Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor | Faculty of Business | en_US |
| dc.contributor.advisor | Wei, Steven (AF) | en_US |
| dc.creator | Pookayaporn, Kriangkai | - |
| dc.identifier.uri | https://theses.lib.polyu.edu.hk/handle/200/12218 | - |
| dc.language | English | en_US |
| dc.publisher | Hong Kong Polytechnic University | en_US |
| dc.rights | All rights reserved | en_US |
| dc.title | The study of the “big tech” effect and the “big tech” risk premium | en_US |
| dcterms.abstract | Low interest rate environment has been a key driver that drove asset prices over a decade, especially for risky asset classes such as stocks. Since the great financial crisis in 2008, the US stock market has been performing very well compared to others. However, since 2014, the winners of the winners of the US stock market are the Big Tech stocks, with listed companies that were classified as technology-oriented companies being in the focus of investors. These tech stocks outperformed other sectors by large margins. This dominance stems from the fact that tech giants are able to penetrate their product offering into large aspect of our daily life, especially in more recent years | en_US |
| dcterms.abstract | This thesis studies the superior returns behavior in Big Tech stocks for the period of 2014 to 2021. It aims to explain the returns anomaly by studying the returns behavior of the NYSE FANG+ Index as the proxy of Big Tech portfolio through perspective described as follows. First of all, it determines the excess returns that were achieved during 2014 to 2021. It tests the excess returns through the classic Fama-French models, both three factors and five factors. Moreover, additional factors are added to confirm the result. It is clear that Big Tech stocks achieved excess returns over the risk-free rate of 10.4% per annum. | en_US |
| dcterms.abstract | Secondly, the thesis also studies the relation of the returns of Big Tech stocks and returns of cryptocurrencies. It examines cryptocurrencies, aggregated through the Bloomberg Galaxy Cryptocurrency Index, and also individual cryptocurrencies like Bitcoin and Ethereum. Even though there is no relationship founded when examining the returns of cryptocurrencies with the Fama French model, there is evidence that Big Tech and cryptocurrencies are related to a certain degree. | en_US |
| dcterms.abstract | Last but not least, the thesis creates Big Tech factors from the NYSE FANG+ Index portfolio. I determine that the Big Tech factor effects and influences price movements of other non-NYSE FANG+ stocks. Evidently, I found that there is an influence not only in technology-oriented stocks but also in others classification of stocks as well. Moreover, it also provides estimated risk premium embedded through Fama-Macbeth approach. | en_US |
| dcterms.abstract | In addition, recent political and economic events that arose in the beginning of 2022 already ended this long period of low interest rates. Recent volatility rose from economic uncertainty, which led to most asset classes to tumble, except for commodities. This presents future opportunities to study how Big Tech reacts when encountering unfavorable economic situations. The following study of this period of volatility will enable the achievement of clearer results in the future. | en_US |
| dcterms.extent | xvi, 179 pages : color illustrations | en_US |
| dcterms.isPartOf | PolyU Electronic Theses | en_US |
| dcterms.issued | 2022 | en_US |
| dcterms.educationalLevel | DFinTech | en_US |
| dcterms.educationalLevel | All Doctorate | en_US |
| dcterms.LCSH | Stocks | en_US |
| dcterms.LCSH | Stocks -- Prices | en_US |
| dcterms.LCSH | High technology industries -- Finance | en_US |
| dcterms.LCSH | Risk | en_US |
| dcterms.LCSH | Hong Kong Polytechnic University -- Dissertations | en_US |
| dcterms.accessRights | restricted access | en_US |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| 6737.pdf | For All Users (off-campus access for PolyU Staff & Students only) | 3.5 MB | Adobe PDF | View/Open |
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