Exploring the dynamics of Bitcoin’s price: a Bayesian structural time series approach

Antonopoulos, A. M. (2014). Mastering Bitcoin: Unlocking digital cryptocurrencies. Newton: O’Reilly Media, Inc.

Athey, S., Parashkevov, I., Sarukkai, V., & Xia, J. (2016). Bitcoin pricing, adoption, and usage: theory and evidence (No. 17-033). IDEAS working paper series from RePEc. St. Louis. Retrieved from https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2826674 .

Baek, C., & Elbeck, M. (2015). Bitcoins as an investment or speculative vehicle? A first look. Applied Economics Letters 22(1), 30–34. https://doi.org/10.1080/13504851.2014.916379 .

Baur, D. G., & Lucey, B. M. (2010). Is Gold a Hedge or a safe haven? An analysis of stocks, bonds and gold. Financial Review, 45(2), 217–229. https://doi.org/10.1111/j.1540-6288.2010.00244.x .

Baur, D. G., & McDermott, T. K. (2010). Is gold a safe haven? International evidence. Journal of Banking and Finance, 34(8), 1886–1898.

Bjerg, O. (2016). How is Bitcoin money? Theory, Culture and Society, 33(1), 53–72. https://doi.org/10.1177/0263276415619015 .

Böhme, R., Christin, N., Edelman, B., & Moore, T. (2015). Bitcoin: Economics, technology, and governance. Journal of Economic Perspectives, 29(2), 213–238. https://doi.org/10.1257/jep.29.2.213 .

Bouoiyour, J., & Selmi, R. (2016). Bitcoin: A beginning of a new phase? Economics Bulletin, 36(3), 1430.

Bouoiyour, J. & Selmi, R. (2017). Are Trump and Bitcoin Good Partners? https://arxiv.org/abs/1703.00308 .

Bouri, E., Gupta, R., Tiwari, A. K., & Roubaud, D. (2017). Does Bitcoin hedge global uncertainty? Evidence from wavelet-based quantile-in-quantile regressions. Finance Research Letters. https://doi.org/10.1016/j.frl.2017.02.009 .

Brodersen, K. H., Gallusser, F., Koehler, J., Remy, N., & Scott, S. L. (2015). Inferring causal impact using bayesian structural time-series models. Annals of Applied Statistics, 9(1), 247–274. https://doi.org/10.1214/14-AOAS788 .

Cheah, E. T., & Fry, J. (2015). Speculative bubbles in Bitcoin markets? An empirical investigation into the fundamental value of Bitcoin. Economics Letters, 130, 32–36. https://doi.org/10.1016/j.econlet.2015.02.029 .

Chipman, H., George, E. I., Mcculloch, R. E., Clyde, M., Foster, D. P., & Stine, R. (2014). The practical implementation of Bayesian Model selection. Lecture Notes—Monograph Series. IMS. https://doi.org/10.1214/lnms/1215540964 .

Ciaian, P., Rajcaniova, M., & Kancs, D. (2016a). The digital agenda of virtual currencies: Can BitCoin become a global currency? Information Systems and e-Business Management, 14(4), 883–919. https://doi.org/10.1007/s10257-016-0304-0 .

Ciaian, P., Rajcaniova, M., & Kancs, D. (2016b). The economics of Bitcoin price formation. Applied Economics, 48(19), 1799–1815. https://doi.org/10.1080/00036846.2015.1109038 .

Ciner, C., Gurdgiev, C., & Lucey, B. M. (2013). Hedges and safe havens: An examination of stocks, bonds, gold, oil and exchange rates. International Review of Financial Analysis, 29, 202–211.

Durbin, J., & Koopman, S. J. (2012). Time series analysis by state space methods. Oxford: Oxford University Press. https://doi.org/10.1017/cbo9781107415324.004 .

Dwyer, G. P. (2015). The economics of Bitcoin and similar private digital currencies. Journal of Financial Stability, 17, 81–91. https://doi.org/10.1016/j.jfs.2014.11.006 .

Dyhrberg, A. H. (2016). Bitcoin, gold and the dollar—a GARCH volatility analysis. Finance Research Letters, 16, 85–92. https://doi.org/10.1016/j.frl.2015.10.008 .

Franco, P. (2014). Understanding Bitcoin: Cryptography, engineering and economics. Oxford: Wiley.

Garcia, D., Tessone, C. J., Mavrodiev, P., & Perony, N. (2014). The digital traces of bubbles: Feedback cycles between socio-economic signals in the Bitcoin economy. Journal of the Royal Society Interface The Royal Society, 11(99), 16. https://doi.org/10.1098/rsif.2014.0623 .

George, E. I., & McCulloch, R. E. (1993). Variable selection via Gibbs sampling. Journal of the American Statistical Association, 88(423), 881–889. https://doi.org/10.1080/01621459.1993.10476353 .

Georgoula, I., Pournarakis, D. Bilanakos, C., Sotiropoulos, D. & Giaglis, G. (2015). Using time-series and sentiment analysis to detect the determinants of Bitcoin prices. https://doi.org/10.2139/ssrn.2607167 .

Glaser, F., Zimmermann, K., Haferkorn, M., Weber, M. C., & Siering, M. (2014). Bitcoin—asset or currency? Revealing users’ hidden intentions. In Twenty Second European Conference on Information Systems (pp. 1–14).

Greenland, S., Maclure, M., Schlesselman, J. J., Poole, C., & Morgenstern, H. (1991). Standardized regression coefficients: A further critique and review of some alternatives. Epidemiology, 2(5), 387–392.

Halaburda, H. (2016). Beyond Bitcoin. The economics of digital currencies. New York: New York University. https://doi.org/10.1057/9781137506429 .

