Homework Help is Here – Start Your Trial Now!
Math
Statistics
Estimate the above regression for each of the five FAANG stocks (using the S&P500 as a measure of market returns) and answer the questions below: 1. What is the value of the alpha and beta parameters for each stock? Based solely on the estimated slope parameters derived using OLS estimation, which stocks would you recommend be included in the tech-fund based on the criterion specified?

Estimate the above regression for each of the five FAANG stocks (using the S&P500 as a measure of market returns) and answer the questions below: 1. What is the value of the alpha and beta parameters for each stock? Based solely on the estimated slope parameters derived using OLS estimation, which stocks would you recommend be included in the tech-fund based on the criterion specified?

MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
See similar textbooks
icon
Related questions
Question
You are a portfolio analyst at an investment firm. Given the high returns of 'tech' stocks over the last decade, your firm decides to create a tech-fund. However, the firm only wants to include stocks whose returns are no more volatile than market returns. You are given a spread sheet with data on monthly returns (in percent) for a five-year period (62 observations) of five technology companies and must select those to be included in the tech-fund based on the above criterion. To test the relative volatility you regress monthly returns of each tech stock (Facebook, Amazon, Apple, Netflix, Google - sometimes called the FAANG companies) on monthly returns of a market index fund (using the S&P500 index as a proxy). This procedure is known as determining the characteristic line of a stock and is the first step in estimating the Capital Asset Pricing Model (CAPM)¹. A regression model for the characteristic line is given by: rit = ai + Birmt + Ui Where it is the return of asset i at time t, a; is the intercept parameter for asset i, ß, is the slope parameter for asset i, rmt is the market return at time t, and uit is a stochastic disturbance term (unexplained return) for stock i. The estimated slope parameter of this regression can be interpreted as follows: if the slope parameter exceeds 1 for a given stock, that stock's returns are more volatile than the market returns. If the slope parameter is equal to or smaller than 1, the stock's returns are no more volatile than the market's returns. The estimated intercept parameter can be interpreted as follows: if a; is different from zero, the stock has excess returns relative to the market as a whole. Questions Estimate the above regression for each of the five FAANG stocks (using the S&P500 as a measure of market returns) and answer the questions below: 1. What is the value of the alpha and beta parameters for each stock? Based solely on the estimated slope parameters derived using OLS estimation, which stocks would you recommend be included in the tech-fund based on the criterion specified?
Transcribed Image Text:You are a portfolio analyst at an investment firm. Given the high returns of 'tech' stocks over the last decade, your firm decides to create a tech-fund. However, the firm only wants to include stocks whose returns are no more volatile than market returns. You are given a spread sheet with data on monthly returns (in percent) for a five-year period (62 observations) of five technology companies and must select those to be included in the tech-fund based on the above criterion. To test the relative volatility you regress monthly returns of each tech stock (Facebook, Amazon, Apple, Netflix, Google - sometimes called the FAANG companies) on monthly returns of a market index fund (using the S&P500 index as a proxy). This procedure is known as determining the characteristic line of a stock and is the first step in estimating the Capital Asset Pricing Model (CAPM)¹. A regression model for the characteristic line is given by: rit = ai + Birmt + Ui Where it is the return of asset i at time t, a; is the intercept parameter for asset i, ß, is the slope parameter for asset i, rmt is the market return at time t, and uit is a stochastic disturbance term (unexplained return) for stock i. The estimated slope parameter of this regression can be interpreted as follows: if the slope parameter exceeds 1 for a given stock, that stock's returns are more volatile than the market returns. If the slope parameter is equal to or smaller than 1, the stock's returns are no more volatile than the market's returns. The estimated intercept parameter can be interpreted as follows: if a; is different from zero, the stock has excess returns relative to the market as a whole. Questions Estimate the above regression for each of the five FAANG stocks (using the S&P500 as a measure of market returns) and answer the questions below: 1. What is the value of the alpha and beta parameters for each stock? Based solely on the estimated slope parameters derived using OLS estimation, which stocks would you recommend be included in the tech-fund based on the criterion specified?
