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dc.contributor.advisorTichý, Tomáš
dc.contributor.authorZhou, Yuchun
dc.date.accessioned2021-11-08T12:19:29Z
dc.date.available2021-11-08T12:19:29Z
dc.date.issued2021
dc.identifier.otherOSD002
dc.identifier.urihttp://hdl.handle.net/10084/145481
dc.description.abstractWith the continuous development of the financial market, financial products, funds and other professional investment products have become important tools for investors to enter the capital market. These products are essentially an investment portfolio, so how to accurately evaluate the investment portfolio is an important subject faced by investors. However, in reality, investment is often a dynamic and constantly adjusted multi-stage process, and it is not reasonable to pay attention to the evaluation method of the final result only. Meanwhile, investment in different stages is correlated with each other. In order to make a reasonable evaluation of this kind of investment portfolio, it is necessary to comprehensively consider the performance of each stage and the relationship between stages. Therefore, it is of great significance to construct a reasonable dynamic portfolio efficiency evaluation model. The objective of this thesis is to form a practical guiding way of asset selection by using two distinct investment strategies: static investment strategy and dynamic investment strategy. Different investment groups have different expectations on the performance of asset portfolios due to their different investment capabilities and risk tolerance, so there are various types of optimal asset portfolios. The primary goal of the optimal portfolio set by this paper is to minimize the risk and volatility of the portfolio, to seek a stable rate of return, and then to choose a portfolio with the highest expected rate of return within an acceptable range of low risk as the optimal portfolio. Generally speaking, static investment strategy is based on the current point in time and conducts asset allocation according to the acquired information about asset volatility, expected return and so on. In a static investment strategy, once the asset allocation proportion is determined, no matter what happens to the market, the asset allocation proportion will not be changed or corrected before the maturity of the portfolio. Dynamic investment strategies are the opposite of this asset allocation approach. Under the dynamic investment strategy, the asset allocation weights will be regularly changed or revised in a specific interval and at a certain frequency according to the changes of market situation and asset information. In short, a static investment strategy determines the optimal asset allocation at the time the decision is made. However, dynamic investment strategy will periodically modify the portfolio based on market changes, so this investment strategy determines the dynamic optimal portfolio for each interval. The argument for static versus dynamic investment strategy is about application performance and efficiency. Theoretically speaking, dynamic investment strategy seems to be better than static investment strategy, but it cannot be proved without empirical analysis that the return rate of the portfolio under dynamic investment strategy is higher than the return performance of the portfolio under static investment strategy. Moreover, because dynamic investment strategies require asset allocation modifications and adjustments at defined intervals, it naturally takes more time, effort, and expense than static investment strategies. From the perspective of investment efficiency, the static investment strategy is likely to be higher than the dynamic investment strategy. Therefore, so as to make the detailed comparison of static investment strategy and dynamic strategy from the portfolio return and asset allocation efficiency and find out the more suitable method for asset allocation, the thesis will select 30 real stocks’ daily closed prices as a data source and evaluate the performances of both static and dynamic strategies. There are daily closed prices of these stocks from 2010 to 2020, and data from the previous 10 years will be used for asset allocation, data from the last year will be used to measure the performance of static and dynamic investments and to compare the two strategies.en
dc.description.abstractWith the continuous development of the financial market, financial products, funds and other professional investment products have become important tools for investors to enter the capital market. These products are essentially an investment portfolio, so how to accurately evaluate the investment portfolio is an important subject faced by investors. However, in reality, investment is often a dynamic and constantly adjusted multi-stage process, and it is not reasonable to pay attention to the evaluation method of the final result only. Meanwhile, investment in different stages is correlated with each other. In order to make a reasonable evaluation of this kind of investment portfolio, it is necessary to comprehensively consider the performance of each stage and the relationship between stages. Therefore, it is of great significance to construct a reasonable dynamic portfolio efficiency evaluation model.cs
dc.format.extent4749096 bytes
dc.format.mimetypeapplication/pdf
dc.language.isoen
dc.publisherVysoká škola báňská – Technická univerzita Ostravacs
dc.subjectStock portfolios, Static investment, Dynamic investment, Mean-variance model, GARCH model, Geometric Brownian motionen
dc.subjectStock portfolios, Static investment, Dynamic investment, Mean-variance model, GARCH model, Geometric Brownian motioncs
dc.titleAnalysis of Static and Dynamic Investment Strategiesen
dc.title.alternativeAnalysis of Static and Dynamic Investment Strategiescs
dc.typeDiplomová prácecs
dc.contributor.refereeGuo, Haochen
dc.date.accepted2021-08-31
dc.thesis.degree-nameIng.
dc.thesis.degree-levelMagisterský studijní programcs
dc.thesis.degree-grantorVysoká škola báňská – Technická univerzita Ostrava. Ekonomická fakultacs
dc.description.department154 - Katedra financícs
dc.thesis.degree-programFinancecs
dc.description.resultvelmi dobřecs
dc.identifier.senderS2751
dc.identifier.thesisZHO0016_EKF_N0412A050005_2021
dc.rights.accessopenAccess


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