Study and Research on the Six-Year Process of Bitcoin Price and Return

Document Type : Research Paper

Authors

1 Department of Finance, College of Management and Economics, International Finance, Science and Research Branch, Islamic Azad University, Tehran, Iran

2 Associate Professor in Accounting, Head of Accounting Department, Islamic Azad University- Karaj Branch, Iran

3 Assistance Professor, Faculty of e- learning, Islamic Azad University

10.22034/amfa.2019.577434.1126

Abstract

The purpose of this study, is create a challenge and discussion concerning the existence of information about the Bitcoin price and return, which suggests the relationship of information and the strong performance it. The information trends are available at different time periods and the summary data related to the statistical descriptions for the price and return index are also discussed. In this paper we show a significant correlation between the price trend and return in the Bitcoin that has been confirmed by various statistical methodology. Using statistical tests and reviewing trends and relationships between the variables, planning can be done to invest in it and its performance or inefficiency can be tested. The results of this research shows a significant and positive relationship between the price and return of Bitcoin.

Keywords

Main Subjects

References

[1] Aurelio F. B., The inefficiency of Bitcoin revisited: A dynamic approach, Economics Letters, 2017,161, P.1-4. Doi: https://doi.org/10.1016/j.econlet.2017.09.013
[2] Balcilar, M., Bouri, E., Gupta, R., Roubaud, D., Can volume predict Bitcoin returns and volatility? A quan-tiles-based approach, Economic Modelhing, 2017, 64, P. 74–81. Doi:10.1016/j.econmod.2017.03.019.
[3] Bariviera, A.F., Basgall, M.J., Hasperué, W., Naiouf, M., Some stylized facts of the Bitcoin marke, Physics, A, 2017, 484, P. 82–90. Doi:10.1016/j.physa.2017.04.159.
[4] Blau, B. M., Price dynamics and speculative trading in Bitcoin, Research in International Business and Finance, 2017, 5, P. 41-55. Doi: 10.1016/j.ribaf.2017.05.010
[5] Bouri, E., Azzi, G., Dyhrberg, A.H., On the return-volatility relationship in the Bitcoin market around the price crash of 2013. Economics: Open-Assessment E-Journal, 2017, 11, P.1–16. Doi: http://dx.doi.org/10.2139/ ssrn.28 69855
[6] Bouri, E., Molnr, P., Azzi, G., Roubaud, D., Hagfors, L., On the hedge and safe haven properties of Bitcoin Is it really more than a diversifier?,Financial Research Letters., 2017, 20, P.192–198. Doi: 10.1016/j.frl.2016.09.025.
[7] Chaim P., Laurini M., Is Bitcoin a bubble?, Physica A: Statistical Mechanics and its Applications, 2019, 517, P. 222-232. Doi: 10.1016/j.physa.2018.11.031.
[8] Cheunge, A., Su, J. J., Roca, E., Crypto-currency bubbles: An application of the Philips-Shi-Yu methodlogy on Mt. Gox Bitcoin price. Applied Economics, 2015, 47, P. 1-15. Doi: 10.1080/00036846.2015.1005827
[9] Donier, J., Bouchaud, J.-P., Why do markets crash? Bitcoin data offers unprecedented insights, PLOS ONE, 2015, 10, P. 1–11. Doi: https://doi.org/10.1371/journal.pone.0139356.
[10] Dyhrberg A., Foley S., Svec J., How investible is Bitcoin? Analyzing the liquidity and transaction costs of Bitcoin markets, Economics Letters, 2018, 171, P. 140-143. Doi: https://doi.org/10.1016/j.econlet.2018.07.032
[11] Fama, E.F., Efficient capital markets: A review of theory and empirical work, Journal of Finance, 1970, 25, P. 383-417. Doi:10.2307/2325486.
[12] Faruk A., Demirb E., Gozgord G., Keung C., Lau M,Effects of the geopolitical risks on Bitcoin returns and volatility,Research in International Business and Finance,2019, 47, P.511-518.Doi:10.1016/j.ribaf.2018.09.011.
[13] Garcia, D., Tessone, C.J., Mavrodiev, P., Perony, N., The digital trace of bubble: Feedback cycle between sicio-economic signal in Bitcoin economy, Journal of Research. Society Interface, 2014, 12, P. 6-23. Doi: 10.109 8/rsif.2014.0623
[14] George S., Atsalaki I., Pasiouras F., Zopounidis C.,  Bitcoin price forecasting with neuro-fuzzy techniques,European Journal of Operational Research, 2019, In press. Doi: https://doi.org/10.1016/j.ejor.2019.01.040.
[15] Henecic, A., Gourieroux, C., Noncausal autoregressive model in application to Bitcoin/USD exchange rate, In: proceeding of the 7th Financial Risk International forum, Paris, France. 2014. Doi:10.1007/978-3-319-13449-9_2.
[16] Kim., T., On the transaction cost of Bitcoin. Finance. Research Letters. 2017, 23, P. 300-305. Doi: 10.1016/j.frl.2017.07.014
[17] Kristoufek, L., Bitcoin meets Google Trends and Wikipedia: Quantifying the relationship between phenomena of the internet era, Scientefic Reports, 2013, 15, P. 15-34. Doi:10.1038/srep03415
 
