Tâm lý thị trường, bất ổn kinh tế và biến động tiền mã hoá
Từ khóa:
Bất ổn chính sách, biến động giá, tâm lý thị trường, tiền mã hoá, SARIMAX, GARCHXTóm tắt
Tiền mã hóa hiện này vẫn được xem là khoản đầu tư có tính rủi ro cao, do biên độ dao động lớn và biến động liên tục. Do đó, việc dự báo chính xác và hiểu được các yếu tố quyết định mức độ biến động của tiền mã hoá đặc biệt quan trọng đối với các nhà đầu tư. Nghiên cứu áp dụng mô hình ARIMAX và GARCHX để dự báo độ biến động của tiền mã hoá bằng cách sử dụng các chỉ số tài chính truyền thống, tâm lý thị trường, và bất ổn kinh tế. Nghiên cứu thu thập dữ liệu theo ngày của sáu đồng tiền mã hoá trong giai đoạn 2021-2023. Kết quả cho thấy mô hình GARCHX có hiệu quả vượt trội so với mô hình ARIMAX trong ước lượng biến động tiền mã hoá.
Tài liệu tham khảo
Apergis, N., & Apergis, E. (2022), ‘The role of Covid-19 for Chinese stock returns: evidence from a GARCHX model’, Asia-Pacific Journal of Accounting & Economics, 29(5), 1175-1183.
Baker, S. R., Bloom, N., & Davis, S. J. (2016), ‘Measuring economic policy uncertainty’, The Quarterly Journal of Economics, 131(4), 1593-1636.
Blau, B. M. (2017), ‘Price dynamics and speculative trading in bitcoin’, Research in International Business and Finance, 41, 493-499.
Bollerslev, T. (1986), ‘Generalized autoregressive conditional heteroskedasticity’, Journal of Econometrics, 31(3), 307-327.
Box, G. E. P., & Jenkins, G. M. (1970), Time Series Analysis: Forecasting and Control, San Francisco: Holden-Day.
Conrad, C., Custovic, A., & Ghysels, E. (2018), ‘Long-and short-term cryptocurrency volatility components: A GARCH-MIDAS analysis’, Journal of Risk and Financial Management, 11(2), 23.
Corbet, S., Lucey, B., & Yarovaya, L. (2018), ‘Datestamping the Bitcoin and Ethereum bubbles’, Finance Research Letters, 26, 81-88.
Cheng, H.-P., & Yen, K.-C. (2020). ‘The relationship between the economic policy uncertainty and the cryptocurrency market’. Finance Research Letters, 35, 101308.
Da, Z., Engelberg, J., & Gao, P. (2015), ‘The sum of all FEARS investor sentiment and asset prices’, The Review of Financial Studies, 28(1), 1-32.
Demir, E., Gozgor, G., Lau, C. K. M., & Vigne, S. A. (2018), ‘Does economic policy uncertainty predict the Bitcoin returns? An empirical investigation’, Finance Research Letters, 26, 145-149.
Dias, I. K., Fernando, J. M. R., & Fernando, P. N. D. (2022), ‘Does investor sentiment predict bitcoin return and volatility? A quantile regression approach’, International Review of Financial Analysis, 84, 102383.
Engle, R. (1995), ARCH: Selected readings, Oxford University Press.
Engle, R. F. (1982). Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation. Econometrica, 50(4), 987-1007.
Fang, L., Bouri, E., Gupta, R., & Roubaud, D. (2019), ‘Does global economic uncertainty matter for the volatility and hedging effectiveness of Bitcoin?’, International Review of Financial Analysis, 61, 29-36.
Ferreira, J., & Morais, F. (2023), ‘Predict or to be predicted? A transfer entropy view between adaptive green markets, structural shocks and sentiment index’, Finance Research Letters, 56, 104100.
Gong, J., Wang, G.-J., Zhou, Y., Zhu, Y., Xie, C., & Foglia, M. (2023), ‘Spreading of cross-market volatility information: Evidence from multiplex network analysis of volatility spillovers’, Journal of International Financial Markets, Institutions and Money, 83, 101733.
Guégan, D., & Renault, T. (2021), ‘Does investor sentiment on social media provide robust information for Bitcoin returns predictability?’, Finance Research Letters, 38, 101494.
