Question

2. A financial analyst measures the monthly returns of two stocks (A and B) over a twenty year period. Over that time period,SUMMARY OUTPUT Regression Statistics Multiple R 0.890981589 R Square 0.793848192 Adjusted R Square 0.792982008 Standard Error

0 0
Add a comment Improve this question Transcribed image text
Answer #1

Risk Premium = (Rm – Rrf)

The CAPM formula is used for calculating the expected returns of an asset. It is based on the idea of systematic risk or non-diversifiable risk and that investors need to be compensated for it in the form of a risk premium. A risk premium is a rate of return greater than the risk-free rate.
Expected return = Risk Free Rate + [Beta x Market Return Premium].
Therefore calculating from above given information, stock B seems to have more diversified risk

Add a comment
Know the answer?
Add Answer to:
2. A financial analyst measures the monthly returns of two stocks (A and B) over a...
Your Answer:

Post as a guest

Your Name:

What's your source?

Earn Coins

Coins can be redeemed for fabulous gifts.

Not the answer you're looking for? Ask your own homework help question. Our experts will answer your question WITHIN MINUTES for Free.
Similar Homework Help Questions
  • Use the info to create the model's equation. Mkt-RF SMB HML RF S&P 500 NASDAQ 1.250...

    Use the info to create the model's equation. Mkt-RF SMB HML RF S&P 500 NASDAQ 1.250 -0.940 -0.560 0.100 1.441 0.015 Find Expected return given the following market performance c. What is SMB and MHL in this model? 13. This regression output is used in estimating the Fama- French 3 factor model. Use it to answer the following questions: Regression Statistics Multiple R 0.793 R Square 62.8% Adjusted R Square 61.7% Standard Error 2.830 Observations 103 ANOVA F 3 SS...

  • Regression Statistics Multiple R 0.88012 R Square 0.77461 Adjusted R Square 0.77190 Standard Error 56.6927 Observations...

    Regression Statistics Multiple R 0.88012 R Square 0.77461 Adjusted R Square 0.77190 Standard Error 56.6927 Observations 253 ANOVA Significance 285.2516 MS 916816.787 3214.0637 Regression Residual Total 0.000 2750450.3598 800301.8665 3550752.226 252 Intercept Income Coefficients Standard Error 70.2382 15.8338 5.45850 .2485 t Stat P-value 4.4360 0.000014 21.96960 .000 Lower 3 9.053 4.969 "pper 95% 1.4234 479 HULLU LIIS TILIR. SUMMARY OUTPUT Regression Statistics Multiple R 0.8778 R Square Adjusted R Square 0.6558 Standard Error Observations ANOVA ANOVA Significance Regression 45.3528 de...

  • 1.a. Conduct a two-sample t-test to find out if there is a significant difference between U.S. stock returns and U.S. corporate bond returns using the monthly data covering the sample period 1980-2017...

    1.a. Conduct a two-sample t-test to find out if there is a significant difference between U.S. stock returns and U.S. corporate bond returns using the monthly data covering the sample period 1980-2017. 1.b. Conduct a two-sample t-test to find out if there is a greater returns for U.S. stock as compared to U.K. stock returns using the monthly data covering the sample period 1980-2017. 2. Estimate a multiple linear regression relationship with the U.K. stock returns as the dependent variable,...

  • What is the coefficient? What is the standard error? What is the z-statistic? Is the coefficient...

    What is the coefficient? What is the standard error? What is the z-statistic? Is the coefficient sufficiently different from zero? How about one? Explain. SUMMARY OUTPUT Regression Statistics Multiple R 0.58175248 R Square 0.33843594 Adjusted R S 0.31393357 Standard Err 1.1991813 Observations 29 ANOVA df SS MS Significance F 0.000932269 Regression 1 19.86268888 19.86268888 13.8123745 Residual 38.82696629 27 1.438035789 Total 58.68965517 28 Coefficients Standard Error P-value t Stat Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept -0.0202247 0.223805467 -0.090367404...

  • Hi I was wondering if i could have some help with some distribution questions. 1. show...