[18] Mashhadizadeh M., Dastgir M.,  Salahshour S., Economic Appraisal of Investment Projects in Solar Energy under Uncertainty via Fuzzy Real Option Approach (Case Study: a 2-MW Photovoltaic Plant in South of Isfahan, Iran), Advances in Mathematical Finance and Applications, 2018, 3(4),P. 37-50. Doi:10.22034/amfa. 2019.574157.1116.
[19] Mardani M., Sarlakb A., The Effect of Investment on the Financing of Listed Companies in Tehran Stock Exchange, Advances in Mathematical Finance and Applications, 2018, 3(1), P. 79-89 Doi:10.22034/amfa.2018. 539136.
[20] Mohammadtalebi B., Mohammad taleb M., Jahangiri M., Eshghiaraghi M., Investigating the Effect of Internal Rate of Return on Cash Re-cycling on the Abnormal Returns of Companies Accepted in Tehran Stock Exchange, Advances in Mathematical Finance and Applications, 2018, 3(3), P.1-10. Doi:10.22034/amfa. 2018.544942.
[21] Moor, T., Christin, N., Beware  the middleman: Empirical analysis of Bitcoin exchange risk. In: Financial Cryptography and Data Security. In: Lecture Note in Computer Science, 2013, 12,  P. 25-23. Doi:10.1007/978-3-642-39884-1_3.
[22] Nadarajah, S., Chu, J., On the inefficiency of Bitcoin, Economic Letters, 2017, 150, P. 6-9. Doi: 10.1016/j.econlet.2016.10.033.
[23] Nakamoto, S., Bitcoin: A peer-to-peer electronic cash system. https://Bitcoin. org/Bitcoin.pdf/ , 2009, 27, P. 12-25.
[24] Pasandideh Parsa B., Sarraf F., Financial Statement Comparability and the Expected Crash Risk of Stock Prices, Advances in Mathematical Finance and Applications, 2018, 3(3), P.77-93. Doi: 10.22034/amfa.2018 .544951.
[25] Schuettel, P.,The Concise Fintech Compendium. Fribourg, School of Management Fribourg. Switzerland, 2017.
[26] Serinaldi, F., Use and misuse of some Hurst parameter estimators applied to stationary and non-stationary financial time series. Physics, 2010,  389, P. 2770–2781. Doi:10.1016/j.physa.2010.02.044
[27] Symitsia E., Chalvatzisb K.,  The economic value of Bitcoin: A portfolio analysis of currencies, gold, oil and stocks, Research in International Business and Finance,2018,48, P. 97-110. Doi:10.1016/j.ribaf.2018.12.001
[28] Rezaei N., Elmi Z., Behavioral Finance Models and Behavioral Biases in Stock Price Forecasting, Advances in Mathematical Finance and Applications, 2018, 3(4), P. 51-63. Doi:10.22034/amfa.2019 .576127.1118.
[29] Urquhart, A., The inefficiency of Bicoin, Economic Letters, 2016, 148, P. 80-82. Doi:10.1016/j.econlet.201   6.09.019
Advances in Mathematical Finance and Applications
Volume 4, Issue 1
March 2019
Pages 45-54

Files

History

  • Receive Date: 05 November 2018
  • Revise Date: 24 January 2019
  • Accept Date: 16 February 2019
  • First Publish Date: 01 March 2019

Share

How to cite

Statistics