Date 1 01 02 2017 2 01 03 2017 3 01 04 2017 4 01 05 2017 5 01 06 2017 6 01 07 2017 7 01 08 2017 8 01 09 2017 9 01 10 2017 10 01 11 2017 11 01 12 2017 12 01 01 2018 13 01 02 2018 14 01 03 2018 15 01 04 2018 16 01 05 2018 17 01 06 2018 18 01 07 2018 19 01 08 2018 20 01 09 2018 21 01 10 2018 22 01 11 2018 23 01 12 2018 24 01 01 2019 25 01 02 2019 26 01 03 2019 27 01 04 2019 28 01 05 2019 29 01 06 2019 30 01 07 2019 31 01 08 2019 32 01 09 2019 33 01 10 2019 34 01 11 2019 35 01 12 2019 36 01 01 2020 37 01 02 2020 38 01 03 2020 39 01 04 2020 40 01 05 2020 41 01 06 2020 42 01 07 2020 43 01 08 2020 44 01 09 2020 45 01 10 2020 46 01 11 2020 47 01 12 2020 48 01 01 2021 49 01 02 2021 50 01 03 2021 51 01 04 2021 52 01 05 2021 53 01 06 2021 54 01 07 2021 55 01 08 2021 56 01 09 2021 57 01 10 2021 58 01 11 2021 59 01 12 2021 60 01 01 2022 61 01 02 2022 62 01 03 2022 Netfilx Amazon 0.037198 0.026182 Facebook Google Apple 0.12879 0.066595 0.033158 0.010092 0.04911 0.04869 0.037493 0.007714 0.039963 -0.00039 -7E-05 0.044478 0.092097 0.009091 0.043371 0.011576 0.075276 0.063418 -0.02834 0.065014 0.0297 0.071419 -0.05817 -0.08377 0.004814 -0.02676 -0.05721 -0.01925 0.019349 0.020434 0.032704 0.111866 0,023957 0.215849 0.000546 -0.00727 0.102669 -0.02308 0.00949 -0.03826 0.019303 -0.06024 0.007644 0.021058 0.038006 -0.05186 -0.01963 0.022188 0.149717 0.096808 0.063931 0.059983 0.083154 0.028083 0.064662 0.016623 -0.03974 0.004692 -0.04505 0.02335 -0.01525 0.003713 0.024466 0.009832 -0.00619 0.02132 0.118062 0.408106 0.056179 0.240639 -0.01064 -0.02542 -0.05574 0.077987 -0.03895 0.042429 0.063848 -0.05805 -0.12426 -0.06603 0.013625 -0.02688 -0.04305 -0.01401 0.057931 0.002719 0.082075 -0.01502 0.099684 0.021608 0.040539 0.130764 0.153582 0.066507 0.125264 0.004842 0.043065 -0.00942 0.019584 0.028258 0.113282 -0.1379 0.036022 0.045676 0.027983 -0.11507 0.091077 0.030263 0.132365 0.196227 0.021031 0.000764 0.089584 0.004294 -0.00482 -0.0083 -0.05704 -0.02029 0.017542 -0.0694 -0.20219 -0.03048 -0.19338 -0.05692 -0.09778 0.017859 0.057672 -0.18404 -0.08552 0.016401 -0.11135 0.09178 -0.1167 -0.04165 -0.05374 -0.06455 0.2684 0.078684 0.144317 0.055154 0.237696 0.077983 0.029729 -0.04591 0.040315 -0.02909 0.00318 0.054786 -0.0043 0.017924 0.085936 0.097026 0.041872 0.047673 0.039313 0.081859 0.056436 0.176996 0.012929 0.039208 -0.06578 -0.07861 -0.12757 -0.07737 -0.07139 -0.07357 0.07003 0.06893 0.066792 0.130519 0.043365 -0.02059 0.013128 -0.01418 0.076394 0.054102 0.125607 -0.12069 -0.01809 -0.04847 -0.02018 -0.04124 -0.02349 -0.09053 0.017181 -0.02273 0.072962 -0.04183 0.026008 -0.08895 0.020432 0.023475 0.110684 0.083004 0.033724 0.073948 0.034047 0.013587 0.074329 0,043047 0.035592 0.094812 0.02859 0.026122 0.098784 0.012228 0.024568 0.028316 -0.00163 0.087064 0.05401 -0.01532 0.072706 0.066508 -0.08411 -0.06221 -0.12512 0.035021 0.126844 0.2689 0.155374 0.210916 0.159828 0.118109 0.045282 -0.01278 0.082165 0.088216 0.059511 -0.00029 0.018388 0.129567 0.147386 -0.01765 -0.01071 0.084126 0.055101 0.147114 0.165132 0.075444 0.049059 0.074367 0.070065 0.090461 0.21438 0.150292 0.101972 0.083211 -0.03923 -0.08758 -0.10253 -0.08602 -0.10071 -0.05576 -0.02767 -0.03575 -0.06001 -0.00577 0.103028 -0.04858 0.107546 0.04344 