Application of Matlab in Portfolio Optimization
| dc.contributor.advisor | Kresta, Aleš | |
| dc.contributor.author | Chen, Shufan | |
| dc.contributor.referee | Valecký, Jiří | |
| dc.date.accepted | 2018-05-28 | |
| dc.date.accessioned | 2018-06-26T08:01:33Z | |
| dc.date.available | 2018-06-26T08:01:33Z | |
| dc.date.issued | 2018 | |
| dc.description.abstract | There exists a rule in investing activities, which is “don’t put all eggs in one basket”. It’s because of the existence of this rule, the portfolio optimization becomes important. As we all know, portfolio optimization is a process of selecting the best portfolio that meet the investor’s requirement. The main idea of the portfolio optimization is how investors make a choice between the risk and return. In general, the investors want to maximum the return at a low-level risk, but in fact, the rise in return is also followed by the increase of risk. The portfolio optimization was firstly proposed by Markowitz (1952), who proposed that if the investor need to make a decision between two portfolios with the same return, all investors will choose the portfolio with less risky. | en |
| dc.description.abstract | There exists a rule in investing activities, which is “don’t put all eggs in one basket”. It’s because of the existence of this rule, the portfolio optimization becomes important. As we all know, portfolio optimization is a process of selecting the best portfolio that meet the investor’s requirement. The main idea of the portfolio optimization is how investors make a choice between the risk and return. In general, the investors want to maximum the return at a low-level risk, but in fact, the rise in return is also followed by the increase of risk. The portfolio optimization was firstly proposed by Markowitz (1952), who proposed that if the investor need to make a decision between two portfolios with the same return, all investors will choose the portfolio with less risky. | cs |
| dc.description.department | 154 - Katedra financí | cs |
| dc.description.result | velmi dobře | cs |
| dc.format.extent | 4161436 bytes | |
| dc.format.mimetype | application/pdf | |
| dc.identifier.other | OSD002 | |
| dc.identifier.sender | S2751 | |
| dc.identifier.thesis | CHE0026_EKF_N6202_6202T010_2018 | |
| dc.identifier.uri | http://hdl.handle.net/10084/127523 | |
| dc.language.iso | en | |
| dc.publisher | Vysoká škola báňská - Technická univerzita Ostrava | cs |
| dc.rights.access | openAccess | |
| dc.subject | Portfolio optimization | en |
| dc.subject | Risk | en |
| dc.subject | Return | en |
| dc.subject | Matlab | en |
| dc.subject | Naive strategy | en |
| dc.subject | Mean-variance model | en |
| dc.subject | Random mode | en |
| dc.subject | Max Sharpe ratio | en |
| dc.subject | Wealth | en |
| dc.subject | Sharpe ratio | en |
| dc.subject | Maximum Drawdown | en |
| dc.subject | Stock price | en |
| dc.subject | Portfolio optimization | cs |
| dc.subject | Risk | cs |
| dc.subject | Return | cs |
| dc.subject | Matlab | cs |
| dc.subject | Naive strategy | cs |
| dc.subject | Mean-variance model | cs |
| dc.subject | Random mode | cs |
| dc.subject | Max Sharpe ratio | cs |
| dc.subject | Wealth | cs |
| dc.subject | Sharpe ratio | cs |
| dc.subject | Maximum Drawdown | cs |
| dc.subject | Stock price | cs |
| dc.thesis.degree-branch | Finance | cs |
| dc.thesis.degree-grantor | Vysoká škola báňská - Technická univerzita Ostrava. Ekonomická fakulta | cs |
| dc.thesis.degree-level | Magisterský studijní program | cs |
| dc.thesis.degree-name | Ing. | |
| dc.thesis.degree-program | Hospodářská politika a správa | cs |
| dc.title | Application of Matlab in Portfolio Optimization | en |
| dc.title.alternative | Využití Matlabu při optimalizaci portfolia | cs |
| dc.type | Diplomová práce | cs |
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