Is Bitcoin business income or speculative bubble? Unconditional vs. conditional frequency domain analysis

Bouoiyour, Jamal and Selmi, Refk and Tiwari, Aviral (2014): Is Bitcoin business income or speculative bubble? Unconditional vs. conditional frequency domain analysis.

Abstract

The present study addresses one of the most problematic phenomena: Bitcoin price. We explore the Granger causality for two relationships (Bitcoin price and transactions; Bitcoin price and investors’ attractiveness) from a frequency domain perspective using Breitung and Candelon’s (2006) approach. Intuitively, this research gauges empirically the causal links between these variables unconditionally on the one hand and conditionally to the Chinese stock market and the processing power of Bitcoin network on the other hand. The observed outcomes reveal some differences with respect to the frequencies involved, highlighting the complexity of assessing what Bitcoin looks like and the difficulty to gain clearer insights into this nascent crypto-currency. Beyond the nuances of short-, medium- and long-run frequencies, this paper confirms the extremely speculative nature of Bitcoin without neglecting its usefulness in economic reasons (trade transactions). The consideration of the Chinese market index and the hash rate has led to solid and unambiguous findings connecting further Bitcoin to speculation.

• Item Type: MPRA Paper
• Language: English
• Keywords: Bitcoin price; transactions; investors’ attractiveness; unconditional frequency domain; conditional frequency domain.
• Subjects: C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General; E - Macroeconomics and Monetary Economics > E4 - Money and Interest Rates; E - Macroeconomics and Monetary Economics > E4 - Money and Interest Rates > E44 - Financial Markets and the Macroeconomy

References

Aguiar-Conraria, L. & Soares, M-J. (2011) The continuous wavelet transform: A primer. NIPE working paper n°16, University of Minho.

Askitas, N., Zimmermann, K. & Klaus F. (2009) Google econometrics and unemployment forecasting.” Applied Economics Quarterly 55, 107–120.

Barber, S., Boyen, X., Shi, E. & Uzun, E. (2012) Bitter to Better-How to Make Bitcoin a Better Currency. In A.D. Keromytis (ed.), Financial Cryptography and Data Security. Vol. 7397 of Lecture Notes in Computer Science, 399-414, Berlin/Heidelberg: Springer. Bodart, V. & Candelon, B., (2009) Evidence of interdependence and contagion using a frequency domain framework. Emerging Markets Review, 10 (2), 140-150. Bornholdt, S. and Sneppen, K. (2014) Do Bitcoins make the world go around? On the dynamics of competing crypto-currencies. https://www.researchgate.net/publication/261100860_Do_Bitcoins_make_the_world_go_round_On_the_dynamics_of_competing_crypto-currencies.

Bouoiyour, J. & Selmi, R. (2014) What Bitcoin looks like? Gaining insight into Bitcoin Phenomenon, working paper CATT, University of Pau.

Bouoiyour, J., Selmi, R., Tiwari, A-K. & Olayeni, O-R., (2014) Measuring Bitcoin Price: Multiscale Analysis via Empirical Mode Decomposition, working paper CATT, University of Pau.

Breitung, J., & Candelon, B. (2006) Testing for short and long-run causality: a frequency domain approach. Journal of Econometrics 132, 363-378.

Buchholz, M., Delaney, J., Warren, J. & Parker, J. (2012) Bits and Bets, Information, Price Volatility, and Demand for Bitcoin. http://www.bitcointrading.com/pdf/bitsandbets.pdf

Ciaian, P., Rajcaniova, M. & Kancs, D. (2014) The Economics of BitCoin Price Formation. http://arxiv.org/ftp/arxiv/papers/1405/1405.4498.pdf

Geweke, J. (1982) Measurement of linear dependence and feedback between multiple time series. Journal of American Statistical Association, 77, 304-324.

Geweke, J. (1984) Inference and causality in economic time series models. Handbook of Econometrics, in: Griliches, Z. andIntriligator, M.D. (ed.), Handbook of Econometrics, edition 1, 2, chapter 19, 1101-1144.

Glaster, F., Kai, Z., Haferkorn, M., Weber, M. & Sieiring, M. (2014) Bitcoin - asset or currency? Revealing users’hidden intentions. Twenty Second European Conference on Information Systems. http://ecis2014.eu/E-poster/files/0917-file1.pdf

Granger, C.W.J. (1969) Investigation causal relations by econometric models and cross-spectral methods. Econometrica, 37, 424-438.

Grinberg, R. (2011) BitCoin: An Innovative Alternative Digital Currency. Hastings Science & Technology Law Journal, 4, 159-208.

Kristoufek, L. (2013), BitCoin meets Google Trends and Wikipedia: Quantifying the relationship between phenomena of the Internet era. Scientific Reports, 3 (3415), 1-7.

Kristoufek, L. (2014) What are the main drivers of the Bitcoin price? Evidence from wavelet coherence analysis. .http://arxiv.org/pdf/1406.0268.pdf

Kroll, J., Davey, I. & Felten, E. (2013) The Economics of Bitcoin Mining, or Bitcoin in the Presence of Adversaries. http://weis2013.econinfosec.org/papers/KrollDaveyFeltenWEIS2013.pdf

Kulkarni, R., Haynes, K., Stough, R. & Paelinck, J.H.P., (2009) Forecasting housing prices with Google econometrics. Unpublished working paper. Lemmens, A., Croux, C. & Dekimpe, M.G. (2008) Measuring and Testing Granger causality over the spectrum: An Application to European Production Expectation Surveys. International Journal of Forecasting, 24, 414-431. Moore, T. & Chitristin, N. (2013) Beware the Middleman: Empirical Analysis of Bitcoin-Exchange Risk. Financial Cryptography and Data Security, 7859, 25-33. Ng, E.K. & Chan, J.C. (2012) Geophysical Applications of Partial Wavelet Coherence and Multiple Wavelet Coherence. American Meteological Society, December. DOI: 10.1175/JTECH-D-12-00056.1

Palombizio E. and Morris, I. (2012) Forecasting Exchange Rates using Leading Economic Indicators. Open Access Scientific Reports,1 (8), 1-6.

Piskorec, P., Antulov-Fantulin, N., Novak, P.K., Mozetic, I., Grcar, M., Vodenska, I. & Šmuc, T. (2014) News Cohesiveness: an Indicator of Systemic Risk in Financial Markets. http://arxiv.org/pdf/1402.3483v1.pdf

Tiwari, A.K., Arouri, M. & Teulon, F. (2014) Oil prices and trade balance: A frequency domain analysis for India. Economics Bulletin, 34(2), 663-680.

Vlastakis, Nikolaos, Markellos & Raphael N., (2010) Information demand and stock market volatility. Journal of Banking and Finance, 36 (6), 1808-1821.

Vosen, S. & Schmidt, T. (2011) Forecasting private consumption: survey-based indicators vs. Google Trends. Journal of Forecasting 30, 565–578.

Yermack, D. (2011) Is Bitcoin a Real Currency? An economic appraisal. NBER Working Paper No. 19747. http://www.nber.org/papers/w19747.