0.093606 0.022103 0.086199 0.031446 0.037121 0.028058 0.114574 -0.01311 -0.00503 0.101956 -0.01558 -0.0055 -0.06463 0.047869 -0.01542 -0.03533 -0.08109 0.034311 0.109558 0.012134 -0.1168 -0.06638 -0.06617 0.069373 -0.06976 -0.09715 -0.1318 0.017532 -0.01114 0.026091 0.042439 0.000372 0.00734 0.152368 0.015597 0.0319 0.052425 0.120663 0.076218 0.075839 0.16508 -0.0157 0.005487 -0.07047 0.05211 -0.01218 0.000597 -0.02076 0.022214 0.067355 0.099109 0.100878 0.039294 0.050516 0.022748 -0.03272 0.064982 0.023757 0.07904 -0.02014 0.02899 0.043034 0.04093 0.066634 0.075735 0.099735 -0.04757 -0.05352 0.069144 0.026602 0.058657 -0.00833 0.039924 0.103471 0.043613 -0.04925 0.074229 0.055286 0.015637 -0.06147 -0.05259 -0.10283 -0.01571 -0.08901 -0.06208 -0.29098 -0.03136 0.026673 -0.05527 -0.32937 -0.00595 -0.07637 0.035773 0.061437 0.057473 0.09086 0.035277 -0.05052 0.06804 -0.08827 -0.08385 0.072296 0.04142 0.112595 0.131025 0.02596 -0.03924 -0.07013
Transcribed Image Text:Date 1 01 02 2017 2 01 03 2017 3 01 04 2017 4 01 05 2017 5 01 06 2017 6 01 07 2017 7 01 08 2017 8 01 09 2017 9 01 10 2017 10 01 11 2017 11 01 12 2017 12 01 01 2018 13 01 02 2018 14 01 03 2018 15 01 04 2018 16 01 05 2018 17 01 06 2018 18 01 07 2018 19 01 08 2018 20 01 09 2018 21 01 10 2018 22 01 11 2018 23 01 12 2018 24 01 01 2019 25 01 02 2019 26 01 03 2019 27 01 04 2019 28 01 05 2019 29 01 06 2019 30 01 07 2019 31 01 08 2019 32 01 09 2019 33 01 10 2019 34 01 11 2019 35 01 12 2019 36 01 01 2020 37 01 02 2020 38 01 03 2020 39 01 04 2020 40 01 05 2020 41 01 06 2020 42 01 07 2020 43 01 08 2020 44 01 09 2020 45 01 10 2020 46 01 11 2020 47 01 12 2020 48 01 01 2021 49 01 02 2021 50 01 03 2021 51 01 04 2021 52 01 05 2021 53 01 06 2021 54 01 07 2021 55 01 08 2021 56 01 09 2021 57 01 10 2021 58 01 11 2021 59 01 12 2021 60 01 01 2022 61 01 02 2022 62 01 03 2022 Netfilx Amazon 0.037198 0.026182 Facebook Google Apple 0.12879 0.066595 0.033158 0.010092 0.04911 0.04869 0.037493 0.007714 0.039963 -0.00039 -7E-05 0.044478 0.092097 0.009091 0.043371 0.011576 0.075276 0.063418 -0.02834 0.065014 0.0297 0.071419 -0.05817 -0.08377 0.004814 -0.02676 -0.05721 -0.01925 0.019349 0.020434 0.032704 0.111866 0,023957 0.215849 0.000546 -0.00727 0.102669 -0.02308 0.00949 -0.03826 0.019303 -0.06024 0.007644 0.021058 0.038006 -0.05186 -0.01963 0.022188 0.149717 0.096808 0.063931 0.059983 0.083154 0.028083 0.064662 0.016623 -0.03974 0.004692 -0.04505 0.02335 -0.01525 0.003713 0.024466 0.009832 -0.00619 0.02132 0.118062 0.408106 0.056179 0.240639 -0.01064 -0.02542 -0.05574 0.077987 -0.03895 0.042429 0.063848 -0.05805 -0.12426 -0.06603 0.013625 -0.02688 -0.04305 -0.01401 0.057931 0.002719 0.082075 -0.01502 0.099684 0.021608 0.040539 0.130764 0.153582 0.066507 0.125264 0.004842 0.043065 -0.00942 0.019584 0.028258 0.113282 -0.1379 0.036022 0.045676 0.027983 -0.11507 0.091077 0.030263 0.132365 0.196227 0.021031 0.000764 0.089584 0.004294 -0.00482 -0.0083 -0.05704 -0.02029 0.017542 -0.0694 -0.20219 -0.03048 -0.19338 -0.05692 -0.09778 0.017859 0.057672 -0.18404 -0.08552 0.016401 -0.11135 0.09178 -0.1167 -0.04165 -0.05374 -0.06455 0.2684 0.078684 0.144317 0.055154 0.237696 0.077983 0.029729 -0.04591 0.040315 -0.02909 0.00318 0.054786 -0.0043 0.017924 0.085936 0.097026 