This document provides stock price data for 8 companies (TSLA, AMZN, WMT, AAPL, F, DIS, IBM, MSFT) from July 2010 to December 2016 in a table with the adjusted closing price for each stock listed for each month. The data will be used for a project analyzing the efficient frontier for a portfolio of these stocks.
1. A Project on Efficient Frontier
Course: FIN 435.4
Submitted To
Hasan A. Mamun
Lecturer,
Department of Accounting and Finance,
North South University
Submitted By
Group Name: Versatile
Name ID
Shuvonkor Karmokar 1420032030
Rifat Hossain Khan 1411038030
Shad Bin Abdur Rahim 1420357030
Sumaiya Fairuz Nabony 1420035030
Md. Ahsan Habib 1410894030
12. About the Project
At first, we searched different companies listed in New York Stock Exchange
(NYSE) and selected 8 stocks from different Industries. Our selected stocks
are TSLA, AMZN, WMT, AAPL, F, DIS, IBM and MSFT. We have collected
monthly adjusted closing price (Raw Data) of July 1, 2010 to June 1, 2018
from the website Yahoo Finance.
We have calculated monthly return of these stocks. We convert it into
annualized form. Then we have calculated standard deviation of these
stocks. We have calculated monthly covariance through generating monthly
covariance matrix by excel extension called "Data Analysis" and Used
‘VAR.P’ equation. Later on we filled the gaps of the matrix and made
another matrix to get an annualized covariance matrix.
Then, used solver application for follow Portfolio Optimization: Markowitz
Method. We have made template and took specific constraint by
adjustments in solver application. We tried to make some portfolio though
changing expected return and minimizing variance simultaneously around
18 times. We took 4.08% as lowest return because this the lowest expected
return and 49.59% as highest return because that's the highest among 8
stocks in the output table.
Next we inserted a ‘Scatter Plot Graph’ where; in X axis indicates ‘risk’ and
‘returns’ in Y axis. The graph that we got there is an "Efficient Frontier" of
selected 8 stocks portfolio.