| Full text | |
| Author(s): |
Total Authors: 4
|
| Affiliation: | [1] Univ Sao Paulo, Syst Dynam Grp, BR-13635900 Pirassununga, SP - Brazil
[2] Inacio Jr, Jr., C. M. C., Univ Sao Paulo, Syst Dynam Grp, BR-13635900 Pirassununga, SP - Brazil
[3] Inst Engn, Polytechn Porto, Rua Dr Antonio B Almeida 431, P-4249015 Porto - Portugal
Total Affiliations: 3
|
| Document type: | Journal article |
| Source: | JOURNAL OF ADVANCED RESEARCH; v. 32, n. SI, p. 85-98, SEP 2021. |
| Web of Science Citations: | 1 |
| Abstract | |
Introduction: Cryptocurrencies have been attracting the attention from media, investors, regulators and academia during the last years. In spite of some scepticism in the financial area, cryptocurrencies are a relevant subject of academic research. Objectives: In this paper, several tools are adopted as an instrument that can help market agents and investors to more clearly assess the cryptocurrencies price dynamics and, thus, guide investment decisions more assertively while mitigating risks. Methods: We consider three methods, namely the Auto-Regressive Integrated Moving Average (ARIMA), Auto-Regressive Fractionally Integrated Moving Average (ARFIMA) and Detrended Fluctuation Analysis, and three indices given by the Hurst and Lyapunov exponents or the Fractal Dimension. This information allows assessing the behaviour of the time series, such as their persistence, randomness, predictability and chaoticity. Results: The results suggest that, except for the Bitcoin, the other cryptocurrencies exhibit the characteristic of mean reverting, showing a lower predictability when compared to the Bitcoin. The results for the Bitcoin also indicate a persistent behavior that is related to the long memory effect. Conclusions: The ARFIMA reveals better predictive performance than the ARIMA for all cryptocurrencies. Indeed, the obtained residual values for the ARFIMA are smaller for the auto and partial auto correlations functions, as well as for confidence intervals. (C) 2021 The Authors. Published by Elsevier B.V. on behalf of Cairo University. (AU) | |
| FAPESP's process: | 17/13815-3 - Fractional dynamics of ethanol price series in Brazil |
| Grantee: | Sergio Adriani David |
| Support Opportunities: | Program for Research on Bioenergy (BIOEN) - Regular Program Grants |
| FAPESP's process: | 17/15517-0 - Dynamic behavior in the fractional scope of agricultural commodities price series vis-a-vis ethanol prices |
| Grantee: | Claudio Marcio Cassela Inacio Junior |
| Support Opportunities: | Scholarships in Brazil - Scientific Initiation |