Güler, D. (2023), ‘The Impact of investor sentiment on bitcoin returns and conditional volatilities during the era of Covid-19’, Journal of Behavioral Finance, 24(3), 276-289.
Husted, L., Rogers, J., & Sun, B. (2020), ‘Monetary policy uncertainty’, Journal of Monetary Economics, 115, 20-36.
Liu, J., & Serletis, A. (2019), ‘Volatility in the cryptocurrency market’, Open Economies Review, 30(4), 779-811.
Merton, R. C. (1980), ‘On estimating the expected return on the market: An exploratory investigation’, Journal of Financial Economics, 8(4), 323-361.
Mokni, K. (2021), ‘When, where, and how economic policy uncertainty predicts Bitcoin returns and volatility? A quantiles-based analysis’, The Quarterly Review of Economics and Finance, 80, 65-73.
Nasekin, S., & Chen, C. Y. H. (2020), ‘Deep learning-based cryptocurrency sentiment construction’, Digital Finance, 2(1), 39-67.
Nelson, D. B. (1992), ‘Filtering and forecasting with misspecified ARCH models I: Getting the right variance with the wrong model’, Journal of Econometrics, 52(1-2), 61-90.
Nouir, J. B., & Hamida, H. B. H. (2023), ‘How do economic policy uncertainty and geopolitical risk drive Bitcoin volatility?’, Research in International Business and Finance, 64, 101809.
Paule-Vianez, J., Prado-Román, C., & Gómez-Martínez, R. (2020), ‘Economic policy uncertainty and Bitcoin. Is Bitcoin a safe-haven asset?’, European Journal of Management and Business Economics, 29(3), 347-363.
Poon, S. H., & Granger, C. W. J. (2003), ‘Forecasting volatility in financial markets: A review’, Journal of Economic Literature, 41(2), 478-539.
Segnon, M., & Bekiros, S. (2020), ‘Forecasting volatility in bitcoin market’, Annals of Finance, 16(3), 435-462.
Shiller, R. J. (2020), Narrative Economics: How Stories Go Viral and Drive Major Economic Events, Princeton University Press.
Sifat, I. (2021), ‘On cryptocurrencies as an independent asset class: Long-horizon and COVID-19 pandemic era decoupling from global sentiments’, Finance Research Letters, 43, 102013.
Smuts, N. (2019), ‘What drives cryptocurrency prices? An investigation of Google trends and telegram sentiment’, ACM SIGMETRICS Performance Evaluation Review, 46(3), 131-134.
Taylor, S. J. (2008), Modelling financial time series, World Scientific.
Urquhart, A., & Lucey, B. (2022), ‘Crypto and digital currencies—nine research priorities’, Nature, 604(7904), 36-39.
Van Wijk, D. (2013), What can be expected from the BitCoin, Erasmus Universiteit Rotterdam, 18.
Wang, G.-J., Xie, C., Wen, D., & Zhao, L. (2019), ‘When Bitcoin meets economic policy uncertainty (EPU): Measuring risk spillover effect from EPU to Bitcoin’, Finance Research Letters, 31, 101431.
Wu, W., Tiwari, A. K., Gozgor, G., & Leping, H. (2021), ‘Does economic policy uncertainty affect cryptocurrency markets? Evidence from Twitter-based uncertainty measures’, Research in International Business and Finance, 58, 101478.
Yen, K.-C., & Cheng, H.-P. (2020). Economic policy uncertainty and cryptocurrency volatility. Finance Research Letters, 34, 101428.
Yermack, D. (2015), ‘Is Bitcoin a real currency? An economic appraisal’, In Handbook of digital currency (pp. 31-43), Academic Press.
Yousaf, I., Riaz, Y., & Goodell, J. W. (2023), ‘The impact of the SVB collapse on global financial markets: Substantial but narrow’, Finance Research Letters, 55(Part B), 103948.
Yu, M., Gao, R., Su, X., Jin, X., Zhang, H., & Song, J. (2019), ‘Forecasting Bitcoin volatility: The role of leverage effect and uncertainty’, Physica A: Statistical Mechanics and its Applications, 533, 120707.
