dc.contributor.advisor | Majumdar, Mahbubul Alam | |
dc.contributor.author | Kundu, Souvik | |
dc.contributor.author | Khan, Mustaqim | |
dc.contributor.author | Rahman, Faisal | |
dc.date.accessioned | 2020-08-19T15:35:33Z | |
dc.date.available | 2020-08-19T15:35:33Z | |
dc.date.copyright | 2019 | |
dc.date.issued | 2019-12 | |
dc.identifier.other | ID 19141015 | |
dc.identifier.other | ID 19141013 | |
dc.identifier.other | ID 19141014 | |
dc.identifier.uri | http://hdl.handle.net/10361/13987 | |
dc.description | This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2019. | en_US |
dc.description | Cataloged from PDF version of thesis. | |
dc.description | Includes bibliographical references (pages 30). | |
dc.description.abstract | A portfolio is a collection of stocks made from different companies, the number
of stocks can range from 10 to 30 depending on expected return by the investors.
Portfolio management is finding the right group of stocks to invest in with detailed
risk and return assessment. Finding the right combination is easier said than done,
we opted to work with S&P 500 data set. We filter the data set picking the top
10 stocks from each sector based on different criteria, using Markowitz portfolio
theory, we generate random portfolios and compare between them on the basis of
Voaltility and Sharpe ratio, a ratio generated from return and risk. When plotting
all the portfolios a curve is generated called the efficient frontier from which we can
select an optimum portfolio based on volatility and return. We then compare our
generated portfolio which is dynamic based on the requirements by looking at the
most recent stock market data and determine the accuracy for future prediction. | en_US |
dc.description.statementofresponsibility | Souvik Kundu | |
dc.description.statementofresponsibility | Mustaqim Khan | |
dc.description.statementofresponsibility | Faisal Rahman | |
dc.format.extent | 30 pages | |
dc.language.iso | en | en_US |
dc.publisher | Brac University | en_US |
dc.rights | Brac University theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. | |
dc.subject | Portfolio management | en_US |
dc.subject | S&P 500 | en_US |
dc.subject | Markowitz model | en_US |
dc.subject | Sharpe ratio | en_US |
dc.subject | Efficient frontier | en_US |
dc.subject | Volatility | en_US |
dc.subject | Expected return | en_US |
dc.title | Advanced portfolio management using markowitz portfolio theory | en_US |
dc.type | Thesis | en_US |
dc.contributor.department | Department of Computer Science and Engineering, Brac University | |
dc.description.degree | B. Computer Science | |