| 摘要(英) |
The thesis aims to explore the performance of the cryptocurrency market as an investment, specifically examining the potential for better returns compared to the stock market by investing in Bitcoin (BTC), Ether (ETH), Tether (USDT), and Dogecoin (DOGE). The sample period spans from June 1, 2017, to December 31, 2021.
First, the thesis employs the "Cryptocurrency 3-Factor Model" to investigate the impact of three cryptocurrency-specific risk factors in cryptocurrency market. And find whether there have any excess returns. Furthermore, using the "First-Order Stochastic Dominance (FSD), Second-Order Stochastic Dominance (SSD), and Almost First-Order Stochastic Dominance (AFSD)", to examines whether the four cryptocurrencies outperform the MSCI World Index (wMSCI) of the stock market and analyzes the potential dominance relationships among the four cryptocurrencies. Lastly, the thesis utilizes the Omega index to obtain a prioritized ranking of investment in the five assets across the entire sample period and pre- and post-pandemic periods.
The empirical results show that, based on the cryptocurrency 3-factor model, BTC, ETH, USDT, and DOGE all had negative excess returns before the pandemic. After the pandemic, only Tether maintained a negative excess return, while the excess returns of other currencies were not significantly different from zero. Through the traditional FSD and SSD methods, as well as the AFSD method, we can obtain the following information. The results reveal that investing in the four cryptocurrencies does not dominate the wMSCI, and there is no dominance relationship among the four cryptocurrencies themselves. Furthermore, this study utilizes the Omega index to rank the five assets and determine their investment priorities. DOGE is identified as a favorable investment target throughout the entire sample period and postpandemic period, while USDT is the least preferred investment among the five assets in all research periods. |
| 參考文獻 |
王馨平，2018，加密貨幣市場投資者行為之研究，國立成功大學會計研究所碩士論文。
毛慕耘，2022，加密貨幣與金融市場之價格關聯和外溢效果，國立台北大學資訊管理研究所碩士論文。
李語潔，2020，加密貨幣的定價與金融壓力及不確定性之關聯，國立中央大學產業經濟研究所碩士論文。
Bouri, E., Lucey, B., & Roubaud, D. (2020). Cryptocurrencies and the downside risk in equity investments. Finance Research Letters, 33, 101211.
Hu, A. S., Parlour, C. A., & Rajan, U. (2019). Cryptocurrencies: Stylized facts on a new investible instrument. Financial Management, 48 (4), 1049-1068.
Ji, Q., Bouri, E., Lau, C. K. M., & Roubaud, D. (2019). Dynamic connectedness and integration in cryptocurrency markets. International Review of Financial Analysis, 63, 257-272.
Levy, H., Leshno, M., & Leibovitch, B. (2010). Economically relevant preferences for all observed epsilon. Annals of Operations Research, 176 (1), 153-178.
Liu, Y., & Tsyvinski, A. (2021). Risks and returns of cryptocurrency. Review of Financial Studies, 34 (6), 2689-2727.
Lin, Z. Y. (2021). Investor attention and cryptocurrency performance. Finance Research Letters, 40, 101702.
Liu, Y., Tsyvinski, A., & Wu, X. (2022). Common risk factors in cryptocurrency. Journal of Finance, 77 (2), 1133-1177.
Menkhoff, L., Sarno, L., Schmeling, M., & Schrimpf, A. (2012). Currency momentum strategies. Journal of Financial Economics, 106 (3), 660-684.
Shen, D., Urquhart, A., & Wang, P. (2020). A three-factor pricing model for cryptocurrencies. Finance Research Letters, 34, 101248.
Wang, H., Wang, X., Yin, S., & Ji, H. (2022). The asymmetric contagion effect between stock market and cryptocurrency market. Finance Research Letters, 46, 102345.
Wasiuzzaman, S., & Rahman, H. S. W. H. A. (2021). Performance of gold-backed cryptocurrencies during the COVID-19 crisis. Finance Research Letters, 43, 101958. |
[Endnote RIS 格式]
[相關文章]
[文章引用]
[完整記錄]
[館藏目錄]
[檢視]
plurk
funp
live
udn
HD
myshare
netvibes
friend
youpush
delicious
baidu
Google bookmarks
del.icio.us
hemidemi
facebook
twitter
google
reddit