簡易檢索 / 詳目顯示
| 研究生： |
任魯姆 Lumta Ramadani |
|---|---|
| 論文名稱： |
比特加密貨幣指數之間的波動度外溢效果的實證研究 Analysing the volatility spillovers between cryptocurrency indices |
| 指導教授： |
蔡政憲
Tsai, Jason |
| 口試委員: |
林姿婷
Lin, Tzu-Ting 曾毓英 Tseng, Yu-Ying |
| 學位類別： |
碩士
Master |
| 系所名稱： |
商學院 - 國際經營管理英語碩士學位學程(IMBA) International MBA Program College of Commerce(IMBA) |
| 論文出版年： | 2022 |
| 畢業學年度： | 110 |
| 語文別： | 英文 |
| 論文頁數： | 50 |
| 中文關鍵詞： | 比特幣 、加密貨幣 、以太坊 、GARCH模型 、波動度外溢 |
| 外文關鍵詞： | Bitcoin, Cryptocurrencies, Ethereum, GARCH models, Volatility Spillovers |
| DOI URL： | http://doi.org/10.6814/NCCU202200763 |
| 相關次數： | 點閱：253 下載：19 |
| 分享至: |
| 查詢本校圖書館目錄 查詢臺灣博碩士論文知識加值系統 勘誤回報 |
無
The research analyses the volatility spillovers of the S&P Bitcoin and the S&P Ethereum Indexes as a hot research topic nowadays. This market is growing, thus it is important for investors and policy makers to understand the price volatility and make better investment and policy decisions. The data is extracted online from the S&P Cryptocurrency Index from the period April 2016 to April 2022. The data was chosen before COVID-19, and the impact of the virus on these two indices up to April, 2022. The results show a volatility clustering between these two indices. Moreover, the news in the S&P Bitcoin Index price returns impact largely the future volatility of the S&P Index price returns, and vice versa. There is a lack of literature for the Ethereum market, and researchers need to conduct research on this yet new market. Therefore, we hope that our thesis empirical research can influence future researchers to conduct more research in this field.
1. Introduction of the cryptocurrency market 1
2. The overview of cryptocurrency market 4
2.1 The price discovery on Bitcoin market 4
2.2 The price discovery on ether 6
3. Research purpose 6
4. Literature review 8
4.1 Speculative bubbles in Bitcoin market 8
4.2 Market efficiency 9
4.3 The volatility of cryptocurrency price returns 10
4.4 Diversification benefits of the cryptocurrencies 12
4.5 Regulation in the cryptocurrency market 13
5. Data and Methodology 14
5.1 Description of data 14
5.2 Unit Root Test 15
5.3 ARCH LM Test 16
6. Econometric models 16
6.1 The GARCH (1,1) Model 17
6.2 Diagonal BEKK Multivariate GARCH Model 18
7. Empirical Results and Interpretations 19
8. Conclusion 28
9. References 29
10. Appendices 33
10.1 Appendix A: Unit Root Test 33
10.2 Appendix B: Descriptive statistics 35
10.3 Appendix C Heteroscedasticity Test 40
10.4 Appendix D: GARCH(1,1) model 45
10.5 Appendix E: Multivariate Diagonal BEKK GARCH 49
Alexander, C., Choi, J., Massie, H. and Sohn, S., 2020. Price Discovery and Microstructure in Ether Spot and Derivative Markets. SSRN Electronic Journal,.Auer, R. and Claessens, S., 2018. Regulating cryptocurrencies: assessing market reactions. BIS Quarterly Review September.
Baur, D., Hong, K. and Lee, A., 2018. Bitcoin: Medium of exchange or speculative assets?. Journal of International Financial Markets, Institutions and Money, 54, pp.177-189.
Begu, L.S., Spătaru, S. and Marin, E., 2012. Investigating the Evolution of RON/EUR Exchange Rate: The Choice of Appropriate Model. Journal of Social and Economic Statistics, 1(2), pp.23-39.
Brandvold, M., Molnár, P., Vagstad, K. and Andreas Valstad, O., 2015. Price discovery on Bitcoin exchanges. Journal of International Financial Markets, Institutions and Money, 36, pp.18-35.
Bouoiyour, J. and Selmi, R., 2015. What does Bitcoin look like?. Annals of Economics & Finance, 16(2).
Borri, N. and Shakhnov, K., 2020. Regulation spillovers across cryptocurrency markets. Finance Research Letters, 36, p.101333.
Bouri, E., Molnár, P., Azzi, G., Roubaud, D. and Hagfors, L., 2017. On the hedge and safe haven properties of Bitcoin: Is it really more than a diversifier?. Finance Research Letters, 20, pp.192-198.
Casals, J., Jerez, M. and Sotoca, S., 2000. Exact smoothing for stationary and non-stationary time series. International Journal of Forecasting, 16(1), pp.59-69.
Chokor, A. and Alfieri, E., 2021. Long and short-term impacts of regulation in the cryptocurrency market. The Quarterly Review of Economics and Finance, 81, pp.157-173.
Ciaian, P., Rajcaniova, M. and Kancs, d., 2016. The economics of BitCoin price formation. Applied Economics, 48(19), pp.1799-1815.
Cheah, E. and Fry, J., 2015. Speculative bubbles in Bitcoin markets? An empirical investigation into the fundamental value of Bitcoin. Economics Letters, 130, pp.32-36.
