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Fintech Theories and Its Applications in Emerging Markets

A Study of Bitcoin-Based Intraday Volatility Forecasting for Cross-Market Spreads

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References

  • Aalborg, H. A., P. Molnár, and J. E. de Vries. 2019. What can explain the price, volatility and trading volume of Bitcoin? Finance Research Letters 29:255–65. doi:10.1016/j.frl.2018.08.010.
  • Brauneis, A., and R. Mestel. 2018. Price discovery of cryptocurrencies: Bitcoin and beyond. Economics Letters 165:58–61. doi:10.1016/j.econlet.2018.02.001.
  • Burnside, C. 2019. Exchange rates, interest parity, and the carry trade. Oxford Research Encyclopedia of Economics and Finance. doi:10.1093/acrefore/9780190625979.013.315.
  • Cheah, E. T., and J. Fry. 2015. Speculative bubbles in Bitcoin markets? An empirical investigation into the fundamental value of Bitcoin. Economics Letters 130:32–36. doi:10.1016/j.econlet.2015.02.029.
  • Cheah, J. E. T., D. Luo, Z. Zhang, and M.-C. Sung. 2022. Predictability of bitcoin returns. The European Journal of Finance 28 (1):66–85. doi:10.1080/1351847X.2020.1835685.
  • Chen, Z., C. Li, and W. Sun. 2020. Bitcoin price prediction using machine learning: An approach to sample dimension engineering. Journal of Computational and Applied Mathematics 365:112395. doi:10.1016/j.cam.2019.112395.
  • Choi, J. H., and S. Suh. 2021. A filtered currency carry trade. The North American Journal of Economics and Finance 58:101472. doi:10.1016/j.najef.2021.101472.
  • Christoffersen, P. F. 1998. Evaluating interval forecasts. International Economic Review 841–62. doi:10.2307/2527341.
  • Demir, E., G. Gozgor, C. K. M. Lau, and Vigne S. A. 2018. Does economic policy uncertainty predict the Bitcoin returns? An empirical investigation. Finance Research Letters 26:145–49. doi:10.1016/j.frl.2018.01.005.
  • Dupuy, P. 2021. Risk-adjusted return managed carry trade. Journal of Banking & Finance 129:106172. doi:10.1016/j.jbankfin.2021.106172.
  • Dyhrberg, A. H., S. Foley, and J. Svec. 2018. How investible is Bitcoin? Analyzing the liquidity and transaction costs of Bitcoin markets. Economics Letters 171:140–43. doi:10.1016/j.econlet.2018.07.032.
  • Fang, L., E. Bouri, R. Gupta, and D. Roubaud. 2019. Does global economic uncertainty matter for the volatility and hedging effectiveness of Bitcoin? International Review of Financial Analysis 61:29–36. doi:10.1016/j.irfa.2018.12.010.
  • Figá-Talamanca, G., S. Focardi, and M. Patacca. 2021. Common dynamic factors for cryptocurrencies and multiple pair-trading statistical arbitrages. Decisions in Economics and Finance 44 (2):863–82. doi:10.1007/s10203-021-00318-x.
  • Garman, M. B., and M. J. Klass. 1980. On the estimation of security price volatilities from historical data. Journal of Business 67–78. https://www.jstor.org/stable/2352358.
  • Hansen, P. R., and A. Lunde. 2005. A forecast comparison of volatility models: Does anything beat a GARCH (1, 1)? Journal of Applied Econometrics 20 (7):873–89. doi:10.1002/jae.800.
  • Jareño, F., M. D. L. O. González, M. Tolentino, and K. Sierra. 2020. B1A quantile regression and NARDL analysis. Resources Policy 67:101666. doi:10.1016/j.resourpol.2020.101666.
  • Jiang, Y., H. Nie, and W. Ruan. 2018. Time-varying long-term memory in Bitcoin market. Finance Research Letters 25:280–84. doi:10.1016/j.frl.2017.12.009.
  • Karavias, Y., P. K. Narayan, and J. Westerlund. 2022. Structural breaks in interactive effects panels and the stock market reaction to COVID-19. Journal of Business & Economic Statistics 1–14. doi:10.1080/07350015.2022.2053690.
  • Kristoufek, L. 2018. On Bitcoin markets (in) efficiency and its evolution. physica A: Statistical mechanics and its applications. 503:257–62. doi:10.1016/j.physa.2018.02.161.
