Neural Network for Valuing Bitcoin: Availability of Data, Code and Materials, Contributions by@cryptosovereignty
Neural Network for Valuing Bitcoin: Availability of Data, Code and Materials, Contributions
by Crypto Sovereignty Through Technology, Math & LuckMay 13th, 2024
Too Long; Didn't Read
This study considers a bivariate jump-diffusion model to describe Bitcoin price dynamics and the number of Google searches affecting the price.
This paper is available on arxiv under CC 4.0 license.
Authors:
(1) Edson Pindza, Tshwane University of Technology; Department of Mathematics and Statistics; 175 Nelson Mandela Drive OR Private Bag X680 and Pretoria 0001; South Africa [[email protected]];
(2) Jules Clement Mba, University of Johannesburg; School of Economics, College of Business and Economics and P. O. Box 524, Auckland Park 2006; South Africa [[email protected]];
(3) Sutene Mwambi, University of Johannesburg; School of Economics, College of Business and Economics and P. O. Box 524, Auckland Park 2006; South Africa [[email protected]];
(4) Nneka Umeorah, Cardiff University; School of Mathematics; Cardiff CF24 4AG; United Kingdom [[email protected]].
Table of Links
- Abstract and Introduction
- Methodology
- Neural Network Methodology
- Numerical results, implementation and discussion
- Conclusion, Acknowledgments, and Funding
- Availability of data, code and materials, Contributions and Declarations
- References
Availability of data, code and materials
Please contact the corresponding author for request.
Contributions
All authors contributed equally to the paper. All authors read and approved the final manuscript.
Declarations
Conflict of interest: All authors declare that they have no conflict of interest.
Ethical approval: This article does not contain any studies with human participants or animals performed by any of the authors.
L O A D I N G
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