    Hi I was wondering if i could have some help with some distribution questions. 1. show where zero and one fall on a normal distribution based on thedata. 2.is the coefficient sufficiently different than zero? explain 3. is the coefficient sufficiently different than one? explain. Regression Statistics Multiple R 0.806174983 0.649918103 R Square Adjusted R Square Standard Error Observations 0.636952107 13.57635621 29 ANOVA Significance F E SS MS df 9238.877183 9238.877 50.12481 1.30123E-07 Regression Residual 4976.571093 184.3174 27 14215.44828 Total...

  • Dep.= % WRK Indep.= % MGT SUMMARY OUTPUT Regression Statistics Multiple R R Square Adjusted R...

    Dep.= % WRK Indep.= % MGT SUMMARY OUTPUT Regression Statistics Multiple R R Square Adjusted R Square Standard Error Observations ANOVA Significance df SS MS F F Regression 102.1488 148.9539 Residual Total 12.0000 Standard Coefficients Error t Stat P-value Lower 95% Upper 95% Intercept % MGT 0.4543 SE CI CI PI PI Predicted Predicted Lower Upper Lower Upper x0 Value Value 95% 95% 95% 95% 67.0000 67.8474 65.8779 69.8169 72.0000 70.1189 68.2003 72.0375 76.0000 71.9361 69.7884 74.0838 Dep.= % MGT...

  • 7,10,11 Based on the following regression output, what is the equation of the regression line? Regression...

    7,10,11 Based on the following regression output, what is the equation of the regression line? Regression Statistics Multiple R 0.917214 R Square 0.841282 Adjusted R Square 0.821442 Standard Error 9.385572 Observations 10 ANOVA df SS MS Significance F 1 Regression 3735.3060 3735.30600 42.40379 0.000186 8 Residual 704.7117 88.08896 9 Total 4440.0170 Coefficients Standard Error t Stat P-value Lower 95% Intercept 31.623780 10.442970 3.028236 0.016353 7.542233 X Variable 1.131661 0.173786 6.511819 0.000186 0.730910 o a. 9; = 7.542233+0.7309 Xli o b....

  • You were asked by your manager to evaluate the regression tables below to decide which cost driver would be best to use...

    You were asked by your manager to evaluate the regression tables below to decide which cost driver would be best to use for the production department. Since your manager is new and does not understand the regression analysis tables, you will need to explain why one set of statistics is better than the other and why you have chosen the better driver.   Manufacturing Direct Labor Hours Regression Statistics Multiple R 0.799304258 R Square 0.638887297 Adjusted R Square 0.602776026 Standard Error...

  • 11. (35 pts) An agent for a real estate company wanted to predict the monthly rent...

    11. (35 pts) An agent for a real estate company wanted to predict the monthly rent for one- bedroom apartments, based on the size of the apartment (see summary output below). Using the results, identify the coefficient of determination, r2, and interpret its meaning. SUMMARY OUTPUT Regression Statistics Multiple R 0.354314 R Square 0.125539 Adjusted R Square 0.106529 Standard Error 186.0407 Observations 48 ANOVA df Regression Residual Total 1 46 47 Significance SS MS F F 228565.2 228565.2 6.603807 0.013481439...

  • Calculate the following statistics given the existing information (1 point per calculation): Regression Statistics Multiple R...

    Calculate the following statistics given the existing information (1 point per calculation): Regression Statistics Multiple R R Square Adjusted R Square 0.559058 Standard Error Observations 30 ANOVA df SS MS F Significance F Regression 2 3609132796 19.38411515 6.02827E-06 Residual 27 2513568062 Total 29 6122700857 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Intercept -15800.8 57294.51554 -0.27578 0.784814722 CARAT 12266.83 1999.250369 6.135715 1.48071E-06 DEPTH 156.686 928.9461882 0.168671 0.867312915 Additionally interpret your results. Be sure to comment on Accuracy, significance...

ADVERTISEMENT
Free Homework Help App
Download From Google Play
Scan Your Homework
to Get Instant Free Answers
Need Online Homework Help?
Ask a Question
Get Answers For Free
Most questions answered within 3 hours.
ADVERTISEMENT
ADVERTISEMENT
ADVERTISEMENT