Corbet, S., Lucey, B., Urquhart, A. and Yarovaya, L., 2019. Cryptocurrencies as a financial asset: A systematic analysis. International Review of Financial Analysis, 62, pp.182-199.
Corbet, S., Meegan, A., Larkin, C., Lucey, B. and Yarovaya, L., 2018. Exploring the dynamic relationships between cryptocurrencies and other financial assets. Economics Letters, 165, pp.28-34.
Corbet, S., Larkin, C., Lucey, B., 2020. The contagion effects of the covid-19 pandemic: Evidence from gold and cryptocurrencies. Finance Research Letters 101554.
Dyhrberg, A., 2016. Bitcoin, gold and the dollar – A GARCH volatility analysis. Finance Research Letters, 16, pp.85-92.
Engle, R. and Kroner, K., 1995. Multivariate Simultaneous Generalised ARCH. Econometric Theory, 11(1), pp.122-150.
Fama, E.F., 1970. Efficient market hypothesis: A review of theory and empirical work. Journal of Finance, 25(2), pp.28-30.
Ferretti, S. and D'Angelo, G., 2019. On the Ethereum blockchain structure: A complex networks theory perspective. Concurrency and Computation: Practice and Experience, 32(12).
Frisby, D., 2014. Bitcoin: the future of money?. Unbound Publishing.
Georgoula, I., Pournarakis, D., Bilanakos, C., Sotiropoulos, D. and Giaglis, G., 2015. Using Time-Series and Sentiment Analysis to Detect the Determinants of Bitcoin Prices. SSRN Electronic Journal.
Geng, J., Chen, F., Ji, Q. and Liu, B., 2021. Network connectedness between natural gas markets, uncertainty and stock markets. Energy Economics, 95, p.105001.
Huang, Y., Duan, K. and Mishra, T., 2021. Is Bitcoin really more than a diversifier? A pre- and post-COVID-19 analysis. Finance Research Letters, 43, p.102016.
Katsiampa, P., Corbet, S. and Lucey, B., 2019. Volatility spillover effects in leading cryptocurrencies: A BEKK-MGARCH analysis. Finance Research Letters, 29, pp.68-74.
Katsiampa, P., 2017. Volatility estimation for Bitcoin: A comparison of GARCH models. Economics Letters, 158, pp.3-6.
Katsiampa, P., 2019. Volatility co-movement between Bitcoin and Ether. Finance Research Letters, 30, pp.221-227.
Khuntia, S. and Pattanayak, J., 2018. Adaptive market hypothesis and evolving predictability of bitcoin. Economics Letters, 167, pp.26-28.
Kristoufek, L., 2013. BitCoin meets Google Trends and Wikipedia: Quantifying the relationship between phenomena of the Internet era. Scientific Reports, 3(1).
Kroll, J.A., Davey, I.C. and Felten, E.W., 2013, June. The economics of Bitcoin mining, or Bitcoin in the presence of adversaries. In Proceedings of WEIS (Vol. 2013, No. 11).
Kondo, M., Oliva, G., Jiang, Z., Hassan, A. and Mizuno, O., 2020. Code cloning in smart contracts: a case study on verified contracts from the Ethereum blockchain platform. Empirical Software Engineering, 25(6), pp.4617-4675.
Li, X. and Wang, C., 2017. The technology and economic determinants of cryptocurrency exchange rates: The case of Bitcoin. Decision Support Systems, 95, pp.49-60.
Nakamoto, S., 2008. Bitcoin: A Peer-to-Peer Electronic Cash System. SSRN Electronic Journal, [online] Available at: <https://bitcoin.org/bitcoin>.
Özdemir, O., 2022. Cue the volatility spillover in the cryptocurrency markets during the COVID-19 pandemic: evidence from DCC-GARCH and wavelet analysis. Financial Innovation, 8(1).
Pagnottoni, P. and Dimpfl, T., 2019. Price discovery on Bitcoin markets. Digital Finance, 1(1-4), pp.139-161.
Panagiotidis, T., Stengos, T. and Vravosinos, O., 2018. On the determinants of bitcoin returns: A LASSO approach. Finance Research Letters, 27, pp.235-240.
M., Poongodi., Sharma, A., V., V., Bhardwaj, V., Sharma, A., Iqbal, R. and Kumar, R., 2020. Prediction of the price of Ethereum blockchain cryptocurrency in an industrial finance system. Computers & Electrical Engineering, 81, p.106527.
Sjölander, P., 2010. A stationary unbiased finite sample ARCH-LM test procedure. Applied Economics, 43(8), pp.1019-1033.
Tiwari, A., Kumar, S. and Pathak, R., 2019. Modelling the dynamics of Bitcoin and Litecoin: GARCH versus stochastic volatility models. Applied Economics, 51(37), pp.4073-4082.
Urquhart, A., 2016. The inefficiency of Bitcoin. Economics Letters, 148, pp.80-82.
Urquhart, A. and Zhang, H., 2019. Is Bitcoin a hedge or safe haven for currencies? An intraday analysis. International Review of Financial Analysis, 63, pp.49-57.
Weber, B., 2016. Bitcoin and the legitimacy crisis of money. Cambridge Journal of Economics, 40(1), pp.17-41.