Harvey, A. C. (1990). Forecasting, structural time series models and the Kalman filter. London: Cambridge University Press.

Hoerl, A. E., & Kennard, R. W. (1970). Ridge regression: Biased estimation for nonorthogonal problems. Technometrics, 12(1), 55–67. https://doi.org/10.1080/00401706.1970.10488634 .

Ishwaran, H., & Rao, J. S. (2005). Spike and Slab variable selection: Frequentist and Bayesian strategies. The Annals of Statistics, 33(2), 730–773. https://doi.org/10.1214/009053604000001147 .

Kaminski, J. (2014). Nowcasting the Bitcoin market with Twitter signals. Cambridge. Retrieved from http://arxiv.org/abs/1406.7577 .

Kate, R. J. (2016). Using dynamic time warping distances as features for improved time series classification. Data Mining and Knowledge Discovery, 30(2), 283–312. https://doi.org/10.1007/s10618-015-0418-x .

Kim, Y. B., Kim, J. G., Kim, W., Im, J. H., Kim, T. H., Kang, S. J., et al. (2016). Predicting fluctuations in cryptocurrency transactions based on user comments and replies. PLoS One, 11(8), 1–18. https://doi.org/10.1371/journal.pone.0161197 .

Koop, G., Poirier, D. J., & Tobias, J. L. (2007). Bayesian econometric methods. Cambridge: Cambridge University Press.

Kristoufek, L. (2015). What are the main drivers of the Bitcoin price? Evidence from wavelet coherence analysis. PLoS One, 10(4), 1–19. https://doi.org/10.1371/journal.pone.0123923 .

Luther, W. J. (2016). Bitcoin and the future of digital payments. Independent Review, 20(3), 397–404. https://doi.org/10.2139/ssrn.2631314 .

Merlise, A. (1999). Bayesian model averaging and model search strategies. Bayesian Statistics, 6, 157–185.

Mitchell, T. J., & Beauchamp, J. J. (1988). Bayesian variable selection in linear regression. Journal of the American Statistical Association, 83(404), 1023. https://doi.org/10.2307/2290129 .

Nakamoto, S. (2008). Bitcoin: A peer-to-peer electronic cash system. Retrieved from: https://bitcoin.org/bitcoin.pdf .

Nimon, K. F., & Oswald, F. L. (2013). Understanding the results of multiple linear regression. Organizational Research Methods, 16(4), 650–674. https://doi.org/10.1177/1094428113493929 .

Owusu, R. A., Mutshinda, C. M., Antai, I., Dadzie, K. Q., & Winston, E. M. (2016). Which UGC features drive web purchase intent? A Spike-and-Slab Bayesian variable selection approach. Internet Research, 26(1), 22–37. https://doi.org/10.1108/intr-06-2014-0166 .

Parmigiani, G., Petrone, S., & Campagnoli, P. (2009). Dynamic linear models with R. New York: Springer.

Raskin, M., & Yermack, D. (2016). Digital Currencies, descentralized ledgers, and the future of Central Banking (NBER Working Paper No. 22238). Cambridge.

Ročková, V., & George, E. I. (2014). Negotiating multicollinearity with Spike-and-Slab priors. Metron, 72(2), 217–229. https://doi.org/10.1007/s40300-014-0047-y .

Rogojanu, A., & Badea, L. (2014). The issue of competing currencies. Case study—Bitcoin. Theoretical and Applied Economics, 21(1), 103–114.

Scott, S. L., & Varian, H. (2013). Bayesian variable selection for nowcasting economic time series. NBER Working Paper Series. Cambridge. https://doi.org/10.3386/w19567 .

Shumway, R. H., & Stoffer, D. S. (2010). Time series analysis and its applications: With R examples. Berlin: Springer.

Simser, J. (2015). Bitcoin and modern alchemy: In code we trust. Journal of Financial Crime, 22(1), 155–169. https://doi.org/10.1108/JFC-11-2013-0067 .

Smith, G. (2017). How a China Crackdown Caused Bitcoin’s Price to Plunge. http://fortune.com/2017/01/05/bitcoin-plunge-china-currency/ . Retrieved 29 June 2018.

Tibshirani, R. (1996). Regression shrinkage and selection via the Lasso. Journal of the Royal Statistical Society 58(1), 267–288.

Vaughan, N. (2016). Comparing and combining time series trajectories using dynamic time warping. Procedia Computer Science, 96(January), 465–474. https://doi.org/10.1016/j.procs.2016.08.106 .

West, M., & Harrison, J. (2006). Bayesian forecasting and dynamic models (Second). New York: Springer Science & Business Media. https://doi.org/10.1007/b98971 .

Wisniewska, A. (2015). Bitcoin as an example of a virtual currency. Institute of Economic Research Working Papers. Torun. Retrieved from: https://www.researchgate.net/profile/Anna_Wisniewska10/publication/317304290_Bitcoin_as_an_example_of_virtual_currency/links/593122caa6fdcc89e78ca1be/Bitcoin-as-an-example-of-virtual-currency.pdf .

Xi, R., Li, Y., Yiming, H., et al. (2016). Bayesian quantile regression based on the empirical likelihood with Spike and Slab priors. Bayesian Analysis, 11(3), 821–855.

Yelowitz, A., & Wilson, M. (2015). Characteristics of Bitcoin users: An analysis of Google search data. Applied Economics Letters, 4851(January), 1–7. https://doi.org/10.1080/13504851.2014.995359 .

Yermack, D. (2013). Is Bitcoin a real currency? An economic appraisal. National Bureau of Economic Research.

Yildirim, I. (2012). Bayesian inference: Gibbs sampling. Technical Note, University of Rochester, New York.