0.041872 0.047673 0.039313 0.081859 0.056436 0.176996 0.012929 0.039208 -0.06578 -0.07861 -0.12757 -0.07737 -0.07139 -0.07357 0.07003 0.06893 0.066792 0.130519 0.043365 -0.02059 0.013128 -0.01418 0.076394 0.054102 0.125607 -0.12069 -0.01809 -0.04847 -0.02018 -0.04124 -0.02349 -0.09053 0.017181 -0.02273 0.072962 -0.04183 0.026008 -0.08895 0.020432 0.023475 0.110684 0.083004 0.033724 0.073948 0.034047 0.013587 0.074329 0,043047 0.035592 0.094812 0.02859 0.026122 0.098784 0.012228 0.024568 0.028316 -0.00163 0.087064 0.05401 -0.01532 0.072706 0.066508 -0.08411 -0.06221 -0.12512 0.035021 0.126844 0.2689 0.155374 0.210916 0.159828 0.118109 0.045282 -0.01278 0.082165 0.088216 0.059511 -0.00029 0.018388 0.129567 0.147386 -0.01765 -0.01071 0.084126 0.055101 0.147114 0.165132 0.075444 0.049059 0.074367 0.070065 0.090461 0.21438 0.150292 0.101972 0.083211 -0.03923 -0.08758 -0.10253 -0.08602 -0.10071 -0.05576 -0.02767 -0.03575 -0.06001 -0.00577 0.103028 -0.04858 0.107546 0.04344 0.093606 0.022103 0.086199 0.031446 0.037121 0.028058 0.114574 -0.01311 -0.00503 0.101956 -0.01558 -0.0055 -0.06463 0.047869 -0.01542 -0.03533 -0.08109 0.034311 0.109558 0.012134 -0.1168 -0.06638 -0.06617 0.069373 -0.06976 -0.09715 -0.1318 0.017532 -0.01114 0.026091 0.042439 0.000372 0.00734 0.152368 0.015597 0.0319 0.052425 0.120663 0.076218 0.075839 0.16508 -0.0157 0.005487 -0.07047 0.05211 -0.01218 0.000597 -0.02076 0.022214 0.067355 0.099109 0.100878 0.039294 0.050516 0.022748 -0.03272 0.064982 0.023757 0.07904 -0.02014 0.02899 0.043034 0.04093 0.066634 0.075735 0.099735 -0.04757 -0.05352 0.069144 0.026602 0.058657 -0.00833 0.039924 0.103471 0.043613 -0.04925 0.074229 0.055286 0.015637 -0.06147 -0.05259 -0.10283 -0.01571 -0.08901 -0.06208 -0.29098 -0.03136 0.026673 -0.05527 -0.32937 -0.00595 -0.07637 0.035773 0.061437 0.057473 0.09086 0.035277 -0.05052 0.06804 -0.08827 -0.08385 0.072296 0.04142 0.112595 0.131025 0.02596 -0.03924 -0.07013
Expert Solution
steps

Step by step

Solved in 4 steps with 7 images

SEE SOLUTIONCheck out a sample Q&A here
Blurred answer
Similar questions
  • SEE MORE QUESTIONS
Recommended textbooks for you
MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
Statistics
ISBN:
9781119256830
Author:
Amos Gilat
Publisher:
John Wiley & Sons Inc
Probability and Statistics for Engineering and th…
Probability and Statistics for Engineering and th…
Statistics
ISBN:
9781305251809
Author:
Jay L. Devore
Publisher:
Cengage Learning
Statistics for The Behavioral Sciences (MindTap C…
Statistics for The Behavioral Sciences (MindTap C…
Statistics
ISBN:
9781305504912
Author:
Frederick J Gravetter, Larry B. Wallnau
Publisher:
Cengage Learning
Elementary Statistics: Picturing the World (7th E…
Elementary Statistics: Picturing the World (7th E…
Statistics
ISBN:
9780134683416
Author:
Ron Larson, Betsy Farber
Publisher:
PEARSON
The Basic Practice of Statistics
The Basic Practice of Statistics
Statistics
ISBN:
9781319042578
Author:
David S. Moore, William I. Notz, Michael A. Fligner
Publisher:
W. H. Freeman
Introduction to the Practice of Statistics
Introduction to the Practice of Statistics
Statistics
ISBN:
9781319013387
Author:
David S. Moore, George P. McCabe, Bruce A. Craig
Publisher:
W. H. Freeman
SEE MORE TEXTBOOKS