The volatility of Bitcoin returns and its correlation to financial markets

Nhi N.Y. VO, Guandong XU

Research output: Chapter in Book/Report/Conference proceedingChapters

14 Citations (Scopus)

Abstract

The 2008 financial crisis had scattered incredulity around the globe regarding traditional financial systems, which made investors and non-financial customers turn to other alternative such as digital banking systems. The existence and development of blockchain technology make cryptocurrency in recent years believably become a complete alternative to traditional ones. Bitcoin is the world's first peer-to-peer and decentralized digital cash system initiated by Nakamoto [1]. Though being the most prominent cryptocurrency, Bitcoin has not been a legal trading currency in various countries. Its exchange rate has appeared to be an exceptionally high-risk portfolio with extreme volatility, which requires a more detailed evaluation before making any decision. This paper utilizes knowledge of statistics for financial time series and machine learning to (i) fit the parametric distribution and (ii) model and forecast the volatility of Bitcoin returns, and (iii) analyze its correlation to other financial market indicators. The fitted parametric time series model significantly outperforms other standard models in explaining the stylized facts and statistical variances in the behavior of Bitcoin returns. The model forecast also outperforms some machine learning methodologies, which would benefit policy makers, banks and financial investors in trading activities for both long-term and short-term strategies. Copyright © 2017 IEEE.

Original languageEnglish
Title of host publicationProceedings of 4th International Conference on Behavioral, Economic, and Socio-Cultural Computing, BESC 2017
Place of PublicationUSA
PublisherIEEE
Pages1-6
ISBN (Electronic)9781538623657
DOIs
Publication statusPublished - 2017

Citation

Vo, N. N. Y., & Xu, G. (2017). The volatility of Bitcoin returns and its correlation to financial markets. In Proceedings of 4th International Conference on Behavioral, Economic, and Socio-Cultural Computing, BESC 2017 (pp. 1-6). IEEE. https://doi.org/10.1109/BESC.2017.8256365

Keywords

  • Bitcoin
  • Cryptocurrency
  • Volatility modeling
  • Statistical finance

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