  • Kupiec, P. H. 1995. Techniques for verifying the accuracy of risk measurement models. Division of Research and Statistics, Division of Monetary Affairs, Federal Reserve Board. doi:10.3905/jod.1995.407942.
  • Li, Z., H. Dong, C. Floros, A. Charemis, and P. Failler. 2022. Re-examining bitcoin volatility: A CAViaR-based approach. Emerging Markets Finance and Trade 58 (5):1320–38. doi:10.1080/1540496X.2021.1873127.
  • Liu, W.-Y., B. X. Sun, and M. J. Wang. 2016. Volatility forecasting based on daily frequency prices. Journal of Management Sciences in China 19 (1):60–71. doi:10.3969/j.issn.1007-9807.2016.01.006.
  • Liu, M., G. Li, J. Li, Q. Zhu, and Y. Yao. 2021. Forecasting the price of Bitcoin using deep learning. Finance Research Letters 40:101755. doi:10.1016/j.frl.2020.101755.
  • Nair, S. T. G. 2021. Pairs trading in cryptocurrency market: A long-short story. Investment Management and Financial Innovations 18 (3):127–41. doi:10.21511/imfi.18(3).2021.12.
  • O’Dwyer, K. J., and D. Malone. 2014. Bitcoin mining and its energy footprint. 25th IET Irish Signals & Systems Conference 2014 and 2014 China-Ireland International Conference on Information and Communications Technologies (ISSC 2014/CIICT 2014), 280–285 doi:10.1049/cp.2014.0699.
  • Parkinson, M. 1980. The extreme value method for estimating the variance of the rate of return. Journal of Business 61–65. https://www.jstor.org/stable/2352357.
  • Rogers, L. C. G., and S. E. Satchell. 1991. Estimating variance from high, low and closing prices. The Annals of Applied Probability 504–12. https://www.jstor.org/stable/2959703.
  • Ryu, D. 2011. Intraday price formation and bid-ask spread components: A new approach using a cross-market model. Journal of Futures Markets 31 (12):1142–69. doi:10.1002/fut.20533.
  • Sahoo, P. K., and B. N. Rath. 2022. COVID-19 pandemic and bitcoin returns: Evidence from time and frequency domain causality analysis. Asian Economics Letters 3 (Early View). doi:10.46557/001c.37014.
  • Sarkodie, S. A., M. Y. Ahmed, and T. Leirvik. 2022. Trade volume affects bitcoin energy consumption and carbon footprint. Finance Research Letters 102977. doi:10.1016/j.frl.2022.102977.
  • Sensoy, A. 2019. The inefficiency of Bitcoin revisited: A high-frequency analysis with alternative currencies. Finance Research Letters 28:68–73. doi:10.1016/j.frl.2018.04.002.
  • Sha, Y., and W. Song. 2021. Can Bitcoin hedge belt and road equity markets? Finance Research Letters 42:102129. doi:10.1016/j.frl.2021.102129.
  • Shen, D., A. Urquhart, and P. Wang. 2019. Does twitter predict Bitcoin? Economics Letters 174:118–22. doi:10.1016/j.econlet.2018.11.007.
  • Tessari, C. 2020. Common idiosyncratic volatility and carry trade returns. Available at SSRN. 3730582. DOI: 10.2139/ssrn.3730582.
  • Usman, N., and K.N. Nduka. 2022. Announcement effect of COVID-19 on cryptocurrencies. Asian Economics Letters 3 (Early View):29953. doi:10.46557/001c.29953.
  • Vidal-Tomás, D. 2022. All the frequencies matter in the Bitcoin market: An efficiency analysis. Applied Economics Letters 29 (3):212–18. doi:10.1080/13504851.2020.1861196.
  • Vidal-Tomás, D., and A. Ibañez. 2018. Semi-strong efficiency of Bitcoin. Finance Research Letters 27:259–65. doi:10.1016/j.frl.2018.03.013.
  • Yermack, D.2015. Is Bitcoin a real currency? An economic appraisal. In Handbook of Digital Currency, 31–43. Academic Press. doi:10.1016/B978-0-12-802117-0.00002-3.
  • Yip, H. Y. K., D. Michayluk, L. Prather, and L.-A. Woo. 2002. Decomposing the bid-ask spread of a common stock: A cross-market approach. Business papers 66. http://epublications.bond.edu.au/business_pubs/66.

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