous gifts.

Log In

Sign Up

Not the answer you're looking for?
Ask your own homework help question
Similar Questions
A business statistics professor would like to develop a regression model to predict the final exam...
A business statistics professor would like to develop a regression model to predict the final exam scores for students based on their current GPAs, the number of hours they studied for the exam, the number of times they were absent during the semester, and their genders. The data for these variables are given in the accompanying table. Complete parts a through d below. Score   GPA   Hours   Absences   Gender 87   3.75   2.0   0   Female 77   3.20   4.5   3   Male 82   3.16  ...
1.A real estate analyst has developed a multiple regression line, y = 60 + 0.068 x1...
1.A real estate analyst has developed a multiple regression line, y = 60 + 0.068 x1 – 2.5 x2, to predict y = the market price of a home (in $1,000s), using two independent variables, x1 = the total number of square feet of living space, and x2 = the age of the house in years. With this regression model, the predicted price of a 10-year old home with 2,500 square feet of living area is __________. $205.00 $255,000.00 $200,000.00...
Ford would like to develop a regression model that would predict the number of cars sold...
Ford would like to develop a regression model that would predict the number of cars sold per month by a dealership employee based on the employee's number of years of sales experience (X1), the employee's weekly base salary before commissions (X2), and the education level of the employee. There are three levels of education in the sales force—high school degree, associate's degree, and bachelor's degree. The following dummy variables have been defined. Degree X3 X4 High School 0 0 Associate's...
An analyst is running a regression model using the following data: Y x1 x2 x3 x4...
An analyst is running a regression model using the following data: Y x1 x2 x3 x4 x5 x6 4 1 5 0 -95 17 12 10 5 8 1 -27 7 10 32 1 7 0 -82 0 9 2 2 7 0 17 5 10 9 3 9 1 -46 5 11 Excel performs the regression analysis, but the output looks all messed up: For example the F statistic cannot be computed, standard errors are all zero, etc etc....
Exercise 11. A researcher wants to develop a mathematical model that relates fuel efficiency (MPG), y,...
Exercise 11. A researcher wants to develop a mathematical model that relates fuel efficiency (MPG), y, to three variables: Engine size, x1, curb weight, x2, and horsepower, x3. Data are gathered from 13 randomly selected vehicles and listed in the table below. Find the multiple regression equation for the data. MPG, y Engine size, x1 Curb weight, x2 Horsepower, x3 24 2.4 3289 177 25 2.4 3263 158 24 2.5 3230 170 22 3.5 3580 272 18 2.8 3175 255...
The owner of a movie theater company used multiple regression analysis to predict gross revenue (y)...
The owner of a movie theater company used multiple regression analysis to predict gross revenue (y) as a function of television advertising (x1)  and newspaper advertising (x2).  The estimated regression equation was ŷ = 83.8 + 2.26x1 + 1.50x2. The computer solution, based on a sample of eight weeks, provided SST = 25.8 and SSR = 23.385. (a) Compute and interpret  R2 and Ra2. (Round your answers to three decimal places.) The proportion of the variability in the dependent variable that can be...
The owner of a movie theater company used multiple regression analysis to predict gross revenue (y)...
The owner of a movie theater company used multiple regression analysis to predict gross revenue (y) as a function of television advertising (x1) and newspaper advertising (x2). The estimated regression equation was ŷ = 82.5 + 2.26x1 + 1.30x2. The computer solution, based on a sample of eight weeks, provided SST = 25.3 and SSR = 23.415. (a)Compute and interpret R2 and Ra2. (Round your answers to three decimal places.) The proportion of the variability in the dependent variable that...
The owner of a movie theater company used multiple regression analysis to predict gross revenue (y)...
The owner of a movie theater company used multiple regression analysis to predict gross revenue (y) as a function of television advertising (x1) and newspaper advertising (x2).The estimated regression equation was ŷ = 83.1 + 2.23x1 + 1.30x2. The computer solution, based on a sample of eight weeks, provided SST = 25.4 and SSR = 23.395. (a) Compute and interpret R2 and Ra2. (Round your answers to three decimal places.) The proportion of the variability in the dependent variable that...
Study the following Minitab output from a regression analysis to predict y from x. a. What...
Study the following Minitab output from a regression analysis to predict y from x. a. What is the equation of the regression model? b. What is the meaning of the coefficient of x? c. What is the result of the test of the slope of the regression model? Let α = .10.Why is the t ratio negative? d. Comment on r2 and the standard error of the estimate. e. Comment on the relationship of the F value to the t...
Management of a fast-food chain proposed the following regression model to predict sales at outlets: y...
Management of a fast-food chain proposed the following regression model to predict sales at outlets: y = β0 + β1x1 + β2x2 + β3x3 + ε, where y = sales ($1000s) x1= number of competitors within one mile x2= population (in 1000s) within one mile x3is 1 if a drive-up window is present, 0 otherwise Multiple regression analysis was performed on a random sample of data collected from 25 outlets. Given the following portion of an output of the regression...
ADVERTISEMENT
Need Online Homework Help?

Get Answers For Free
Most questions answered within 1 hours.

Ask a Question
ADVERTISEMENT